Detection of Chemical Warfare Agents by Colorimetric Sensor Arrays

Cell-Free Protein Expression in Polymer Materials

While synthetic biology has advanced complex capabilities such as sensing and molecular synthesis in aqueous solutions, important applications may also be pursued for biological systems in solid materials. Harsh processing conditions used to produce many synthetic materials such as plastics make the incorporation of biological functionality challenging. One technology that shows promise in circumventing these issues is cell-free protein synthesis (CFPS), where core cellular functionality is reconstituted outside the cell. CFPS enables genetic functions to be implemented without the complications of membrane transport or concerns over the cellular viability or release of genetically modified organisms. Here, we demonstrate that dried CFPS reactions have remarkable tolerance to heat and organic solvent exposure during the casting processes for polymer materials. We demonstrate the utility of this observation by creating plastics that have spatially patterned genetic functionality, produce antimicrobials in situ, and perform sensing reactions. The resulting materials unlock the potential to deliver DNA-programmable biofunctionality in a ubiquitous class of synthetic materials.

Deep Learning-Assisted Colorimetric/Electrical Dual-Sensing System for Ultrafast Detection of Hydrogen Sulfide

This study presents a colorimetric/electrical dual-sensing system (CEDS) for low-power, high-precision, adaptable, and real-time detection of hydrogen sulfide (H2S) gas. The lead acetate/poly(vinyl alcohol) (Pb(Ac)2/PVA) nanofiber film was transferred onto a polyethylene terephthalate (PET) flexible substrate by electrospinning to obtain colorimetric/electrical sensors. The CEDS was constructed to simultaneously record both the visual and electrical response of the sensor, and the improved Manhattan segmentation algorithm and deep neural network (DNN) were used as its intelligent algorithmic aids to achieve quantitative exposure to H2S. By exploring the mechanism of color change and resistance response of the sensor, a dual-sensitivity mechanism explanation model was proposed to verify that the system, as a dual-mode parallel system, can adequately solve the sensor redundancy problem. The results show that the CEDS can achieve a wide detection range of H2S from 0.1-100 ppm and identify the H2S concentration in 4 s at the fastest. The sensor can be stabilized for 180 days with excellent selectivity and a low limit of detection (LOD) to 0.1 ppm of H2S. In addition, the feasibility of the CEDS for measuring H2S levels in underground waterways was validated. This work provides a new method for adaptable, wide range of applications and low-power, high-precision H2S gas detection.

Nanosized quantum dots-wrapped metallic particles ensembles integrated into filter disc-based analytical device for garlic evaluation. Application to monitor fake pickled garlic in balsamic vinegar

Herein, an affordable and simple analytical device is presented to portable identify of garlic in 30 min; the evaluation needs no pre-treatment of sample. The analytical device fabrication was did employing a headspace-based nanosensor array using of inexpensive materials as commercial filter discs, quantum dots (QDs), and metallic nanoparticles (MNPs). The nanoarray is fabricated by the accumulation QDs on MNPs surface, that results in the production of ensembles of QDs/MNPs. The ensembles generate diverse colorimetric profiles as "fingerprints" regarding to each garlic sample. The volatile organosulfur compounds (OSCs) of garlic can prefer binding to the MNPs comparing with QDs. The color profiles can be displayed with a smartphone camera, which can be quantitatively distinguished by chemometrics approaches. The analytical device was used to assessment of fake pickled samples in balsamic vinegar. This device proves well potential for qualitative control of garlic.

