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Ahmad RB, Anwar AW, Ali A, Fatima T, Moin M, Nazir A, Batool A, Shabir U. Pressure-dependent band gap engineering with structural, electronic, mechanical, optical, and thermal properties of CsPbBr 3: first-principles calculations. J Mol Model 2024; 30:270. [PMID: 39014125 DOI: 10.1007/s00894-024-06040-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Accepted: 06/21/2024] [Indexed: 07/18/2024]
Abstract
CONTEXT In the renewable industry, pressure-dependent CsPbBr3 perovskite has a lot of potential due to its exceptional properties. Present work revealed the mechanical stability of CsPbBr3 between 0 to 50 GPa. The bandgap of unstressed CsPbBr3 is 2.90 eV, indicating a direct bandgap. Band gap values decrease by increasing external pressure. CsPbBr3 structure showed a direct band gap from 0 to 35 GPa and in-direct from 40 to 50 GPa. The unit cell volume and lattice constants are substantially decreased. Mechanical parameters, i.e., Young's modulus, bulk modulus, anisotropy factor, shear modulus, and poison's ratio are obtained. Under ambient conditions, the mechanical properties of CsPbBr3 showed ductile behavior and with induced pressure, their ductility has significantly improved. By applying stresses ranging from 0 to 50 GPa, the considerable fluctuation in values of dielectric function (imaginary and real), absorption, reflectivity, loss function, refractive index (imaginary and real), and conductivity (imaginary and real), was also identified. When pressure rises, the optical parameters increase and drag in the direction of high energies. Response functions are used to predict the density of states and the phonon lattice dispersion to study the phonon properties. By using the quasi-harmonic Debye model, the thermal effect on the free energy, entropy, enthalpy, and heat capacity were predicted and compared. These results would be useful for theoretical research and indicate how external pressure significantly affects the physical characteristics of CsPbBr3 perovskites, which may open up new possibilities for use in optoelectronic, photonic, and solar cell applications. METHODS The structural, electrical, mechanical, optical, and thermal properties of cesium lead bromide (CsPbBr3) are investigated by applying external pressure from 0 to 50 GPa, using generalized gradient approximations (GGA) and Perdew-Burke-Ernzerhof (PBE) with CASTEP code built-in material studio by density functional theory (DFT).
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Affiliation(s)
- Rana Bilal Ahmad
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan.
| | - Abdul Waheed Anwar
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
| | - Anwar Ali
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
| | - Tehreem Fatima
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
| | - Muhammad Moin
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
| | - Amna Nazir
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
| | - Asma Batool
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
| | - Umer Shabir
- Department of Physics, Faculty of Nano Science and Technology, University of Engineering and Technology, Lahore, Pakistan
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Virumbrales C, Hernández-Ruiz R, Trigo-López M, Vallejos S, García JM. Sensory Polymers: Trends, Challenges, and Prospects Ahead. SENSORS (BASEL, SWITZERLAND) 2024; 24:3852. [PMID: 38931634 PMCID: PMC11207698 DOI: 10.3390/s24123852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024]
Abstract
In recent years, sensory polymers have evolved significantly, emerging as versatile and cost-effective materials valued for their flexibility and lightweight nature. These polymers have transformed into sophisticated, active systems capable of precise detection and interaction, driving innovation across various domains, including smart materials, biomedical diagnostics, environmental monitoring, and industrial safety. Their unique responsiveness to specific stimuli has sparked considerable interest and exploration in numerous applications. However, along with these advancements, notable challenges need to be addressed. Issues such as wearable technology integration, biocompatibility, selectivity and sensitivity enhancement, stability and reliability improvement, signal processing optimization, IoT integration, and data analysis pose significant hurdles. When considered collectively, these challenges present formidable barriers to the commercial viability of sensory polymer-based technologies. Addressing these challenges requires a multifaceted approach encompassing technological innovation, regulatory compliance, market analysis, and commercialization strategies. Successfully navigating these complexities is essential for unlocking the full potential of sensory polymers and ensuring their widespread adoption and impact across industries, while also providing guidance to the scientific community to focus their research on the challenges of polymeric sensors and to understand the future prospects where research efforts need to be directed.
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Affiliation(s)
- Cintia Virumbrales
- Departamento de Química, Facultad de Ciencias, Universidad de Burgos, 09001 Burgos, Spain; (M.T.-L.); (S.V.); (J.M.G.)
| | - Raquel Hernández-Ruiz
- Departamento de Química, Facultad de Ciencias, Universidad de Burgos, 09001 Burgos, Spain; (M.T.-L.); (S.V.); (J.M.G.)
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Lemmink IB, Straub LV, Bovee TFH, Mulder PPJ, Zuilhof H, Salentijn GI, Righetti L. Recent advances and challenges in the analysis of natural toxins. ADVANCES IN FOOD AND NUTRITION RESEARCH 2024; 110:67-144. [PMID: 38906592 DOI: 10.1016/bs.afnr.2024.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
Natural toxins (NTs) are poisonous secondary metabolites produced by living organisms developed to ward off predators. Especially low molecular weight NTs (MW<∼1 kDa), such as mycotoxins, phycotoxins, and plant toxins, are considered an important and growing food safety concern. Therefore, accurate risk assessment of food and feed for the presence of NTs is crucial. Currently, the analysis of NTs is predominantly performed with targeted high pressure liquid chromatography tandem mass spectrometry (HPLC-MS/MS) methods. Although these methods are highly sensitive and accurate, they are relatively expensive and time-consuming, while unknown or unexpected NTs will be missed. To overcome this, novel on-site screening methods and non-targeted HPLC high resolution mass spectrometry (HRMS) methods have been developed. On-site screening methods can give non-specialists the possibility for broad "scanning" of potential geographical regions of interest, while also providing sensitive and specific analysis at the point-of-need. Non-targeted chromatography-HRMS methods can detect unexpected as well as unknown NTs and their metabolites in a lab-based approach. The aim of this chapter is to provide an insight in the recent advances, challenges, and perspectives in the field of NTs analysis both from the on-site and the laboratory perspective.
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Affiliation(s)
- Ids B Lemmink
- Laboratory of Organic Chemistry, Wageningen University & Research, Wageningen, The Netherlands; Wageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands
| | - Leonie V Straub
- Laboratory of Organic Chemistry, Wageningen University & Research, Wageningen, The Netherlands; Wageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands
| | - Toine F H Bovee
- Wageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands
| | - Patrick P J Mulder
- Wageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands
| | - Han Zuilhof
- Laboratory of Organic Chemistry, Wageningen University & Research, Wageningen, The Netherlands; School of Pharmaceutical Sciences and Technology, Tianjin University, Tianjin, P.R. China
| | - Gert Ij Salentijn
- Laboratory of Organic Chemistry, Wageningen University & Research, Wageningen, The Netherlands; Wageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.
| | - Laura Righetti
- Laboratory of Organic Chemistry, Wageningen University & Research, Wageningen, The Netherlands; Wageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.
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Minami K, Zhou Y, Imamura G, Shiba K, Yoshikawa G. Sorption Kinetic Parameters from Nanomechanical Sensing for Discrimination of 2-Nonenal from Saturated Aldehydes. ACS Sens 2024; 9:689-698. [PMID: 38349676 DOI: 10.1021/acssensors.3c01888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Nanomechanical sensors have gained significant attention as promising platforms for artificial olfaction. Since sorption kinetic parameters that can be estimated from the sensing signals of nanomechanical sensors reflect the chemical and physicochemical interactions between the odorant and receptor material, the parameters can be utilized for the direct discrimination of each odorant. In this study, we demonstrated the discrimination of 20 vapors, including hydrocarbons, alcohols, organic acids, ketones, and aldehydes, which are reported as human body odor components, using the parameters extracted in the analytical solution of nanomechanical sensors based on sorption kinetics with viscoelastic behaviors. By using one of the specific nanomechanical sensors─membrane-type surface stress sensor─as a sensing unit, we successfully discriminated trans-2-nonenal known as an aging marker from other saturated aldehydes along with quantifying their concentrations.
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Affiliation(s)
- Kosuke Minami
- Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- International Center for Young Scientists (ICYS), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Yingcheng Zhou
- Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8571, Japan
| | - Gaku Imamura
- Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- Graduate School of Information Science and Technology, Osaka University, 1-2 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Kota Shiba
- Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Genki Yoshikawa
- Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8571, Japan
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Ma M, Yang X, Ying X, Shi C, Jia Z, Jia B. Applications of Gas Sensing in Food Quality Detection: A Review. Foods 2023; 12:3966. [PMID: 37959084 PMCID: PMC10648483 DOI: 10.3390/foods12213966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 11/15/2023] Open
Abstract
Food products often face the risk of spoilage during processing, storage, and transportation, necessitating the use of rapid and effective technologies for quality assessment. In recent years, gas sensors have gained prominence for their ability to swiftly and sensitively detect gases, making them valuable tools for food quality evaluation. The various gas sensor types, such as metal oxide (MOX), metal oxide semiconductor (MOS) gas sensors, surface acoustic wave (SAW) sensors, colorimetric sensors, and electrochemical sensors, each offer distinct advantages. They hold significant potential for practical applications in food quality monitoring. This review comprehensively covers the progress in gas sensor technology for food quality assessment, outlining their advantages, features, and principles. It also summarizes their applications in detecting volatile gases during the deterioration of aquatic products, meat products, fruit, and vegetables over the past decade. Furthermore, the integration of data analytics and artificial intelligence into gas sensor arrays is discussed, enhancing their adaptability and reliability in diverse food environments and improving food quality assessment efficiency. In conclusion, this paper addresses the multifaceted challenges faced by rapid gas sensor-based food quality detection technologies and suggests potential interdisciplinary solutions and directions.
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Affiliation(s)
- Minzhen Ma
- Information Technology Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; (M.M.); (X.Y.); (Z.J.); (B.J.)
- College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan 316004, China
| | - Xinting Yang
- Information Technology Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; (M.M.); (X.Y.); (Z.J.); (B.J.)
- Key Laboratory of Cold Chain Logistics Technology for Agro-Product, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
| | - Xiaoguo Ying
- College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan 316004, China
- Department of Agriculture, Food and Environment (DAFE), Pisa University, Via del Borghetto, 80, 56124 Pisa, Italy
| | - Ce Shi
- Information Technology Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; (M.M.); (X.Y.); (Z.J.); (B.J.)
