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Li M, Cucinotta CS, Horsfield AP. A computational model for a molecular chemical sensor. NANOSCALE 2024; 16:5334-5342. [PMID: 38374810 DOI: 10.1039/d3nr05900f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
In this study, we propose that a molecular junction with a sharp Negative Differential Resistance (NDR) current peak could improve the selectivity, thereby functioning as a potential molecular sensor for molecule recognition. Using DFT-NEGF simulations, we investigate the connection between molecule-molecule coupling, molecule-electrode coupling and the corresponding NDR peak shape. Based on this analysis we propose three design rules to control the sensitivity of a sensor and determine that one mechanism for NDR is for a localised molecular orbital involved in resonant tunneling to enter and leave the bias window. Our findings provide useful insight into the development of single molecule sensors for molecule recognition.
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Affiliation(s)
- Mengxuan Li
- Department of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
| | - Clotilde S Cucinotta
- Department of Chemistry, Imperial College London, White City Campus, 82 Wood Lane, London W12 0BZ, UK
| | - Andrew P Horsfield
- Department of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
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Nie L, Xu Z, Wu L, Chen X, Cui Y, Wang Y, Song J, Yao H. Genome-wide identification of protein phosphatase 2C family members in Glycyrrhiza uralensis Fisch. and their response to abscisic acid and polyethylene glycol stress. JOURNAL OF TAIBAH UNIVERSITY FOR SCIENCE 2022. [DOI: 10.1080/16583655.2022.2027650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Liping Nie
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Zhichao Xu
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Liwei Wu
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Xinlian Chen
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Yingxian Cui
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Yu Wang
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Jingyuan Song
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
| | - Hui Yao
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People’s Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing, People’s Republic of China
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Pandey N, Pal D, Saha D, Ganguly S. Vibration-based biomimetic odor classification. Sci Rep 2021; 11:11389. [PMID: 34059734 PMCID: PMC8166841 DOI: 10.1038/s41598-021-90592-x] [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: 01/17/2021] [Accepted: 05/13/2021] [Indexed: 11/21/2022] Open
Abstract
Olfaction is not as well-understood as vision or audition, nor technologically addressed. Here, Chemical Graph Theory is shown to connect the vibrational spectrum of an odorant molecule, invoked in the Vibration Theory of Olfaction, to its structure, which is germane to the orthodox Shape Theory. Atomistic simulations yield the Eigen-VAlue (EVA) vibrational pseudo-spectra for 20 odorant molecules grouped into 6 different ‘perceptual’ classes by odour. The EVA is decomposed into peaks corresponding to different types of vibrational modes. A novel secondary pseudo-spectrum, informed by this physical insight—the Peak-Decomposed EVA (PD-EVA)—has been proposed here. Unsupervised Machine Learning (spectral clustering), applied to the PD-EVA, clusters the odours into different ‘physical’ (vibrational) classes that match the ‘perceptual’, and also reveal inherent perceptual subclasses. This establishes a physical basis for vibration-based odour classification, harmonizes the Shape and Vibration theories, and points to vibration-based sensing as a promising path towards a biomimetic electronic nose.
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Affiliation(s)
- Nidhi Pandey
- Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Debasattam Pal
- Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Dipankar Saha
- Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Swaroop Ganguly
- Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India.
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Kozitsina AN, Svalova TS, Malysheva NN, Okhokhonin AV, Vidrevich MB, Brainina KZ. Sensors Based on Bio and Biomimetic Receptors in Medical Diagnostic, Environment, and Food Analysis. BIOSENSORS 2018; 8:E35. [PMID: 29614784 PMCID: PMC6022999 DOI: 10.3390/bios8020035] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 03/29/2018] [Accepted: 03/29/2018] [Indexed: 01/09/2023]
Abstract
Analytical chemistry is now developing mainly in two areas: automation and the creation of complexes that allow, on the one hand, for simultaneously analyzing a large number of samples without the participation of an operator, and on the other, the development of portable miniature devices for personalized medicine and the monitoring of a human habitat. The sensor devices, the great majority of which are biosensors and chemical sensors, perform the role of the latter. That last line is considered in the proposed review. Attention is paid to transducers, receptors, techniques of immobilization of the receptor layer on the transducer surface, processes of signal generation and detection, and methods for increasing sensitivity and accuracy. The features of sensors based on synthetic receptors and additional components (aptamers, molecular imprinted polymers, biomimetics) are discussed. Examples of bio- and chemical sensors' application are given. Miniaturization paths, new power supply means, and wearable and printed sensors are described. Progress in this area opens a revolutionary era in the development of methods of on-site and in-situ monitoring, that is, paving the way from the "test-tube to the smartphone".
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Affiliation(s)
- Alisa N Kozitsina
- Department of Analytical Chemistry, Institute of Chemical Engineering, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Yekaterinburg, Russia.
| | - Tatiana S Svalova
- Department of Analytical Chemistry, Institute of Chemical Engineering, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Yekaterinburg, Russia.
| | - Natalia N Malysheva
- Department of Analytical Chemistry, Institute of Chemical Engineering, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Yekaterinburg, Russia.
| | - Andrei V Okhokhonin
- Department of Analytical Chemistry, Institute of Chemical Engineering, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Yekaterinburg, Russia.
| | - Marina B Vidrevich
- Scientific and Innovation Center for Sensory Technologies, Ural State University of Economics, 620144 Yekaterinburg, Russia.
| | - Khiena Z Brainina
- Department of Analytical Chemistry, Institute of Chemical Engineering, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Yekaterinburg, Russia.
- Scientific and Innovation Center for Sensory Technologies, Ural State University of Economics, 620144 Yekaterinburg, Russia.
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