Wearable Nano-Based Gas Sensors for Environmental Monitoring and Encountered Challenges in Optimization

With a rising emphasis on public safety and quality of life, there is an urgent need to ensure optimal air quality, both indoors and outdoors. Detecting toxic gaseous compounds plays a pivotal role in shaping our sustainable future. This review aims to elucidate the advancements in smart wearable (nano)sensors for monitoring harmful gaseous pollutants, such as ammonia (NH3), nitric oxide (NO), nitrous oxide (N2O), nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), hydrogen sulfide (H2S), sulfur dioxide (SO2), ozone (O3), hydrocarbons (CxHy), and hydrogen fluoride (HF). Differentiating this review from its predecessors, we shed light on the challenges faced in enhancing sensor performance and offer a deep dive into the evolution of sensing materials, wearable substrates, electrodes, and types of sensors. Noteworthy materials for robust detection systems encompass 2D nanostructures, carbon nanomaterials, conducting polymers, nanohybrids, and metal oxide semiconductors. A dedicated section dissects the significance of circuit integration, miniaturization, real-time sensing, repeatability, reusability, power efficiency, gas-sensitive material deposition, selectivity, sensitivity, stability, and response/recovery time, pinpointing gaps in the current knowledge and offering avenues for further research. To conclude, we provide insights and suggestions for the prospective trajectory of smart wearable nanosensors in addressing the extant challenges.

Ni-rGO Sensor Combined with Human Olfactory Receptor-Embedded Nanodiscs for Detecting Gas-Phase DMMP as a Simulant of Nerve Agents

Nerve agents are organophosphorus toxic chemicals that can inhibit acetylcholinesterase, leading to paralysis of the nervous system and death. Early detection of nerve agents is important for safety issues. Dimethyl methylphosphonate (DMMP) is widely used as a simulant of nerve agents, and many studies have been conducted using DMMP as a substitute for detecting nerve agents. Despite many studies on sensors for detecting DMMP, they have limitations in sensitivity and selectivity. To overcome these limitations, a nickel-decorated reduced graphene oxide (Ni-rGO) sensor with human olfactory receptor hOR2T7 nanodiscs was utilized to create a bioelectronic nose platform for DMMP gas detection. hOR2T7 was produced and reconstituted into nanodiscs for enhancing the sensor's stability, especially for detection in a gas phase. It could detect DMMP gas selectively and repeatedly at a concentration of 1 ppb. This sensitive and selective bioelectronic nose can be applied as a practical tool for the detection of gaseous chemical warfare agents in military and safety fields.

High-performance metal-oxide gas sensors based on hierarchical core-shell ZnFe2O4 microspheres for detecting 2-chloroethyl ethyl sulfide

Mustard gas, an erosive chemical agent, is primarily used as a chemical weapon, which seriously threatens human life and health. Therefore, detecting mustard gas and its simulant, 2-chloroethyl ethyl sulfide (2-CEES), is a very important task. As a binary metal oxide with a spinel structure, ZnFe₂O₄ is widely used for fabricating gas sensors because of its stable chemical structure and abundant oxygen vacancies. In this study, gas-sensing ZnFe₂O₄ microspheres with a hierarchical core-shell nanosheet structure were prepared via a simple one-step solvothermal method. Scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and N₂ adsorption analyses were performed to characterize the morphology, structure, and chemical composition of these microspheres. A gas sensor was fabricated from the as-synthesized material, and its gas sensing performance was evaluated, using 2-CEES as a target gas. The obtained ZnFe₂O₄-based sensor exhibited a high sensitivity of 9.07 to 1 ppm 2-CEES at the optimal working temperature of 250 °C. The sensor response and recovery times were 18 and 546 s, respectively, and its detection sensitivity of 2.87 achieved at a 2-CEES concentration of 0.01 ppm was within an acceptable range. Additionally, the sensor demonstrated sufficiently high 2-CEES selectivity, repeatability, and long-term stability.