- Key Laboratory of Cold Chain Logistics Technology for Agro-Product, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
| | - Zhixin Jia
- Information Technology Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; (M.M.); (X.Y.); (Z.J.); (B.J.)
- Key Laboratory of Cold Chain Logistics Technology for Agro-Product, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
| | - Boce Jia
- Information Technology Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; (M.M.); (X.Y.); (Z.J.); (B.J.)
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
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Guo D, Yang Y, Wu Y, Liu Y, Cao L, Shi Y, Wan N, Wu Z. Chemical Composition Analysis and Discrimination of Essential Oils of Artemisia Argyi Folium from Different Germplasm Resources Based on Electronic Nose and GC/MS Combined with Chemometrics. Chem Biodivers 2023; 20:e202200991. [PMID: 36650717 DOI: 10.1002/cbdv.202200991] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 01/02/2023] [Accepted: 01/17/2023] [Indexed: 01/19/2023]
Abstract
In this study, the electronic nose and GC/MS were used to analyze the chemical components of essential oils from different germplasm resources of Artemisia argyi Folium (A. argyi), in order to quickly identify essential oils of A. argyi from different germplasm resources and clarify the differences among different A. argyi samples. The essential oils of A. argyi were extracted by steam distillation. This article describes for the first time that electronic nose combined with chemometrics can distinguish the essential oils of A. argyi from different germplasm, which proves the reliability and potential of this technology. GC/MS was used to identify 134 volatile components from the essential oil of A. argyi. The main bioactive components were cineole, thujarone, artemisia ketone, β-caryophyllene, (-)-4-terpinol, 3,3,6-trimethyl-1,5-heptadien-4-ol, (-)-α-thujone, camphor, borneol. In addition, the results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that there were significant differences in the essential oils of A. argyi from different germplasm resources, terpenes, alcohols and ketones played an important role in identifying the essential oils of A. argyi from different germplasm resources. This indicates that electronic nose and GC/MS combined with chemometrics can be used as reliable techniques to identify different germplasm resources of A. argyi, and provide certain reference value for quality evaluation, selection of high-quality varieties and rational development of resources of A. argyi.
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Affiliation(s)
- Dongyun Guo
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
- Affiliated Stomatological Hospital of Nanchang University, The Key Laboratory of Oral Biomedicine, Jiangxi Province, Nanchang, 330004, China
| | - Yiqin Yang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Yi Wu
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Yang Liu
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Lan Cao
- Research Center for Traditional Chinese Medicine Resourcing and Ethnic Minority Medicine, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Yan Shi
- Affiliated Stomatological Hospital of Nanchang University, The Key Laboratory of Oral Biomedicine, Jiangxi Province, Nanchang, 330004, China
| | - Na Wan
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Zhenfeng Wu
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
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Wang B, Zhang J, Wang T, Li W, Lu Q, Sun H, Huang L, Liang X, Liu F, Liu F, Sun P, Lu G. Machine Learning-Assisted Volatile Organic Compound Gas Classification Based on Polarized Mixed-Potential Gas Sensors. ACS APPLIED MATERIALS & INTERFACES 2023; 15:6047-6057. [PMID: 36661846 DOI: 10.1021/acsami.2c17348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
The performance of electrochemical gas sensors depends on the reactions at the three-phase boundary. In this work, a mixed-potential gas sensor containing a counter electrode, a reference electrode, and a sensitive electrode was constructed. By applying a bias voltage to the counter electrode, the three-phase boundary can be polarized. The polarization state of the three-phase boundary determined the gas-sensitive performance. Taking 100 ppm ethanol vapor as an example, by regulating the polarization state of the three-phase boundary, the response value of the sensor can be adjusted from -170 to 40 mV, and the sensitivity can be controlled from -126.4 to 42.6 mV/decade. The working temperature of the sensor can be reduced after polarizing the three-phase boundary, lowering the power consumption from 1.14 to 0.625 W. The sensor also showed good stability and short response-recovery time (3 s). Based on this sensor, the Random Forest algorithm reached 99% accuracy in identifying the kind of VOC vapors. This accuracy was made possible by the ability to generate several signals concurrently. The above gas-sensitive performance improvements were due to the polarized three-phase boundary.
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Affiliation(s)
- Bin Wang
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Jianyu Zhang
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Tong Wang
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Weijia Li
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Qi Lu
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Huaiyuan Sun
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Lingchu Huang
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Xishuang Liang
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Fengmin Liu
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Fangmeng Liu
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
- International Center of Future Science, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Peng Sun
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
- International Center of Future Science, Jilin University, 2699 Qianjin Street, Changchun130012, China
| | - Geyu Lu
- State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun130012, China
- International Center of Future Science, Jilin University, 2699 Qianjin Street, Changchun130012, China
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Minami K, Kobayashi H, Matoba M, Kamiya Y, Maji S, Nemoto T, Tohno M, Nakakubo R, Yoshikawa G. Measurement of Volatile Fatty Acids in Silage through Odors with Nanomechanical Sensors. BIOSENSORS 2023; 13:152. [PMID: 36831918 PMCID: PMC9953262 DOI: 10.3390/bios13020152] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/10/2023] [Accepted: 01/16/2023] [Indexed: 06/18/2023]
Abstract
The measurement of volatile fatty acids (VFAs) is of great importance in the fields of food and agriculture. There are various methods to measure VFAs, but most methods require specific equipment, making on-site measurements difficult. In this work, we demonstrate the measurements of VFAs in a model sample, silage, through its vapor using an array of nanomechanical sensors-Membrane-type Surface stress Sensors (MSS). Focusing on relatively slow desorption behaviors of VFAs predicted with the sorption kinetics of nanomechanical sensing and the dissociation nature of VFAs, the VFAs can be efficiently measured by using features extracted from the decay curves of the sensing response, resulting in sufficient discrimination of the silage samples. Since the present sensing system does not require expensive, bulky setup and pre-treatment of samples, it has a great potential for practical applications including on-site measurements.
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Affiliation(s)
- Kosuke Minami
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Ibaraki, Japan
| | - Hisami Kobayashi
- Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO), 768 Senbonmatsu, Nasushiobara 329-2793, Tochigi, Japan
| | - Masaaki Matoba
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Ibaraki, Japan
| | - Yuko Kamiya
- Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO), 768 Senbonmatsu, Nasushiobara 329-2793, Tochigi, Japan
| | - Subrata Maji
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Ibaraki, Japan
| | - Takahiro Nemoto
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Ibaraki, Japan
| | - Masanori Tohno
- Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO), 768 Senbonmatsu, Nasushiobara 329-2793, Tochigi, Japan
- Research Center of Genetic Resources, National Agriculture and Food Research Organization (NARO), 2-1-2 Kannondai, Tsukuba 305-8602, Ibaraki, Japan
| | - Ryoh Nakakubo
- Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO), 2 Ikenodai, Tsukuba 305-0901, Ibaraki, Japan
| | - Genki Yoshikawa
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Ibaraki, Japan
- Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8571, Ibaraki, Japan
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Sun L, Wu J, Wang K, Liang T, Liu Q, Yan J, Yang Y, Qiao K, Ma S, Wang D. Comparative Analysis of Acanthopanacis Cortex and Periplocae Cortex Using an Electronic Nose and Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis. Molecules 2022; 27:molecules27248964. [PMID: 36558097 PMCID: PMC9781861 DOI: 10.3390/molecules27248964] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 12/09/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
Chinese Herbal Medicines (CHMs) can be identified by experts according to their odors. However, the identification of these medicines is subjective and requires long-term experience. The samples of Acanthopanacis Cortex and Periplocae Cortex used were dried cortexes, which are often confused in the market due to their similar appearance, but their chemical composition and odor are different. The clinical use of the two herbs is different, but the phenomenon of being confused with each other often occurs. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two species for fast and robust discrimination, in order to provide a scientific basis for avoiding confusion and misuse in the process of production, circulation and clinical use. In this study, the odor and volatile components of these two medicinal materials were detected by the E-nose and by gas chromatography-mass spectrometry (GC-MS), respectively. An E-nose combined with pattern analysis methods such as principal component analysis (PCA) and partial least squares (PLS) was used to discriminate the cortex samples. The E-nose was used to determine the odors of the samples and enable rapid differentiation of Acanthopanacis Cortex and Periplocae Cortex. GC-MS was utilized to reveal the differences between the volatile constituents of Acanthopanacis Cortex and Periplocae Cortex. In all, 82 components including 9 co-contained components were extracted by chromatographic peak integration and matching, and 24 constituents could be used as chemical markers to distinguish these two species. The E-nose detection technology is able to discriminate between Acanthopanacis Cortex and Periplocae Cortex, with GC-MS providing support to determine the material basis of the E-nose sensors' response. The proposed method is rapid, simple, eco-friendly and can successfully differentiate these two medicinal materials by their odors. It can be applied to quality control links such as online detection, and also provide reference for the establishment of other rapid detection methods. The further development and utilization of this technology is conducive to the further supervision of the quality of CHMs and the healthy development of the industry.
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Prasad P, Raut P, Goel S, Barnwal RP, Bodhe GL. Electronic nose and wireless sensor network for environmental monitoring application in pulp and paper industry: a review. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:855. [PMID: 36207610 DOI: 10.1007/s10661-022-10479-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 09/10/2022] [Indexed: 06/16/2023]
Abstract
Pulp and paper industries emit various odorous gases during the pulp production and paper-making phase, which are unpleasant and have harmful effects on the human body. The working staffs are continuously exposed to these gases and develop various health issues. Hence, regular monitoring and analysis of such gases are necessary to avoid any sudden high concentration exposure and to prevent adverse health effects on the staff. An electronic nose (EN) has an array of gas sensors with an alert system for early detection of gases. Various ENs have been developed for varying applications till date. The detailed knowledge of the sensors used, their sensitivity and technology is helpful in development of any EN. The objective of this study is to comprehensively review various developed ENs with respect to their gas sensing and pattern recognition (PR) technologies. The information on gases released from pulp and paper industries is also compiled. The evolution of EN technology, its various applications, challenges in developing EN and its utility in safeguarding the industrial workers' life have been described. Further, gap analysis among previously developed EN, contemporary EN and wireless sensor network (WSN) is elaborated. It will facilitate future researchers for better selection of sensors and PR technologies while developing EN. The commonly used sensing technologies are described with their advantages, disadvantages and working principles. Metal oxide semiconductor (MOS) gas sensor and ANN algorithm show better result and hence recommended in the development of EN, whereas ZigBee protocol has been widely used for WSN.
