A Colorimetric Artificial Olfactory System for Airborne Improvised Explosive Identification

Extrusion Printing of Surface-Functionalized Metal-Organic Framework Inks for a High-Performance Wearable Volatile Organic Compound Sensor

Wearable sensors hold immense potential for real-time and non-destructive sensing of volatile organic compounds (VOCs), requiring both efficient sensing performance and robust mechanical properties. However, conventional colorimetric sensor arrays, acting as artificial olfactory systems for highly selective VOC profiling, often fail to meet these requirements simultaneously. Here, a high-performance wearable sensor array for VOC visual detection is proposed by extrusion printing of hybrid inks containing surface-functionalized sensing materials. Surface-modified hydrophobic polydimethylsiloxane (PDMS) improves the humidity resistance and VOC sensitivity of PDMS-coated dye/metal-organic frameworks (MOFs) composites. It also enhances their dispersion within liquid PDMS matrix, thereby promoting the hybrid liquid as high-quality extrusion-printing inks. The inks enable direct and precise printing on diverse substrates, forming a uniform and high particle-loading (70 wt%) film. The printed film on a flexible PDMS substrate demonstrates satisfactory flexibility and stretchability while retaining excellent sensing performance from dye/MOFs@PDMS particles. Further, the printed sensor array exhibits enhanced sensitivity to sub-ppm VOC levels, remarkable resistance to high relative humidity (RH) of 90%, and the differentiation ability for eight distinct VOCs. Finally, the wearable sensor proves practical by in situ monitoring of wheat scab-related VOC biomarkers. This study presents a versatile strategy for designing effective wearable gas sensors with widespread applications.

Human somatosensory systems based on sensor-memory-integrated technology

As a representative artificial neural network (ANN) for incorporating sensing functions and memory functions into one system to achieve highly miniaturized and highly integrated devices or systems, artificial sensory systems (ASSs) can have a far-reaching influence on precise instrumentation, sensing, and automation engineering. Artificial sensory systems have enjoyed considerable progress in recent years, from low degree integrations to highly advanced sophisticated integrations, from single-modal perceptions to multimode-fused perceptions. However, there are issues around the large hardware area, power consumption, and communication bandwidth needed during the processes where multimodal sensing signals are converted into a digital mode before they can be processed by a digital processor. Therefore, deepening the research into sensory integration is of great importance. In this review, we briefly introduce fundamental knowledge about the memristor mechanism, describe some representative human somatosensory systems, and elucidate the relationship between the properties of memristor devices and the structure. The electronic character of the sensors, future prospects, and key challenges surrounding sensor-memory integrated technologies are also discussed.

Smart materials for flexible electronics and devices: hydrogel

In recent years, flexible conductive materials have attracted considerable attention for their potential use in flexible energy storage devices, touch panels, sensors, memristors, and other applications. The outstanding flexibility, electricity, and tunable mechanical properties of hydrogels make them ideal conductive materials for flexible electronic devices. Various synthetic strategies have been developed to produce conductive and environmentally friendly hydrogels for high-performance flexible electronics. In this review, we discuss the state-of-the-art applications of hydrogels in flexible electronics, such as energy storage, touch panels, memristor devices, and sensors like temperature, gas, humidity, chemical, strain, and textile sensors, and the latest synthesis methods of hydrogels. Describe the process of fabricating sensors as well. Finally, we discussed the challenges and future research avenues for flexible and portable electronic devices based on hydrogels.

Design of Highly Efficient Electronic Energy Transfer in Functionalized Quantum Dots Driven Specifically by Ethylenediamine

The exploration of emerging functionalized quantum dots (QDs) through modulating the effective interaction between the sensing element and target analyte is of great significance for high-performance trace sensing. Here, the chromone-based ligand grafted QDs (QDs-Chromone) were initiated to realize the electronic energy transfer (EET) driven specifically by ethylenediamine (EDA) in the absence of spectral overlap. The fluorescent and colorimetric dual-mode responses (from red to blue and from colorless to yellow, respectively) resulting from the expanded conjugated ligands reinforced the analytical selectivity, endowing an ultrasensitive and specific response to submicromolar-liquid of EDA. In addition, a QDs-Chromone-based sensing chip was constructed to achieve the ultrasensitive recognition of EDA vapor with a naked-eye observed response at a concentration as low as 10 ppm, as well as a robust anti-interfering ability in complicated scenarios monitoring. We expect the proposed EET strategy in shaping functionalized QDs for high-performance sensing will shine light on both rational probe design methodology and deep sensing mechanism exploration.