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Visual and Rapid Detection of Nerve Agent Mimics in Gas and Solution Phase by a Simple Fluorescent Probe

Chemical nerve agents are highly toxic organophosphorus compounds that are easy to obtain and can be utilized by terrorists to threaten homeland security and human safety. Those organophosphorus nerve agents contain nucleophilic ability that can react with acetylcholinesterase leading to muscular paralysis and human death. Therefore, there is great importance to explore a reliable and simple method to detect chemical nerve agents. Herein, the o-phenylenediamine-linked dansyl chloride as a colorimetric and fluorescent probe has been prepared to detect specific chemical nerve agent stimulants in the solution and vapor phase. The o-phenylenediamine unit serves as a detection site that can react with diethyl chlorophosphate (DCP) in a rapid response within 2 min. A satisfied relationship line was obtained between fluorescent intensity and the concentration of DCP in the range of 0-90 μM. In the optimized conditions, we conducted the fluorescent titration to measure the limits of detection (0.082 μM) with the fluorescent enhancement up to 18-fold. Fluorescence titration and NMR studies were also conducted to explore the detection mechanism, indicating that the formation of phosphate ester causes the intensity of fluorescent change during the PET process. Finally, probe 1 coated with the paper test is utilized to detect DCP vapor and solution by the naked eye. We expect that this probe may give some admiration to design the small molecule organic probe and applied in the selectivity detection of chemical nerve agents.

Iron oxides based nanozyme sensor arrays for the detection of active substances in licorice

With the increasing applications of traditional Chinese medicines worldwide, authenticity identification and quality control are significant for them to go global. Licorice is a kind of medicinal material with various functions and wide applications. In this work, colorimetric sensor arrays based on iron oxide nanozymes were constructed to discriminate active indicators in licorice. Fe₂O₃, Fe₃O₄, and His-Fe₃O₄ nanoparticles were synthesized by a hydrothermal method, possessing excellent peroxidase-like activity that can catalyze the oxidation of 3,3',5,5' -tetramethylbenzidine (TMB) in the presence of H₂O₂ to produce a blue product. When licorice active substances were introduced in the reaction system, they showed competitive effect on peroxidase-mimicking activity of nanozymes, resulting in inhibitory effect on the oxidation of TMB. Based on this principle, four licorice active substances including glycyrrhizic acid, liquiritin, licochalcone A, and isolicoflavonol with the concentration ranging from 1 μM to 200 μM were successfully discriminated by the proposed sensor arrays. This work supplies a low cost, rapid and accurate method for multiplex discrimination of active substances to guarantee the authenticity and quality of licorice, which is also expected to be applied to distinguish other substances.

Sensing Gas Mixtures by Analyzing the Spatiotemporal Optical Responses of Liquid Crystals Using 3D Convolutional Neural Networks

We report how analysis of the spatial and temporal optical responses of liquid crystal (LC) films to targeted gases, when performed using a machine learning methodology, can advance the sensing of gas mixtures and provide important insights into the physical processes that underlie the sensor response. We develop the methodology using O₃ and Cl₂ mixtures (representative of an important class of analytes) and LCs supported on metal perchlorate-decorated surfaces as a model system. Although O₃ and Cl₂ both diffuse through LC films and undergo redox reactions with the supporting metal perchlorate surfaces to generate similar initial and final optical states of the LCs, we show that a three-dimensional convolutional neural network can extract feature information that is encoded in the spatiotemporal color patterns of the LCs to detect the presence of both O₃ and Cl₂ species in mixtures and to quantify their concentrations. Our analysis reveals that O₃ detection is driven by the transition time over which the brightness of the LC changes, while Cl₂ detection is driven by color fluctuations that develop late in the optical response of the LC. We also show that we can detect the presence of Cl₂ even when the concentration of O₃ is orders of magnitude greater than the Cl₂ concentration. The proposed methodology is generalizable to a wide range of analytes, reactive surfaces, and LCs and has the potential to advance the design of portable LC monitoring devices (e.g., wearable devices) for analyzing gas mixtures using spatiotemporal color fluctuations.