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Affiliation(s)
- Poonam Prasad
- Cleaner Technology and Modelling Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
| | - Piyush Raut
- Cleaner Technology and Modelling Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India
| | - Sangita Goel
- Environmental Audit and Policy Implementation Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India
| | - Rajesh P Barnwal
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
- Information Technology Division, CSIR-Central Mechanical Engineering Research Institute, Durgapur, WB, India
| | - G L Bodhe
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
- Quality Management System Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India
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11
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Recent Advances in Nanomechanical Membrane-Type Surface Stress Sensors towards Artificial Olfaction. BIOSENSORS 2022; 12:bios12090762. [PMID: 36140147 PMCID: PMC9496807 DOI: 10.3390/bios12090762] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/08/2022] [Accepted: 09/14/2022] [Indexed: 11/17/2022]
Abstract
Nanomechanical sensors have gained significant attention as powerful tools for detecting, distinguishing, and identifying target analytes, especially odors that are composed of a complex mixture of gaseous molecules. Nanomechanical sensors and their arrays are a promising platform for artificial olfaction in combination with data processing technologies, including machine learning techniques. This paper reviews the background of nanomechanical sensors, especially conventional cantilever-type sensors. Then, we focus on one of the optimized structures for static mode operation, a nanomechanical Membrane-type Surface stress Sensor (MSS), and discuss recent advances in MSS and their applications towards artificial olfaction.
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12
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Labanska M, van Amsterdam S, Jenkins S, Clarkson JP, Covington JA. Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22145453. [PMID: 35891126 PMCID: PMC9315870 DOI: 10.3390/s22145453] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 07/18/2022] [Accepted: 07/19/2022] [Indexed: 06/01/2023]
Abstract
The evaluation of crop health status and early disease detection are critical for implementing a fast response to a pathogen attack, managing crop infection, and minimizing the risk of disease spreading. Fusarium oxysporum f. sp. cepae, which causes fusarium basal rot disease, is considered one of the most harmful pathogens of onion and accounts for considerable crop losses annually. In this work, the capability of the PEN 3 electronic nose system to detect onion and shallot bulbs infected with F. oxysporum f. sp. cepae, to track the progression of fungal infection, and to discriminate between the varying proportions of infected onion bulbs was evaluated. To the best of our knowledge, this is a first report on successful application of an electronic nose to detect fungal infections in post-harvest onion and shallot bulbs. Sensor array responses combined with PCA provided a clear discrimination between non-infected and infected onion and shallot bulbs as well as differentiation between samples with varying proportions of infected bulbs. Classification models based on LDA, SVM, and k-NN algorithms successfully differentiate among various rates of infected bulbs in the samples with accuracy up to 96.9%. Therefore, the electronic nose was proved to be a potentially useful tool for rapid, non-destructive monitoring of the post-harvest crops.
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Affiliation(s)
- Malgorzata Labanska
- The Plant Breeding and Acclimatization Institute-National Research Institute, Radzikow, 05-870 Blonie, Poland
| | - Sarah van Amsterdam
- Warwick Crop Centre, School of Life Sciences, University of Warwick, Wellesbourne, Warwick CV35 9EF, UK; (S.v.A.); (S.J.); (J.P.C.)
| | - Sascha Jenkins
- Warwick Crop Centre, School of Life Sciences, University of Warwick, Wellesbourne, Warwick CV35 9EF, UK; (S.v.A.); (S.J.); (J.P.C.)
| | - John P. Clarkson
- Warwick Crop Centre, School of Life Sciences, University of Warwick, Wellesbourne, Warwick CV35 9EF, UK; (S.v.A.); (S.J.); (J.P.C.)
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13
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Minami K. Nanomechanical Sensors for Gas Detection towards Artificial Olfaction. BIOSENSORS 2022; 12:bios12040256. [PMID: 35448316 PMCID: PMC9028482 DOI: 10.3390/bios12040256] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 04/12/2022] [Indexed: 12/23/2022]
Affiliation(s)
- Kosuke Minami
- Olfactory Sensors Group, Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Japan
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14
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Cruz C, Matatagui D, Ramírez C, Badillo-Ramirez I, de la O-Cuevas E, Saniger JM, Horrillo MC. Carbon SH-SAW-Based Electronic Nose to Discriminate and Classify Sub-ppm NO 2. SENSORS 2022; 22:s22031261. [PMID: 35162005 PMCID: PMC8840179 DOI: 10.3390/s22031261] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/18/2022] [Accepted: 02/01/2022] [Indexed: 01/27/2023]
Abstract
In this research, a compact electronic nose (e-nose) based on a shear horizontal surface acoustic wave (SH-SAW) sensor array is proposed for the NO2 detection, classification and discrimination among some of the most relevant surrounding toxic chemicals, such as carbon monoxide (CO), ammonia (NH3), benzene (C6H6) and acetone (C3H6O). Carbon-based nanostructured materials (CBNm), such as mesoporous carbon (MC), reduced graphene oxide (rGO), graphene oxide (GO) and polydopamine/reduced graphene oxide (PDA/rGO) are deposited as a sensitive layer with controlled spray and Langmuir–Blodgett techniques. We show the potential of the mass loading and elastic effects of the CBNm to enhance the detection, the classification and the discrimination of NO2 among different gases by using Machine Learning (ML) techniques (e.g., PCA, LDA and KNN). The small dimensions and low cost make this analytical system a promising candidate for the on-site discrimination of sub-ppm NO2.
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Affiliation(s)
- Carlos Cruz
- Grupo de Tecnología de Sensores Avanzados (SENSAVAN), Instituto de Tecnologías Físicas y de la Información (ITEFI), CSIC, 28006 Madrid, Spain;
- Department of Electronics, University of Alcala, 28871 Alcala de Henares, Madrid, Spain
- Correspondence: (C.C.); (D.M.)
| | - Daniel Matatagui
- Grupo de Tecnología de Sensores Avanzados (SENSAVAN), Instituto de Tecnologías Físicas y de la Información (ITEFI), CSIC, 28006 Madrid, Spain;
- Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049 Madrid, Spain
- Correspondence: (C.C.); (D.M.)
| | - Cristina Ramírez
- Institute of Ceramics and Glass, ICV-CSIC, Kelsen 5, Cantoblanco, 28049 Madrid, Spain;
| | - Isidro Badillo-Ramirez
- Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México, Circuito Exterior S/N, Ciudad Universitaria, Ciudad de Mexico 04510, Mexico; (I.B.-R.); (E.d.l.O.-C.); (J.M.S.)
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Emmanuel de la O-Cuevas
- Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México, Circuito Exterior S/N, Ciudad Universitaria, Ciudad de Mexico 04510, Mexico; (I.B.-R.); (E.d.l.O.-C.); (J.M.S.)
- Unidad Académica de Física, Universidad Autónoma de Zacatecas, Zacatecas 98068, Mexico
| | - José M. Saniger
- Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México, Circuito Exterior S/N, Ciudad Universitaria, Ciudad de Mexico 04510, Mexico; (I.B.-R.); (E.d.l.O.-C.); (J.M.S.)
| | - Mari Carmen Horrillo
- Grupo de Tecnología de Sensores Avanzados (SENSAVAN), Instituto de Tecnologías Físicas y de la Información (ITEFI), CSIC, 28006 Madrid, Spain;
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15
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Calvini R, Pigani L. Toward the Development of Combined Artificial Sensing Systems for Food Quality Evaluation: A Review on the Application of Data Fusion of Electronic Noses, Electronic Tongues and Electronic Eyes. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22020577. [PMID: 35062537 PMCID: PMC8778015 DOI: 10.3390/s22020577] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/03/2022] [Accepted: 01/10/2022] [Indexed: 05/02/2023]
Abstract
Devices known as electronic noses (ENs), electronic tongues (ETs), and electronic eyes (EEs) have been developed in recent years in the in situ study of real matrices with little or no manipulation of the sample at all. The final goal could be the evaluation of overall quality parameters such as sensory features, indicated by the "smell", "taste", and "color" of the sample under investigation or in the quantitative detection of analytes. The output of these sensing systems can be analyzed using multivariate data analysis strategies to relate specific patterns in the signals with the required information. In addition, using suitable data-fusion techniques, the combination of data collected from ETs, ENs, and EEs can provide more accurate information about the sample than any of the individual sensing devices. This review's purpose is to collect recent advances in the development of combined ET, EN, and EE systems for assessing food quality, paying particular attention to the different data-fusion strategies applied.
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Affiliation(s)
- Rosalba Calvini
- Department of Life Sciences, University of Modena and Reggio Emilia, Pad. Besta Via Amendola 2, 42122 Reggio Emilia, Italy;
| | - Laura Pigani
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy
- Correspondence:
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16
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Vanarse A, Osseiran A, Rassau A, van der Made P. Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts. SENSORS (BASEL, SWITZERLAND) 2022; 22:440. [PMID: 35062402 PMCID: PMC8778084 DOI: 10.3390/s22020440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/30/2021] [Accepted: 01/03/2022] [Indexed: 06/14/2023]
Abstract
Current developments in artificial olfactory systems, also known as electronic nose (e-nose) systems, have benefited from advanced machine learning techniques that have significantly improved the conditioning and processing of multivariate feature-rich sensor data. These advancements are complemented by the application of bioinspired algorithms and architectures based on findings from neurophysiological studies focusing on the biological olfactory pathway. The application of spiking neural networks (SNNs), and concepts from neuromorphic engineering in general, are one of the key factors that has led to the design and development of efficient bioinspired e-nose systems. However, only a limited number of studies have focused on deploying these models on a natively event-driven hardware platform that exploits the benefits of neuromorphic implementation, such as ultra-low-power consumption and real-time processing, for simplified integration in a portable e-nose system. In this paper, we extend our previously reported neuromorphic encoding and classification approach to a real-world dataset that consists of sensor responses from a commercial e-nose system when exposed to eight different types of malts. We show that the proposed SNN-based classifier was able to deliver 97% accurate classification results at a maximum latency of 0.4 ms per inference with a power consumption of less than 1 mW when deployed on neuromorphic hardware. One of the key advantages of the proposed neuromorphic architecture is that the entire functionality, including pre-processing, event encoding, and classification, can be mapped on the neuromorphic system-on-a-chip (NSoC) to develop power-efficient and highly-accurate real-time e-nose systems.