Ultrafine Silver Nanoparticle Encapsulated Porous Molecular Traps for Discriminative Photoelectrochemical Detection of Mustard Gas Simulants by Synergistic Size-Exclusion and Site-Specific Recognition

The rapid, discriminative, and portable detection of highly toxic chemical warfare agents is extremely important for response to public security emergencies but remains a challenge. One plausible solution involves the integration of porous molecular traps onto a photoelectrochemical (PEC) sensor. Here, a fast and facile protocol is developed to fabricate sub-1 nm AgNPs encapsulated hydrogen-bonded organic framework (HOF) nanocomposite materials through an in situ photoreduction and subsequent encapsulation process. Compared to traditional semiconductors and selected metal-organic frameworks (MOF) materials, these AgNPs@HOFs show significantly enhanced photocurrent. Most importantly, the portable PEC device based on AgNPs@HOF-101 can selectively recognize 13 different mustard gas simulants, including 2-chloroethyl ethyl sulfide (CEES), based on synergistic size-exclusion and specific recognition. The extremely low detection limit for CEES (15.8 nmol L^-1 ), reusability (at least 30 cycles), and long-term working stability (at least 30 d) of the portable PEC device warrant its use as a chemical warfare agents (CWAs) sensor in practical field settings. More broadly, this work indicates that integrating porous molecular traps onto PEC sensors offers a promising strategy to further develop portable devices for CWAs detection with both ultrahigh sensitivity and selectivity.

Advances in Noble-Metal Nanoparticle-Based Fluorescence Detection of Organophosphorus Chemical Warfare Agents

Efficient and simple detection of chemical warfare agents (CWAs) is an essential step in minimizing the potentially lethal consequences of chemical weapons. CWAs are a family of organic chemicals that are used as chemical weapons because of their enormous severity and lethal effects when faced with unforeseen challenges. To stop the spread of CWAs, it is critical to develop a platform that detects them in a sensitive, timely, selective, and minimally invasive manner. Rapid advances in the demand for on-site sensors, metal nanoparticles, and biomarker identification for CWAs have made it possible to use fluorescence as a precise real-time and point-of-care (POCT) testing technique. For POCT-based applications, the new capabilities of micro- and nanomotors offer enormous prospects. In recent decades, significant progress has been made in the design of fluorescent sensors and the further development of noble metal nanoparticles for the detection of organophosphorus CWAs, as described in this review. Through this work, recent attempts to fabricate sensors that can detect organophosphorus CWAs through changes in their fluorescence properties have been summarized. Finally, an integrated outlook on how noble metal nanoparticles could be used to develop smart sensors for organophosphorus CWAs that communicate with and control electronic devices to monitor and improve the health of individuals.

Fast and Selective Detection of Trace Chemical Warfare Agents Enabled by an ESIPT-Based Fluorescent Film Sensor

Reliable detection of airborne chemical warfare agents (CWAs) at the site and in real-time remains a challenge due to the rarity of miniaturized analytical tools. Herein, an o-carborane-functionalized benzothiazole derivative (PCBO) with excited-state intramolecular proton transfer (ESIPT) and AIE characteristics was synthesized. The PCBO-based film sensor showed a highly sensitive response to representative simulants of CWAs, and detection limits were found to be 1.0 mg·m^-3 for triphosgene, 6.0 mg·m^-3 for chloroethyl ethyl sulfide, and 0.2 mg·m^-3 for diethyl chlorophosphite. Moreover, the sensor showed great reusability (>100 cycles) and unprecedented response speed (<0.5 s). The excellent sensing performance was ascribed to the microenvironmental sensitivity of the sensing fluorophore, the porous adlayer structure of the film, and the specific binding of the fluorophore to the analytes. Furthermore, discrimination and identification of the examined CWA simulants were realized via the introduction of another fluorophore (HCBO)-based film. Importantly, a portable fluorescent CWA detector was built with the sensor as the key component, and its applicability was demonstrated by the successful detection of a typical CWA sample (Sarin). The present study indicates that fluorescent film sensors could satisfy reliable onsite and real-time detection of harmful chemicals.