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Affiliation(s)
- Anup Vanarse
- Brainchip Research Institute, Perth 6000, Australia; (A.O.); (P.v.d.M.)
| | - Adam Osseiran
- Brainchip Research Institute, Perth 6000, Australia; (A.O.); (P.v.d.M.)
| | - Alexander Rassau
- School of Engineering, Edith Cowan University, Joondalup 6027, Australia;
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17
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Flexible Impedimetric Electronic Nose for High-Accurate Determination of Individual Volatile Organic Compounds by Tuning the Graphene Sensitive Properties. CHEMOSENSORS 2021. [DOI: 10.3390/chemosensors9120360] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
We investigated functionalized graphene materials to create highly sensitive sensors for volatile organic compounds (VOCs) such as formaldehyde, methanol, ethanol, acetone, and isopropanol. First, we prepared VOC-sensitive films consisting of mechanically exfoliated graphene (eG) and chemical graphene oxide (GO), which have different concentrations of structural defects. We deposited the films on silver interdigitated electrodes on Kapton substrate and submitted them to thermal treatment. Next, we measured the sensitive properties of the resulting sensors towards specific VOCs by impedance spectroscopy. We obtained the eG- and GO-based electronic nose composed of two eG films- and four GO film-based sensors with variable sensitivity to individual VOCs. The smallest relative change in impedance was 5% for the sensor based on eG film annealed at 180 °C toward 10 ppm formaldehyde, whereas the highest relative change was 257% for the sensor based on two-layers deposited GO film annealed at 200 °C toward 80 ppm ethanol. At 10 ppm VOC, the GO film-based sensors were sensitive enough to distinguish between individual VOCs, which implied excellent selectivity, as confirmed by Principle Component Analysis (PCA). According to a PCA-Support Vector Machine-based signal processing method, the electronic nose provided identification accuracy of 100% for individual VOCs. The proposed electronic nose can be used to detect multiple VOCs selectively because each sensor is sensitive to VOCs and has significant cross-selectivity to others.
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18
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Cheema JA, Carraher C, Plank NOV, Travas-Sejdic J, Kralicek A. Insect odorant receptor-based biosensors: Current status and prospects. Biotechnol Adv 2021; 53:107840. [PMID: 34606949 DOI: 10.1016/j.biotechadv.2021.107840] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 09/02/2021] [Accepted: 09/27/2021] [Indexed: 02/01/2023]
Abstract
Whilst the senses of vision and hearing have been successfully automated and miniaturized in portable formats (e.g. smart phone), this is yet to be achieved with the sense of smell. This is because the sensing challenge is not trivial as it involves navigating a chemosensory space comprising thousands of volatile organic compounds. Distinct aroma recognition is based on detecting unique combinations of volatile organic compounds. In natural olfactory systems this is accomplished by employing odorant receptors (ORs) with varying specificities, together with combinatorial neural coding mechanisms. Attempts to mimic the remarkable sensitivity and accuracy of natural olfactory systems has therefore been challenging. Current portable chemical sensors for odorant detection are neither sensitive nor selective, prompting research exploring artificial olfactory devices that use natural OR proteins for sensing. Much research activity to develop OR based biosensors has concentrated on mammalian ORs, however, insect ORs have not been explored as extensively. Insects possess an extraordinary sense of smell due to a repertoire of odorant receptors evolved to interpret olfactory cues vital to the insects' survival. The potential of insect ORs as sensing elements is only now being unlocked through recent research efforts to understand their structure, ligand binding mechanisms and development of odorant biosensors. Like their mammalian counterparts, there are many challenges with working with insect ORs. These include expression, purification and presentation of the insect OR in a stable display format compatible with an effective transduction methodology while maintaining OR structure and function. Despite these challenges, significant progress has been demonstrated in developing OR-based biosensors which exploit insect ORs in cells, lipid bilayers, liposomes and nanodisc formats. Ultrasensitive and highly selective detection of volatile organic compounds has been validated by coupling these insect OR display formats with transduction methodologies spanning optical (fluorescence) and electrical (field effect transistors, electrochemical impedance spectroscopy) techniques. This review summarizes the current status of insect OR based biosensors and their future outlook.
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Affiliation(s)
- Jamal Ahmed Cheema
- Polymer Biointerface Centre, School of Chemical Sciences, The University of Auckland, Auckland 1023, New Zealand; MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington 6140, New Zealand; The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand
| | - Colm Carraher
- The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand
| | - Natalie O V Plank
- MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington 6140, New Zealand; School of Chemical and Physical Sciences, Victoria University of Wellington, Wellington 6021, New Zealand
| | - Jadranka Travas-Sejdic
- Polymer Biointerface Centre, School of Chemical Sciences, The University of Auckland, Auckland 1023, New Zealand; MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington 6140, New Zealand.
| | - Andrew Kralicek
- The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand; Scentian Bio Limited, 1c Goring Road, Sandringham, Auckland 1025, New Zealand.
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19
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Kim C, Raja IS, Lee JM, Lee JH, Kang MS, Lee SH, Oh JW, Han DW. Recent Trends in Exhaled Breath Diagnosis Using an Artificial Olfactory System. BIOSENSORS 2021; 11:337. [PMID: 34562928 PMCID: PMC8467588 DOI: 10.3390/bios11090337] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/06/2021] [Accepted: 09/10/2021] [Indexed: 12/26/2022]
Abstract
Artificial olfactory systems are needed in various fields that require real-time monitoring, such as healthcare. This review introduces cases of detection of specific volatile organic compounds (VOCs) in a patient's exhaled breath and discusses trends in disease diagnosis technology development using artificial olfactory technology that analyzes exhaled human breath. We briefly introduce algorithms that classify patterns of odors (VOC profiles) and describe artificial olfactory systems based on nanosensors. On the basis of recently published research results, we describe the development trend of artificial olfactory systems based on the pattern-recognition gas sensor array technology and the prospects of application of this technology to disease diagnostic devices. Medical technologies that enable early monitoring of health conditions and early diagnosis of diseases are crucial in modern healthcare. By regularly monitoring health status, diseases can be prevented or treated at an early stage, thus increasing the human survival rate and reducing the overall treatment costs. This review introduces several promising technical fields with the aim of developing technologies that can monitor health conditions and diagnose diseases early by analyzing exhaled human breath in real time.
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Affiliation(s)
- Chuntae Kim
- BIO-IT Foundry Technology Institute, Pusan National University, Busan 46241, Korea
| | | | - Jong-Min Lee
- School of Nano Convergence Technology, Hallym University, Chuncheon 24252, Korea
| | | | - Moon Sung Kang
- Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Korea
| | - Seok Hyun Lee
- Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Korea
| | - Jin-Woo Oh
- BIO-IT Foundry Technology Institute, Pusan National University, Busan 46241, Korea
- Department of Nanoenergy Engineering, Pusan National University, Busan 46241, Korea
| | - Dong-Wook Han
- BIO-IT Foundry Technology Institute, Pusan National University, Busan 46241, Korea
- Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Korea
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20
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Zhou Y, Abbas F, Wang Z, Yu Y, Yue Y, Li X, Yu R, Fan Y. HS-SPME-GC-MS and Electronic Nose Reveal Differences in the Volatile Profiles of Hedychium Flowers. Molecules 2021; 26:5425. [PMID: 34500858 PMCID: PMC8433901 DOI: 10.3390/molecules26175425] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 08/30/2021] [Accepted: 09/02/2021] [Indexed: 11/16/2022] Open
Abstract
Floral fragrance is one of the most important characteristics of ornamental plants and plays a pivotal role in plant lifespan such as pollinator attraction, pest repelling, and protection against abiotic and biotic stresses. However, the precise determination of floral fragrance is limited. In the present study, the floral volatile compounds of six Hedychium accessions exhibiting from faint to highly fragrant were comparatively analyzed via gas chromatography-mass spectrometry (GC-MS) and Electronic nose (E-nose). A total of 42 volatile compounds were identified through GC-MS analysis, including monoterpenoids (18 compounds), sesquiterpenoids (12), benzenoids/phenylpropanoids (8), fatty acid derivatives (2), and others (2). In Hedychium coronarium 'ZS', H. forrestii 'Gaoling', H. 'Jin', H. 'Caixia', and H. 'Zhaoxia', monoterpenoids were abundant, while sesquiterpenoids were found in large quantities in H. coccineum 'KMH'. Hierarchical clustering analysis (HCA) divided the 42 volatile compounds into four different groups (I, II, III, IV), and Spearman correlation analysis showed these compounds to have different degrees of correlation. The E-nose was able to group the different accessions in the principal component analysis (PCA) corresponding to scent intensity. Furthermore, the pattern-recognition findings confirmed that the E-nose data validated the GC-MS results. The partial least squares (PLS) analysis between floral volatile compounds and sensors suggested that specific sensors were highly sensitive to terpenoids. In short, the E-nose is proficient in discriminating Hedychium accessions of different volatile profiles in both quantitative and qualitative aspects, offering an accurate and rapid reference technique for future applications.
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Affiliation(s)
- Yiwei Zhou
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
| | - Farhat Abbas
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
| | - Zhidong Wang
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
| | - Yunyi Yu
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
| | - Yuechong Yue
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
| | - Xinyue Li
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
| | - Rangcai Yu
- College of Life Sciences, South China Agricultural University, Guangzhou 510642, China;
| | - Yanping Fan
- The Research Center for Ornamental Plants, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China; (Y.Z.); (F.A.); (Z.W.); (Y.Y.); (Y.Y.); (X.L.)
- Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, South China Agricultural University, Guangzhou 510642, China
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21
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Determination of quasi-primary odors by endpoint detection. Sci Rep 2021; 11:12070. [PMID: 34103566 PMCID: PMC8187439 DOI: 10.1038/s41598-021-91210-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 05/19/2021] [Indexed: 01/02/2023] Open
Abstract
It is known that there are no primary odors that can represent any other odors with their combination. Here, we propose an alternative approach: "quasi" primary odors. This approach comprises the following condition and method: (1) within a collected dataset and (2) by the machine learning-based endpoint detection. The quasi-primary odors are selected from the odors included in a collected odor dataset according to the endpoint score. While it is limited within the given dataset, the combination of such quasi-primary odors with certain ratios can reproduce any other odor in the dataset. To visually demonstrate this approach, the three quasi-primary odors having top three high endpoint scores are assigned to the vertices of a chromaticity triangle with red, green, and blue. Then, the other odors in the dataset are projected onto the chromaticity triangle to have their unique colors. The number of quasi-primary odors is not limited to three but can be set to an arbitrary number. With this approach, one can first find "extreme" odors (i.e., quasi-primary odors) in a given odor dataset, and then, reproduce any other odor in the dataset or even synthesize a new arbitrary odor by combining such quasi-primary odors with certain ratios.
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Zanin RC, Smrke S, Kurozawa LE, Yamashita F, Yeretzian C. Novel experimental approach to study aroma release upon reconstitution of instant coffee products. Food Chem 2020; 317:126455. [PMID: 32109659 DOI: 10.1016/j.foodchem.2020.126455] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 01/16/2020] [Accepted: 02/19/2020] [Indexed: 12/13/2022]
Abstract
This study presents an experimental approach to study the kinetics and fast release of volatile organic compounds (VOCs) upon reconstitution of instant coffee products. A sampling setup coupled to PTR-ToF-MS (Proton Transfer Reaction Time-of-Flight Mass Spectrometry) for the automated and reproducible reconstitution of instant coffee products was developed to monitor the dynamic release of VOCs. A rapid release of aroma compounds was observed in the first seconds upon hot water addition ("aroma burst"), followed by subsequent decrease in headspace (HS) intensities over the course of analysis. Differences in time-intensity release profiles of individual VOCs were correlated to their Henry's Law constant, vapor pressure and water solubility. The setup and approach proposed here have shown to be sensitive and to respond to fast dynamic changes in aroma release. It allows studying VOCs release upon reconstitution and supports the development of novel technologies and formulations for instant products with improved aroma release properties.
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Affiliation(s)
- Rodolfo Campos Zanin
- Departamento de Ciência e Tecnologia de Alimentos, Centro de Ciências Agrárias, Universidade Estadual de Londrina, P O Box 10011, 86057-970 Londrina, PR, Brazil
| | - Samo Smrke
- Zurich University of Applied Sciences, Institute of Chemistry and Biotechnology, 8820 Wädenswil, Switzerland.
| | - Louise Emy Kurozawa
- Department of Food Engineering, School of Food Engineering, University of Campinas, Campinas, SP 13083-862, Brazil.
| | - Fabio Yamashita
- Departamento de Ciência e Tecnologia de Alimentos, Centro de Ciências Agrárias, Universidade Estadual de Londrina, P O Box 10011, 86057-970 Londrina, PR, Brazil.
| | - Chahan Yeretzian
- Zurich University of Applied Sciences, Institute of Chemistry and Biotechnology, 8820 Wädenswil, Switzerland.
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Łabańska M, Ciosek-Skibińska P, Wróblewski W. Critical Evaluation of Laboratory Potentiometric Electronic Tongues for Pharmaceutical Analysis-An Overview. SENSORS 2019; 19:s19245376. [PMID: 31817537 PMCID: PMC6960610 DOI: 10.3390/s19245376] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 11/29/2019] [Accepted: 12/03/2019] [Indexed: 02/07/2023]
Abstract
Electronic tongue systems equipped with cross-sensitive potentiometric sensors have been applied to pharmaceutical analysis, due to the possibility of various applications and developing new formulations. Many studies already proved the complementarity between the electronic tongue and classical analysis such as dissolution tests indicated by Pharmacopeias. However, as a new approach to study pharmaceuticals, electronic tongues lack strict testing protocols and specification limits; therefore, their results can be improperly interpreted and inconsistent with the reference studies. Therefore, all aspects of the development, measurement conditions, data analysis, and interpretation of electronic tongue results were discussed in this overview. The critical evaluation of the effectiveness and reliability of constructed devices may be helpful for a better understanding of electronic tongue systems development and for providing strict testing protocols.
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Affiliation(s)
- Małgorzata Łabańska
- Plant Breeding and Acclimatization Institute—National Research Institute, Bonin Research Centre, Bonin 3, 76-009 Bonin, Poland
- Correspondence:
| | - Patrycja Ciosek-Skibińska
- Chair of Medical Biotechnology, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw, Poland; (P.C.-S.); (W.W.)
| | - Wojciech Wróblewski
- Chair of Medical Biotechnology, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw, Poland; (P.C.-S.); (W.W.)
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24
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Imamura G, Shiba K, Yoshikawa G, Washio T. Free-hand gas identification based on transfer function ratios without gas flow control. Sci Rep 2019; 9:9768. [PMID: 31278339 PMCID: PMC6611792 DOI: 10.1038/s41598-019-46164-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 06/24/2019] [Indexed: 11/08/2022] Open
Abstract
Gas identification is one of the most important functions of a gas sensor system. To identify gas species from sensing signals without gas flow control such as pumps or mass flow controllers, it is necessary to extract decisive dynamic features from complex sensing signals due to uncontrolled airflow. For that purpose, various analysis methods using system identification techniques have been proposed, whereas a method that is not affected by a gas input pattern has been demanded to enhance the robustness of gas identification. Here we develop a novel gas identification protocol based on a transfer function ratio (TFR) that is intrinsically independent of a gas input pattern. By combining the protocol with MEMS-based sensors-Membrane-type Surface stress Sensors (MSS), we have realized gas identification with a free-hand measurement, in which one can simply hold a small sensor chip near samples. From sensing signals obtained through the free-hand measurement, we have developed highly accurate machine learning models that can identify odors of spices and herbs as well as solvent vapors. Since no bulky gas flow control units are required, this protocol will expand the applicability of gas sensors to portable electronics, leading to practical artificial olfaction.
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Affiliation(s)
- Gaku Imamura
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki, 305-0044, Japan.
- Center for Functional Sensor & Actuator (CFSN), National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki, 305-0044, Japan.
| | - Kota Shiba
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki, 305-0044, Japan
- Center for Functional Sensor & Actuator (CFSN), National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki, 305-0044, Japan
| | - Genki Yoshikawa
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki, 305-0044, Japan
- Center for Functional Sensor & Actuator (CFSN), National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki, 305-0044, Japan
- Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki, 305-8571, Japan
| | - Takashi Washio
- The Institute of Scientific and Industrial Research, Osaka University, Mihogaoka 8-1, Ibaraki, Osaka, 567-0047, Japan
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25
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Critical review of electronic nose and tongue instruments prospects in pharmaceutical analysis. Anal Chim Acta 2019; 1077:14-29. [PMID: 31307702 DOI: 10.1016/j.aca.2019.05.024] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 05/10/2019] [Accepted: 05/12/2019] [Indexed: 11/20/2022]
Abstract
Electronic nose (enose, EN) and electronic tongue (etongue, ET) have been designed to simulate human senses of smell and taste in the best possible way. The signals acquired from a sensor array, combined with suitable data analysis system, are the basis for holistic analysis of samples. The efficiency of these instruments, regarding classification, discrimination, detection, monitoring and analytics of samples in different types of matrices, is utilized in many fields of science and industry, offering numerous practical applications. Popularity of both types of devices significantly increased during the last decade, mainly due to improvement of their sensitivity and selectivity. The electronic senses have been employed in pharmaceutical sciences for, among others, formulation development and quality assurance. This paper contains a review of some particular applications of EN and ET based instruments in pharmaceutical industry. In addition, development prospects and a critical summary of the state of art in the field were also surveyed.
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26
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Vanarse A, Osseiran A, Rassau A. Real-Time Classification of Multivariate Olfaction Data Using Spiking Neural Networks. SENSORS (BASEL, SWITZERLAND) 2019; 19:E1841. [PMID: 31003417 PMCID: PMC6515392 DOI: 10.3390/s19081841] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 04/10/2019] [Accepted: 04/15/2019] [Indexed: 11/23/2022]
Abstract
Recent studies in bioinspired artificial olfaction, especially those detailing the application of spike-based neuromorphic methods, have led to promising developments towards overcoming the limitations of traditional approaches, such as complexity in handling multivariate data, computational and power requirements, poor accuracy, and substantial delay for processing and classification of odors. Rank-order-based olfactory systems provide an interesting approach for detection of target gases by encoding multi-variate data generated by artificial olfactory systems into temporal signatures. However, the utilization of traditional pattern-matching methods and unpredictable shuffling of spikes in the rank-order impedes the performance of the system. In this paper, we present an SNN-based solution for the classification of rank-order spiking patterns to provide continuous recognition results in real-time. The SNN classifier is deployed on a neuromorphic hardware system that enables massively parallel and low-power processing on incoming rank-order patterns. Offline learning is used to store the reference rank-order patterns, and an inbuilt nearest neighbor classification logic is applied by the neurons to provide recognition results. The proposed system was evaluated using two different datasets including rank-order spiking data from previously established olfactory systems. The continuous classification that was achieved required a maximum of 12.82% of the total pattern frame to provide 96.5% accuracy in identifying corresponding target gases. Recognition results were obtained at a nominal processing latency of 16ms for each incoming spike. In addition to the clear advantages in terms of real-time operation and robustness to inconsistent rank-orders, the SNN classifier can also detect anomalies in rank-order patterns arising due to drift in sensing arrays.
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Affiliation(s)
- Anup Vanarse
- School of Engineering, Edith Cowan University, Perth 6027, Australia.
| | - Adam Osseiran
- School of Engineering, Edith Cowan University, Perth 6027, Australia.
| | - Alexander Rassau
- School of Engineering, Edith Cowan University, Perth 6027, Australia.