Acoustic Wave Sensors for Detection of Blister Chemical Warfare Agents and Their Simulants

On-site detection and initial identification of chemical warfare agents (CWAs) remain difficult despite the many available devices designed for this type of analysis. Devices using well-established analytical techniques such as ion mobility spectrometry, gas chromatography coupled with mass spectrometry, or flame photometry, in addition to unquestionable advantages, also have some limitations (complexity, high unit cost, lack of selectivity). One of the emerging techniques of CWA detection is based on acoustic wave sensors, among which surface acoustic wave (SAW) devices and quartz crystal microbalances (QCM) are of particular importance. These devices allow for the construction of undemanding and affordable gas sensors whose selectivity, sensitivity, and other metrological parameters can be tailored by application of particular coating material. This review article presents the current state of knowledge and achievements in the field of SAW and QCM-based gas sensors used for the detection of blister agents as well as simulants of these substances. The scope of the review covers the detection of blister agents and their simulants only, as in the available literature no similar paper was found, in contrast to the detection of nerve agents. The article includes description of the principles of operation of acoustic wave sensors, a critical review of individual studies and solutions, and discusses development prospects of this analytical technique in the field of blister agent detection.

Graphene Field Effect Transistors: A Sensitive Platform for Detecting Sarin

Real time, rapid, and accurate detection of chemical warfare agents (CWA) is an ongoing security challenge. Typical detection methods for CWA are adapted from traditional chemistry techniques such as chromatography and mass spectrometry, which lack portability. Here, we address this challenge by evaluating graphene field effect transistors (GFETs) as a sensing platform for sarin gas using both experiment and theory. Experimentally, we measure the sensing response of GFETs when exposed to dimethyl methylphosphonate (DMMP), a less toxic compound used as simulant due to its chemical similarities to sarin. We find low detection limits of 800 ppb, the highest sensitivity reported up to date for this type of sensing platform. In addition to changes in resistance, we implement an in-operando monitor of the GFETs characteristics during and after exposure to the analyte, which gives insights into the graphene-DMMP interactions. Moreover, using theoretical calculations, we show that DMMP and sarin interact similarly with graphene, implying that GFETs should be highly sensitive to detecting sarin. GFETs offer a versatile platform for the development of compact and miniaturized devices that can provide real-time detection of dangerous chemicals in the local environment.

In-situ detoxification of schedule-I chemical warfare agents utilizing Zr(OH)4@W-ACF functional material for the development of next generation NBC protective gears

Chemical warfare agents (CWAs) have become a pivotal concern for the global community and spurred a wide spectrum of research for the development of new generation protective materials. Herein, a highly effective self-detoxifying filter consisting of in-situ immobilized Zirconium hydroxide [Zr(OH)4] over woven activated carbon fabric [Zr(OH)4@W-ACF] is presented for the removal of CWAs. It was prepared to harness the synergistic effect of high surface area of W-ACF, leads to high dispersion of CWAs and high phosphilicity and reactivity of [Zr(OH)4]. The synthesized materials were characterized by ATR-FTIR, EDX, SEM, TEM, XPS, TGA, and BET surface area analyzer. The kinetics of  in-situ degradation of CWAs over Zr(OH)4@W-ACF were studied and found to be following the first-order reaction kinetics. The rate constant was found to be 0.244 min-1 and 2.31 × 10-2 min-1 for sarin and soman, respectively over Zr(OH)4@W-ACF. The potential practical applicability of this work was established by fabricating Zr(OH)4@W-ACF as reactive adsorbent layer for protective suit, and found to be meeting the specified criteria in terms of air permeability, tearing strength and nerve agent permeation as per TOP-08-2-501A:2013 and IS-17380:2020. The degradation products of CWAs were analyzed with NMR and GC-MS. The combined properties of dual functional textile with reactive material are expected to open up new exciting avenues in the field of CWAs protective clothing and thus find diverse application in defence and environmental sector.