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27
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Orlandi G, Calvini R, Foca G, Pigani L, Vasile Simone G, Ulrici A. Data fusion of electronic eye and electronic tongue signals to monitor grape ripening. Talanta 2019; 195:181-189. [DOI: 10.1016/j.talanta.2018.11.046] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 11/08/2018] [Accepted: 11/14/2018] [Indexed: 11/30/2022]
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28
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Kutsanedzie FYH, Guo Z, Chen Q. Advances in Nondestructive Methods for Meat Quality and Safety Monitoring. FOOD REVIEWS INTERNATIONAL 2019. [DOI: 10.1080/87559129.2019.1584814] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Affiliation(s)
| | - Zhiming Guo
- School of Food & Biological Engineering, Jiangsu University, Zhenjiang, P.R. China
| | - Quansheng Chen
- School of Food & Biological Engineering, Jiangsu University, Zhenjiang, P.R. China
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29
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Liu YJ, Zeng M, Meng QH. Electronic nose using a bio-inspired neural network modeled on mammalian olfactory system for Chinese liquor classification. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2019; 90:025001. [PMID: 30831708 DOI: 10.1063/1.5064540] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 01/16/2019] [Indexed: 06/09/2023]
Abstract
The simplification of data processing is the frontier domain for electronic nose (e-nose) applications, whereas there are a lot of manual operations in a traditional processing procedure. To solve this problem, we propose a novel data processing method using the bio-inspired neural network modeled on the mammalian olfactory system. Through a neural coding scheme with multiple squared cosine receptive fields, continuous sensor data are simplified as the spike pattern in virtual receptor units. The biologically plausible olfactory bulb, which mimics the structure and function of main olfactory pathways, is designed to refine the olfactory information embedded in the encoded spikes. As a simplified presentation of cortical function, the bionic olfactory cortex is established to further analyze olfactory bulb's outputs and perform classification. The proposed method can automatically learn features without tedious steps such as denoising, feature extraction and reduction, which significantly simplifies the processing procedure for e-noses. To validate algorithm performance, comparison studies were performed for seven kinds of Chinese liquors using the proposed method and traditional data processing methods. The experimental results show that squared cosine receptive fields and the olfactory bulb model are crucial for improving classification performance, and the proposed method has higher classification rates than traditional methods when the sensor quantity and type are changed.
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Affiliation(s)
- Ying-Jie Liu
- Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
| | - Ming Zeng
- Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
| | - Qing-Hao Meng
- Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
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30
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Discrimination of Chinese Liquors Based on Electronic Nose and Fuzzy Discriminant Principal Component Analysis. Foods 2019; 8:foods8010038. [PMID: 30669607 PMCID: PMC6352173 DOI: 10.3390/foods8010038] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 01/15/2019] [Accepted: 01/18/2019] [Indexed: 02/05/2023] Open
Abstract
The detection of liquor quality is an important process in the liquor industry, and the quality of Chinese liquors is partly determined by the aromas of the liquors. The electronic nose (e-nose) refers to an artificial olfactory technology. The e-nose system can quickly detect different types of Chinese liquors according to their aromas. In this study, an e-nose system was designed to identify six types of Chinese liquors, and a novel feature extraction algorithm, called fuzzy discriminant principal component analysis (FDPCA), was developed for feature extraction from e-nose signals by combining discriminant principal component analysis (DPCA) and fuzzy set theory. In addition, principal component analysis (PCA), DPCA, K-nearest neighbor (KNN) classifier, leave-one-out (LOO) strategy and k-fold cross-validation (k = 5, 10, 20, 25) were employed in the e-nose system. The maximum classification accuracy of feature extraction for Chinese liquors was 98.378% using FDPCA, showing this algorithm to be extremely effective. The experimental results indicate that an e-nose system coupled with FDPCA is a feasible method for classifying Chinese liquors.
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31
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Bakar MABA, Abdullah AHB, Saad FSBA. Development of Application Specific Electronic Nose for Monitoring the Atmospheric Hazards in Confined Space. ADVANCES IN SCIENCE, TECHNOLOGY AND ENGINEERING SYSTEMS JOURNAL 2019; 4:200-216. [DOI: 10.25046/aj040120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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32
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Rottiers H, Tzompa Sosa DA, Van de Vyver L, Hinneh M, Everaert H, De Wever J, Messens K, Dewettinck K. Discrimination of Cocoa Liquors Based on Their Odor Fingerprint: a Fast GC Electronic Nose Suitability Study. FOOD ANAL METHOD 2018. [DOI: 10.1007/s12161-018-1379-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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33
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Shiba K, Tamura R, Sugiyama T, Kameyama Y, Koda K, Sakon E, Minami K, Ngo HT, Imamura G, Tsuda K, Yoshikawa G. Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis. ACS Sens 2018; 3:1592-1600. [PMID: 30110149 DOI: 10.1021/acssensors.8b00450] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A sensing signal obtained by measuring an odor usually contains varied information that reflects an origin of the odor itself, while an effective approach is required to reasonably analyze informative data to derive the desired information. Herein, we demonstrate that quantitative odor analysis was achieved through systematic material design-based nanomechanical sensing combined with machine learning. A ternary mixture consisting of water, ethanol, and methanol was selected as a model system where a target molecule coexists with structurally similar species in a humidified condition. To predict the concentration of each species in the system via the data-driven approach, six types of nanoparticles functionalized with hydroxyl, aminopropyl, phenyl, and/or octadecyl groups were synthesized as a receptor coating of a nanomechanical sensor. Then, a machine learning model based on Gaussian process regression was trained with sensing data sets obtained from the samples with diverse concentrations. As a result, the octadecyl-modified nanoparticles enhanced prediction accuracy for water while the use of both octadecyl and aminopropyl groups was indicated to be a key for a better prediction accuracy for ethanol and methanol. As the prediction accuracy for ethanol and methanol was improved by introducing two additional nanoparticles with finely controlled octadecyl and aminopropyl amount, the feedback obtained by the present machine learning was effectively utilized to optimize material design for better performance. We demonstrate through this study that various information which was extracted from plenty of experimental data sets was successfully combined with our knowledge to produce wisdom for addressing a critical issue in gas phase sensing.
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Affiliation(s)
| | - Ryo Tamura
- Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwa-no-ha, Kashiwa, Chiba 277-8561, Japan
| | | | | | | | | | | | | | | | - Koji Tsuda
- Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwa-no-ha, Kashiwa, Chiba 277-8561, Japan
- Center for Advanced Intelligence Project, RIKEN, 1-4-1 Nihombashi, Chuo-ku, Tokyo 103-0027, Japan
| | - Genki Yoshikawa
- Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8571, Japan
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Orlandi G, Calvini R, Pigani L, Foca G, Vasile Simone G, Antonelli A, Ulrici A. Electronic eye for the prediction of parameters related to grape ripening. Talanta 2018; 186:381-388. [DOI: 10.1016/j.talanta.2018.04.076] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 04/19/2018] [Accepted: 04/23/2018] [Indexed: 02/04/2023]
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35
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Bieganowski A, Józefaciuk G, Bandura L, Guz Ł, Łagód G, Franus W. Evaluation of Hydrocarbon Soil Pollution Using E-Nose. SENSORS 2018; 18:s18082463. [PMID: 30061490 PMCID: PMC6111446 DOI: 10.3390/s18082463] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 07/24/2018] [Accepted: 07/27/2018] [Indexed: 01/12/2023]
Abstract
The possibility of detecting low levels of soil pollution by petroleum fuel using an electronic nose (e-nose) was studied. An attempt to distinguish between pollution caused by petrol and diesel oil, and its relation to the time elapsed since the pollution event was simultaneously performed. Ten arable soils, belonging to various soil groups from the World Reference Base (WRB), were investigated. The measurements were performed on soils that were moistened to field capacity, polluted separately with both hydrocarbons, and then allowed to dry slowly over a period of 180 days. The volatile fingerprints differed throughout the course of the experiment, and, by its end, they were similar to those of the unpolluted soils. Principal component analysis (PCA) and artificial neural network (ANN) analysis showed that the e-nose results could be used to detect soil contamination and distinguish between pollutants and contamination levels.
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Affiliation(s)
- Andrzej Bieganowski
- Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland.
| | - Grzegorz Józefaciuk
- Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland.
| | - Lidia Bandura
- Faculty of Civil Engineering and Architecture, Lublin University of Technology, Nadbystrzycka 40, 20-618 Lublin, Poland.
| | - Łukasz Guz
- Faculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B, 20-618 Lublin, Poland.
| | - Grzegorz Łagód
- Faculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B, 20-618 Lublin, Poland.
| | - Wojciech Franus
- Faculty of Civil Engineering and Architecture, Lublin University of Technology, Nadbystrzycka 40, 20-618 Lublin, Poland.
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36
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Nieminen V, Karjalainen M, Salminen K, Rantala J, Kontunen A, Isokoski P, Müller P, Kallio P, Surakka V, Lekkala J. A compact olfactometer for IMS measurements and testing human perception. ACTA ACUST UNITED AC 2018. [DOI: 10.1007/s12127-018-0235-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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37
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Xin R, Liu X, Wei C, Yang C, Liu H, Cao X, Wu D, Zhang B, Chen K. E-Nose and GC-MS Reveal a Difference in the Volatile Profiles of White- and Red-Fleshed Peach Fruit. SENSORS 2018; 18:s18030765. [PMID: 29498705 PMCID: PMC5876536 DOI: 10.3390/s18030765] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 02/24/2018] [Accepted: 03/01/2018] [Indexed: 01/05/2023]
Abstract
First purchases of fruit are mainly dependent on aspects of appearance such as color. However, repeat buys of fruit are determined by internal quality traits such as flavor-related volatiles. Differences in volatile profiles in white- and red-fleshed peach fruit are not well understood. In the present study, peach cultivars with white- and red-fleshed fruit were subjected to sensory analysis using electronic nose (e-nose) to evaluate overview volatile profiles. Approximately 97.3% of the total variation in peach color-volatiles was explained by the first principle component 1 (PC1) and PC2. After analyzing sensory differences between peach fruit samples, 50 volatile compounds were characterized based on GC-MS. Multivariate analysis such as partial least squares discriminant analysis (PLS-DA) was applied to identify volatile compounds that contribute to difference in white- and red-fleshed peach fruit cultivars. A total of 18 volatiles that could separate peach fruit cultivars with different colors in flesh during ripening were identified based on variable importance in projection (VIP) score. Fruity note latone γ-hexalactone had higher contents in red-fleshed cultivars, while grassy note C6 compounds such as hexanal, 2-hexenal, (E)-2-hexenal, 1-hexanol, and (Z)-2-hexen-1-ol showed great accumulation in white-fleshed peach fruit.
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Affiliation(s)
- Rui Xin
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Xiaohong Liu
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Chunyan Wei
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Chong Yang
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Hongru Liu
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Xiangmei Cao
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Di Wu
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Bo Zhang
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
| | - Kunsong Chen
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/Laboratory of Fruit Quality Biology, Zhejiang University, Hangzhou 310058, China.
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Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations. JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING 2018. [DOI: 10.1155/2018/1092718] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Gas sensors have been widely reported for industrial gas detection and monitoring. However, the rapid detection and identification of industrial gases are still a challenge. In this work, we measure four typical industrial gases including CO2, CH4, NH3, and volatile organic compounds (VOCs) based on electronic nose (EN) at different concentrations. To solve the problem of effective classification and identification of different industrial gases, we propose an algorithm based on the selective local linear embedding (SLLE) to reduce the dimensionality and extract the features of high-dimensional data. Combining the Euclidean distance (ED) formula with the proposed algorithm, we can achieve better classification and identification of four kinds of gases. We compared the classification and recognition results of classical principal component analysis (PCA), linear discriminate analysis (LDA), and PCA + LDA algorithms with the proposed SLLE algorithm after selecting the original data and performing feature extraction. The experimental results show that the recognition accuracy rate of the SLLE reaches 91.36%, which is better than the other three algorithms. In addition, the SLLE algorithm provides more efficient and accurate responses to high-dimensional industrial gas data. It can be used in real-time industrial gas detection and monitoring combined with gas sensor networks.
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Design and Evolution of an Opto-electronic Device for VOCs Detection. BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, INTERNATIONAL JOINT CONFERENCE, BIOSTEC ... REVISED SELECTED PAPERS. BIOSTEC (CONFERENCE) 2018; 1:48-55. [PMID: 30079403 DOI: 10.5220/0006558100480055] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Electronic noses (E-noses) are devices capable of detecting and identifying Volatile Organic Compounds (VOCs) in a simple and fast method. In this work, we present the development process of an opto-electronic device based on sensing films that have unique stimuli-responsive properties, altering their optical and electrical properties, when interacting with VOCs. This interaction results in optical and electrical signals that can be collected, and further processed and analysed. Two versions of the device were designed and assembled. E-nose V1 is an optical device, and E-nose V2 is a hybrid opto-electronic device. Both E-noses architectures include a delivery system, a detection chamber, and a transduction system. After the validation of the E-nose V1 prototype, the E-nose V2 was implemented, resulting in an easy-to-handle, miniaturized and stable device. Results from E-nose V2 indicated optical signals reproducibility, and the possibility of coupling the electrical signals to the optical response for VOCs sensing.
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An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems. SENSORS 2017; 17:s17112591. [PMID: 29125586 PMCID: PMC5713038 DOI: 10.3390/s17112591] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 11/06/2017] [Accepted: 11/07/2017] [Indexed: 02/07/2023]
Abstract
The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses.
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Pigani L, Vasile Simone G, Foca G, Ulrici A, Masino F, Cubillana-Aguilera L, Calvini R, Seeber R. Prediction of parameters related to grape ripening by multivariate calibration of voltammetric signals acquired by an electronic tongue. Talanta 2017; 178:178-187. [PMID: 29136810 DOI: 10.1016/j.talanta.2017.09.027] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Revised: 09/07/2017] [Accepted: 09/10/2017] [Indexed: 10/18/2022]
Abstract
An electronic tongue (ET) consisting of two voltammetric sensors, namely a poly-ethylendioxythiophene modified Pt electrode and a sonogel carbon electrode, has been developed aiming at monitoring grape ripening. To test the effectiveness of device and measurement procedures developed, samples of three varieties of grapes have been collected from veraison to harvest of the mature grape bunches. The derived musts have been then submitted to electrochemical investigation using Differential Pulse Voltammetry technique. At the same time, quantitative determination of specific analytical parameters for the evaluation of technological and phenolic maturity of each sample has been performed by means of conventional analytical techniques. After a preliminary inspection by principal component analysis, calibration models were calculated both by partial least squares (PLS) on the whole signals and by the interval partial least squares (iPLS) variable selection algorithm, in order to estimate physico-chemical parameters. Calibration models have been obtained both considering separately the signals of each sensor of the ET, and by proper fusion of the voltammetric data selected from the two sensors by iPLS. The latter procedure allowed us to check the possible complementarity of the information brought by the different electrodes. Good predictive models have been obtained for estimation of pH, total acidity, sugar content, and anthocyanins content. The application of the ET for fast evaluation of grape ripening and of most suitable harvesting time is proposed.
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Affiliation(s)
- L Pigani
- Dipartimento di Scienze Chimiche e Geologiche, Università degli Studi di Modena e Reggio Emilia, Via G. Campi, 103, 41125 Modena, Italy; Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy.
| | - G Vasile Simone
- Dipartimento di Scienze Chimiche e Geologiche, Università degli Studi di Modena e Reggio Emilia, Via G. Campi, 103, 41125 Modena, Italy; Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy
| | - G Foca
- Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy; Dipartimento di Scienze della Vita, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy
| | - A Ulrici
- Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy; Dipartimento di Scienze della Vita, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy
| | - F Masino
- Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy; Dipartimento di Scienze della Vita, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy
| | - L Cubillana-Aguilera
- Institute of Research on Electron Microscopy and Materials, Department of Analytical Chemistry, Faculty of Sciences, Campus de Excelencia Internacional del Mar, University of Cadiz, República Saharaui, S/N, 11510 Puerto Real, Cadiz, Spain
| | - R Calvini
- Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy
| | - R Seeber
- Dipartimento di Scienze Chimiche e Geologiche, Università degli Studi di Modena e Reggio Emilia, Via G. Campi, 103, 41125 Modena, Italy; Centro Interdipartimentale BIOGEST-SITEIA, Università di Modena e Reggio Emilia, Padiglione Besta, Via Amendola, 2, 42122 Reggio Emilia, Italy
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The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment. SENSORS 2017; 17:s17071624. [PMID: 28703760 PMCID: PMC5539596 DOI: 10.3390/s17071624] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 07/08/2017] [Accepted: 07/11/2017] [Indexed: 02/05/2023]
Abstract
The olfactory evaluation function (e.g., odor intensity rating) of e-nose is always one of the most challenging issues in researches about odor pollution monitoring. But odor is normally produced by a set of stimuli, and odor interactions among constituents significantly influenced their mixture’s odor intensity. This study investigated the odor interaction principle in odor mixtures of aldehydes and esters, respectively. Then, a modified vector model (MVM) was proposed and it successfully demonstrated the similarity of the odor interaction pattern among odorants of the same type. Based on the regular interaction pattern, unlike a determined empirical model only fit for a specific odor mixture in conventional approaches, the MVM distinctly simplified the odor intensity prediction of odor mixtures. Furthermore, the MVM also provided a way of directly converting constituents’ chemical concentrations to their mixture’s odor intensity. By combining the MVM with usual data-processing algorithm of e-nose, a new e-nose system was established for an odor intensity rating. Compared with instrumental analysis and human assessor, it exhibited accuracy well in both quantitative analysis (Pearson correlation coefficient was 0.999 for individual aldehydes (n = 12), 0.996 for their binary mixtures (n = 36) and 0.990 for their ternary mixtures (n = 60)) and odor intensity assessment (Pearson correlation coefficient was 0.980 for individual aldehydes (n = 15), 0.973 for their binary mixtures (n = 24), and 0.888 for their ternary mixtures (n = 25)). Thus, the observed regular interaction pattern is considered an important foundation for accelerating extensive application of olfactory evaluation in odor pollution monitoring.
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Shiba K, Tamura R, Imamura G, Yoshikawa G. Data-driven nanomechanical sensing: specific information extraction from a complex system. Sci Rep 2017. [PMID: 28623343 PMCID: PMC5473933 DOI: 10.1038/s41598-017-03875-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Smells are known to be composed of thousands of chemicals with various concentrations, and thus, the extraction of specific information from such a complex system is still challenging. Herein, we report for the first time that the nanomechanical sensing combined with machine learning realizes the specific information extraction, e.g. alcohol content quantification as a proof-of-concept, from the smells of liquors. A newly developed nanomechanical sensor platform, a Membrane-type Surface stress Sensor (MSS), was utilized. Each MSS channel was coated with functional nanoparticles, covering diverse analytes. The smells of 35 liquid samples including water, teas, liquors, and water/EtOH mixtures were measured using the functionalized MSS array. We selected characteristic features from the measured responses and kernel ridge regression was used to predict the alcohol content of the samples, resulting in successful alcohol content quantification. Moreover, the present approach provided a guideline to improve the quantification accuracy; hydrophobic coating materials worked more effectively than hydrophilic ones. On the basis of the guideline, we experimentally demonstrated that additional materials, such as hydrophobic polymers, led to much better prediction accuracy. The applicability of this data-driven nanomechanical sensing is not limited to the alcohol content quantification but to various fields including food, security, environment, and medicine.
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Affiliation(s)
- Kota Shiba
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.
| | - Ryo Tamura
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan. .,Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba, Ibaraki, 305-0047, Japan.
| | - Gaku Imamura
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.,Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba, Ibaraki, 305-0047, Japan.,International Center for Young Scientists (ICYS), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan
| | - Genki Yoshikawa
- World Premier International Research Center Initiative (WPI), International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.,Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, Tennodai 1-1-1 Tsukuba, Ibaraki, 305-8571, Japan
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Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges. SENSORS 2017; 17:s17051073. [PMID: 28486407 PMCID: PMC5470463 DOI: 10.3390/s17051073] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 05/03/2017] [Accepted: 05/03/2017] [Indexed: 12/24/2022]
Abstract
This paper provides a review of the most recent works in machine olfaction as applied to the identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the complexity of growing sources and the diverse specifications of herb components, the quality control of CHMs is a challenging issue. Much research has demonstrated that an electronic nose (E-nose) as an advanced machine olfaction system, can overcome this challenge through identification of the complex odors of CHMs. E-nose technology, with better usability, high sensitivity, real-time detection and non-destructive features has shown better performance in comparison with other analytical techniques such as gas chromatography-mass spectrometry (GC-MS). Although there has been immense development of E-nose techniques in other applications, there are limited reports on the application of E-noses for the quality control of CHMs. The aim of current study is to review practical implementation and advantages of E-noses for robust and effective odor identification of CHMs. It covers the use of E-nose technology to study the effects of growing regions, identification methods, production procedures and storage time on CHMs. Moreover, the challenges and applications of E-nose for CHM identification are investigated. Based on the advancement in E-nose technology, odor may become a new quantitative index for quality control of CHMs and drug discovery. It was also found that more research could be done in the area of odor standardization and odor reproduction for remote sensing.