3D Core-Shell TiO2@MnO2 Nanorod Arrays on Microcantilevers for Enhancing the Detection Sensitivity of Chemical Warfare Agents

Nanostructured microcantilevers have shown promise for sensing application of molecules in the vapor phase. Nanostructures have improved the molecule capture ability of microcantilevers by highly enhancing the surface of capture. Here, to improve the sensitivity and selectivity of a commercial microcantilever without functionalization, we developed 3D core-shell titanium dioxide@manganese dioxide (TiO₂@MnO₂) nanorod arrays on a microcantilever, which exhibited a high enhancement in the sensing performance beyond that of 1D nanostructures for the detection of dimethyl methylphosphonate, a simulant of sarin.

Blind Spot: A Braille Patterned Novel Multiplex Lateral Flow Immunoassay Sensor Array for the Detection of Biothreat Agents

Lateral flow immunoassays (LFIs) are simple, point-of-care diagnostic devices used for detecting biological agents or other analytes of interest in a sample. LFIs are predominantly singleplex assays, interrogating one target analyte at a time. There is a need for multiplex LFI devices, e.g., a syndromic panel to differentiate pathogens causing diseases exhibiting similar symptoms. Multiplex LFI devices would be especially valuable in instances where sample quantity is limiting and reducing assay time and costs is critical. There are limitations to the design parameters and performance characteristics of a multiplex LFI assay with many horizontal test lines due to constraints in capillary flow dynamics. To address some of the performance issues, we have developed a spot array multiplex LFI using Braille format (hence called Blind Spot) and a sensor, MACAW (Modular Automated Colorimetric Analyses Widget), that can analyze and interpret the results. As a proof of concept, we created a multiplex toxin panel, for detecting three toxins, using two letter codes for each. The results indicated that the six-plex, triple toxin assay performs as well as singleplex assays. The sensor-based calls are better compared to human interpretation in discriminating and interpreting ambiguous test results correctly especially at lower antigen concentrations and from strips with blemishes.

Recent Advances on Detection of Insecticides Using Optical Sensors

Insecticides are enormously important to industry requirements and market demands in agriculture. Despite their usefulness, these insecticides can pose a dangerous risk to the safety of food, environment and all living things through various mechanisms of action. Concern about the environmental impact of repeated use of insecticides has prompted many researchers to develop rapid, economical, uncomplicated and user-friendly analytical method for the detection of insecticides. In this regards, optical sensors are considered as favorable methods for insecticides analysis because of their special features including rapid detection time, low cost, easy to use and high selectivity and sensitivity. In this review, current progresses of incorporation between recognition elements and optical sensors for insecticide detection are discussed and evaluated well, by categorizing it based on insecticide chemical classes, including the range of detection and limit of detection. Additionally, this review aims to provide powerful insights to researchers for the future development of optical sensors in the detection of insecticides.

Colorimetric Sensing of Volatile Organic Compounds Produced from Heated Cooking Oils

Measurement of cooking-associated air pollution indoors is an integral part of exposure monitoring and human health risk assessment. There is a need for easy to use, fast, and economical detection systems to quantify the various emissions from different sources in the home. Addressing this challenge, a colorimetric sensor array (CSA) is reported as a new method to characterize volatile organic compounds produced from cooking, a major contributor to indoor air pollution. The sensor array is composed of pH indicators and aniline dyes from classical spot tests, which enabled molecular recognition of a variety of aldehydes, ketones, and carboxylic acids as demonstrated by hierarchical clustering and principal component analyses. To demonstrate the concept, these CSAs were employed for differentiation of emissions from heated cooking oils (sunflower, rapeseed, olive, and groundnut oils). Sensor results were validated by gas chromatography-mass spectrometry analysis, highlighting the potential of the sensor array for evaluating cooking emissions as a source of indoor air pollution.