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Potyrailo RA. Multivariable Sensors for Ubiquitous Monitoring of Gases in the Era of Internet of Things and Industrial Internet. Chem Rev 2016; 116:11877-11923. [DOI: 10.1021/acs.chemrev.6b00187] [Citation(s) in RCA: 224] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Wang H, Zhuang J, Raghupathi KR, Thayumanavan S. A supramolecular dissociation strategy for protein sensing. Chem Commun (Camb) 2016; 51:17265-8. [PMID: 26462172 DOI: 10.1039/c5cc07408h] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We report a simple, robust, and general strategy for protein detection based on supramolecular dissociation. The simplicity of the design is exemplified by the fact that the host assemblies can be widely varied and that these assemblies can be achieved from commercially available surfactants. An operating mechanism that is consistent with all the data has been proposed.
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Affiliation(s)
- Hui Wang
- Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.
| | - Jiaming Zhuang
- Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.
| | - Krishna R Raghupathi
- Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.
| | - S Thayumanavan
- Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.
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Pérez Antón A, Del Nogal Sánchez M, Crisolino Pozas ÁP, Pérez Pavón JL, Moreno Cordero B. Headspace-programmed temperature vaporizer-mass spectrometry and pattern recognition techniques for the analysis of volatiles in saliva samples. Talanta 2016; 160:21-27. [PMID: 27591583 DOI: 10.1016/j.talanta.2016.06.061] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Revised: 06/24/2016] [Accepted: 06/28/2016] [Indexed: 12/25/2022]
Abstract
A rapid method for the analysis of volatiles in saliva samples is proposed. The method is based on direct coupling of three components: a headspace sampler (HS), a programmable temperature vaporizer (PTV) and a quadrupole mass spectrometer (qMS). Several applications in the biomedical field have been proposed with electronic noses based on different sensors. However, few contributions have been developed using a mass spectrometry-based electronic nose in this field up to date. Samples of 23 patients with some type of cancer and 32 healthy volunteers were analyzed with HS-PTV-MS and the profile signals obtained were subjected to pattern recognition techniques with the aim of studying the possibilities of the methodology to differentiate patients with cancer from healthy controls. An initial inspection of the contained information in the data by means of principal components analysis (PCA) revealed a complex situation were an overlapped distribution of samples in the score plot was visualized instead of two groups of separated samples. Models using K-nearest neighbors (KNN) and Soft Independent Modeling of Class Analogy (SIMCA) showed poor discrimination, specially using SIMCA where a small distance between classes was obtained and no satisfactory results in the classification of the external validation samples were achieved. Good results were obtained when Mahalanobis discriminant analysis (DA) and support vector machines (SVM) were used obtaining 2 (false positives) and 0 samples misclassified in the external validation set, respectively. No false negatives were found using these techniques.
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Affiliation(s)
- Ana Pérez Antón
- Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, Universidad de Salamanca, 37008 Salamanca, Spain
| | - Miguel Del Nogal Sánchez
- Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, Universidad de Salamanca, 37008 Salamanca, Spain.
| | - Ángel Pedro Crisolino Pozas
- Servicio de Medicina Interna, Hospital Virgen de la Vega, Complejo Asistencial Universitario de Salamanca, 37007 Salamanca, Spain
| | - José Luis Pérez Pavón
- Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, Universidad de Salamanca, 37008 Salamanca, Spain
| | - Bernardo Moreno Cordero
- Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, Universidad de Salamanca, 37008 Salamanca, Spain
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48
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Cai B, Song Z, Tong Y, Tang Q, Shaymurat T, Liu Y. A Single Nanobelt Transistor for Gas Identification: Using a Gas-Dielectric Strategy. SENSORS 2016; 16:s16060917. [PMID: 27338394 PMCID: PMC4934343 DOI: 10.3390/s16060917] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2016] [Revised: 06/14/2016] [Accepted: 06/14/2016] [Indexed: 12/13/2022]
Abstract
Despite tremendous potential and urgent demand in high-response low-cost gas identification, the development of gas identification based on a metal oxide semiconductor nanowire/nanobelt remains limited by fabrication complexity and redundant signals. Researchers have shown a multisensor-array strategy with "one key to one lock" configuration. Here, we describe a new strategy to create high-response room-temperature gas identification by employing gas as dielectric. This enables gas discrimination down to the part per billion (ppb) level only based on one pristine single nanobelt transistor, with the excellent average Mahalanobis distance (MD) as high as 35 at the linear discriminant analysis (LDA) space. The single device realizes the selective recognition function of electronic nose. The effect of the gas dielectric on the response of the multiple field-effect parameters is discussed by the comparative investigation of gas and solid-dielectric devices and the studies on trap density changes in the conductive channel. The current work opens up exciting opportunities for room-temperature gas recognition based on the pristine single device.
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Affiliation(s)
- Bin Cai
- Key Laboratory of UV Light Emitting Materials and Technology (Northeast Normal University), Ministry of Education, 5268 Renmin Street, Changchun 130024, China.
| | - Zhiqi Song
- Key Laboratory of UV Light Emitting Materials and Technology (Northeast Normal University), Ministry of Education, 5268 Renmin Street, Changchun 130024, China.
| | - Yanhong Tong
- Key Laboratory of UV Light Emitting Materials and Technology (Northeast Normal University), Ministry of Education, 5268 Renmin Street, Changchun 130024, China.
| | - Qingxin Tang
- Key Laboratory of UV Light Emitting Materials and Technology (Northeast Normal University), Ministry of Education, 5268 Renmin Street, Changchun 130024, China.
| | - Talgar Shaymurat
- Key Laboratory of New Energy and Materials Research, Xinjiang Institute of Engineering, Urumqi 830091, China.
| | - Yichun Liu
- Key Laboratory of UV Light Emitting Materials and Technology (Northeast Normal University), Ministry of Education, 5268 Renmin Street, Changchun 130024, China.
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Fraiwan A, Lee H, Choi S. A paper-based cantilever array sensor: Monitoring volatile organic compounds with naked eye. Talanta 2016; 158:57-62. [PMID: 27343578 DOI: 10.1016/j.talanta.2016.05.048] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Revised: 05/14/2016] [Accepted: 05/16/2016] [Indexed: 11/18/2022]
Abstract
Volatile organic compound (VOC) detection is critical for controlling industrial and commercial emissions, environmental monitoring, and public health. Simple, portable, rapid and low-cost VOC sensing platforms offer the benefits of on-site and real-time monitoring anytime and anywhere. The best and most practically useful approaches to monitoring would include equipment-free and power-free detection by the naked eye. In this work, we created a novel, paper-based cantilever sensor array that allows simple and rapid naked-eye VOC detection without the need for power, electronics or readout interface/equipment. This simple VOC detection method was achieved using (i) low-cost paper materials as a substrate and (ii) swellable thin polymers adhered to the paper. Upon exposure to VOCs, the polymer swelling adhered to the paper-based cantilever, inducing mechanical deflection that generated a distinctive composite pattern of the deflection angles for a specific VOC. The angle is directly measured by the naked eye on a 3-D protractor printed on a paper facing the cantilevers. The generated angle patterns are subjected to statistical algorithms (linear discriminant analysis (LDA)) to classify each VOC sample and selectively detect a VOC. We classified four VOC samples with 100% accuracy using LDA.
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Affiliation(s)
- Arwa Fraiwan
- Bioelectronics & Microsystems Laboratory, Department of Electrical & Computer Engineering, State University of New York-Binghamton, Binghamton, NY 13902, USA
| | - Hankeun Lee
- Bioelectronics & Microsystems Laboratory, Department of Electrical & Computer Engineering, State University of New York-Binghamton, Binghamton, NY 13902, USA
| | - Seokheun Choi
- Bioelectronics & Microsystems Laboratory, Department of Electrical & Computer Engineering, State University of New York-Binghamton, Binghamton, NY 13902, USA.
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50
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Lowry TW, Prommapan P, Rainer Q, Van Winkle D, Lenhert S. Lipid Multilayer Grating Arrays Integrated by Nanointaglio for Vapor Sensing by an Optical Nose. SENSORS 2015; 15:20863-72. [PMID: 26308001 PMCID: PMC4570451 DOI: 10.3390/s150820863] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Revised: 07/29/2015] [Accepted: 08/17/2015] [Indexed: 01/06/2023]
Abstract
Lipid multilayer gratings are recently invented nanomechanical sensor elements that are capable of transducing molecular binding to fluid lipid multilayers into optical signals in a label free manner due to shape changes in the lipid nanostructures. Here, we show that nanointaglio is suitable for the integration of chemically different lipid multilayer gratings into a sensor array capable of distinguishing vapors by means of an optical nose. Sensor arrays composed of six different lipid formulations are integrated onto a surface and their optical response to three different vapors (water, ethanol and acetone) in air as well as pH under water is monitored as a function of time. Principal component analysis of the array response results in distinct clustering indicating the suitability of the arrays for distinguishing these analytes. Importantly, the nanointaglio process used here is capable of producing lipid gratings out of different materials with sufficiently uniform heights for the fabrication of an optical nose.
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Affiliation(s)
- Troy W Lowry
- Department of Biological Science and Integrative Nanoscience Institute, Florida State University, 89 Chieftan Way, Tallahassee, FL 32304, USA.
- Department of Physics, Florida State University, 77 Chieftan Way, Tallahassee, FL 32304, USA.
| | - Plengchart Prommapan
- Department of Physics, Florida State University, 77 Chieftan Way, Tallahassee, FL 32304, USA.
| | - Quinn Rainer
- Department of Biological Science and Integrative Nanoscience Institute, Florida State University, 89 Chieftan Way, Tallahassee, FL 32304, USA.
| | - David Van Winkle
- Department of Physics, Florida State University, 77 Chieftan Way, Tallahassee, FL 32304, USA.
| | - Steven Lenhert
- Department of Biological Science and Integrative Nanoscience Institute, Florida State University, 89 Chieftan Way, Tallahassee, FL 32304, USA.
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