Remote Detection of HCN, HF, and Nerve Agent Vapors Based on Self-Referencing, Dye-Impregnated Porous Silicon Photonic Crystals

A one-dimensional photonic crystal is prepared from porous silicon (pSi) and impregnated with a chemically specific colorimetric indicator dye to provide a self-referenced vapor sensor for the selective detection of hydrogen fluoride (HF), hydrogen cyanide (HCN), and the chemical nerve agent diisopropyl fluorophosphate (DFP). The photonic crystal is prepared with two stop bands: one that coincides with the optical absorbance of the relevant activated indicator dye and the other in a spectrally "clear" region, to provide a reference. The inner pore walls of the pSi sample are then modified with octadecylsilane to provide a hydrophobic interior, and the indicator dye of interest is then loaded into the mesoporous matrix. Remote analyte detection is achieved by measurement of the intensity ratio of the two stop bands in the white light reflectance spectrum, which provides a means to reliably detect colorimetric changes in the indicator dye. Indicator dyes were chosen for their specificity for the relevant agents: rhodamine-imidazole (RDI) for HF and DFP, and monocyanocobinamide (MCbi) for HCN. The ratiometric readout allows detection of HF and HCN at concentrations (14 and 5 ppm, respectively) that are below their respective IDLH (immediately dangerous to life and health) concentrations (30 ppm for HF; 50 ppm for HCN); detection of DFP at a concentration of 114 ppb is also demonstrated. The approach is insensitive to potential interferents such as ammonia, hydrogen chloride, octane, and the 43-component mixture of VOCs known as EPA TO-14A, and to variations in relative humidity (20-80% RH). Detection of HF and HCN spiked into the complex mixture EPA TO-14A is demonstrated. The approach provides a general means to construct robust remote detection systems for chemical agents.

Chemical QR Code: A simple and disposable paper-based optoelectronic nose for the identification of olive oil odor

Olive oil is an appreciated food product with high nutritional value, besides being an essential component in many culture diets. In this study, we present for the first time the application of a simple and non-invasive paper-based optoelectronic nose designed in a QR code configuration to evaluate the odor of olive oils. The chemical QR code was fabricated by the addition of 12 dyes, which provided high dimensional data resulting from the interaction between the volatile compounds and the colorimetric array. The color changes were employed to build differential maps with a unique fingerprint (i) to discriminate between olive oil and other edible oil samples; (ii) to quantify nonanaldehyde as an oxidation marker; and (iii) to identify oxidized oils through principal component analysis (PCA) and hierarchical component analysis (HCA). By developing suitable mobile apps, we anticipate the employment of the chemical QR code for portable, low-cost, and in-situ evaluation of food product quality.

Evaluating the Fitness of Combinations of Adsorbents for Quantitative Gas Sensor Arrays

Robust, high-performance gas-sensing technology has applications in industrial process monitoring and control, air quality monitoring, food quality assessment, medical diagnosis, and security threat detection. Nanoporous materials (NPMs) could be utilized as recognition elements in a gas sensor because they selectively adsorb gas. Imitating mammalian olfaction, sensor arrays of NPMs use measurements of the adsorbed mass of gas in a set of distinct NPMs to infer the gas composition. Modular and adjustable NPMs, such as metal-organic frameworks (MOFs), offer a vast material space to sample for combinations to comprise a sensor array that produces a response pattern rich with information about the gas composition. Herein, we frame quantitative gas sensing, using arrays of NPMs, as an inverse problem, which equips us with a method to evaluate the fitness of a proposed combination of NPMs in a sensor array. While the (routine) forward problem is to use an adsorption model to predict the mass of gas adsorbed in each NPM when immersed in a gas mixture of a given composition, the inverse problem is to predict the gas composition from the observed masses of adsorbed gas in the NPMs of the array. The fitness of a given combination of NPMs for gas sensing is then determined by the conditioning of its inverse problem: the prediction of the gas composition provided by a fit (unfit) combination of NPMs is insensitive (sensitive) to inevitable errors in the measurements of the mass of gas adsorbed in the NPMs. For illustration, we use experimentally measured adsorption data to analyze the conditioning of the inverse problem associated with a (IRMOF-1 and HKUST-1) CH₄/CO₂ sensor array.