Interfacially Confined Dynamic Reaction Resulted to Fluorescent Nanofilms Depicting High-Performance Ammonia Sensing

Sensing materials innovation plays a crucial role in the development of high-performance film-based fluorescent sensors (FFSs). In our current study, we present the innovative fabrication of four fluorescent nanofilms via interfacially confined dynamic reaction of a specially designed fluorescent building block, a new boron-coordinated compound (NI-CHO), with a chosen one, benzene-1,3,5-tricarbohydrazide (BTH). The nanofilms as prepared are robust, uniform, flexible, and thickness tunable, at least from 40 to 1500 nm. The fabricated FFSs based on Film 3, one of the four nanofilms, shows highly selective and fully reversible response to NH3 vapor with an experimental detection limit of <0.1 ppm and a response time of 0.2 s. The unprecedented high performance of the nanofilm is ascribed to the specific quenching of its fluorescence emission owing to formation of an excited-state complex between the sensing unit and the analyte molecule. Efficient mass transfer also contributes to the high performance owing to the porous adlayer structure of the nanofilm. This work provides an example to show how to develop a high-performance sensing film via controlling the film's structure, especially the thickness.

Machine Learning-Assisted Janus Colorimetric Face Mask for Breath Ammonia Analysis

Artificial olfactory systems have been widely used in medical fields such as in the analysis of volatile organic compounds (VOCs) in human exhaled breath. However, there is still an urgent demand for a portable, accurate breath VOC analysis system for the healthcare industry. In this work, we proposed a Janus colorimetric face mask (JCFM) for the comfortable evaluation of breath ammonia levels by combining the machine learning K-nearest neighbor (K-NN) algorithm. Such a Janus fabric is designed for the unidirectional penetration of exhaled moisture, which can reduce stickiness and ensure facial dryness and comfort. Four different pH indicators on the colorimetric array serve as recognition elements that cross-react with ammonia, capturing the optical fingerprint information on breath ammonia by mimicking the sophisticated olfactory structure of mammals. The Euclidean distance (ED) is used to quantitatively describe the ammonia concentration between 1 ppm and 10 ppm, indicating that there is a linear relationship between the ammonia concentration and the ED response (R2 = 0.988). The K-NN algorithm based on RGB response features aids in the analysis of the target ammonia level and achieves a prediction accuracy of 96%. This study integrates colorimetry, Janus design, and machine learning to present a wearable and portable sensing system for breath ammonia analysis.

An Artificial Olfactory System Based on a Memristor Can Simulate Organ Injury and Functions in Air Purification

Artificial olfactory systems are receiving increasing attention because of their potential applications in humanoid robots, artificial noses, and the next generation of human-computer interactions. However, simulating the human olfactory system, which recognizes, remembers, and automatically takes protective measures against gases, remains a challenge. In this paper, a WO3-TiO2@Ag NPs (silver nanoparticle) gas sensor was prepared by the sol-gel method, and an Al/pectin:AgNP/ITO memristor was prepared by spin coating and vacuum evaporation. The gas sensor has been combined with the memristor to simulate physical damage to humans in a dangerous gas environment for a long time, and an artificial olfactory system is constructed by field-programmable gate array external control. The WO3-TiO2@Ag NPs gas sensor can sense and identify ethanol vapor through changes in resistance, and the signal transmitted to the pectin-based memristor can switch the resistance state of the memristor to store gas information. Furthermore, the activation of the memristor can also trigger rotation of the fan to purify the gas and reduce damage caused by excessive exposure to dangerous gases. This artificial olfactory system provides a promising strategy for the development of artificial intelligence and human-computer interaction systems.

Energy Efficient Artificial Olfactory System with Integrated Sensing and Computing Capabilities for Food Spoilage Detection

Artificial olfactory systems (AOSs) that mimic biological olfactory systems are of great interest. However, most existing AOSs suffer from high energy consumption levels and latency issues due to data conversion and transmission. In this work, an energy- and area-efficient AOS based on near-sensor computing is proposed. The AOS efficiently integrates an array of sensing units (merged field effect transistor (FET)-type gas sensors and amplifier circuits) and an AND-type nonvolatile memory (NVM) array. The signals of the sensing units are directly connected to the NVM array and are computed in memory, and the meaningful linear combinations of signals are output as bit line currents. The AOS is designed to detect food spoilage by employing thin zinc oxide films as gas-sensing materials, and it exhibits low detection limits for H2 S and NH3 gases (0.01 ppm), which are high-protein food spoilage markers. As a proof of concept, monitoring the entire spoilage process of chicken tenderloin is demonstrated. The system can continuously track freshness scores and food conditions throughout the spoilage process. The proposed AOS platform is applicable to various applications due to its ability to change the sensing temperature and programmable NVM cells.

Four levels of in-sensor computing in bionic olfaction: from discrete components to multi-modal integrations

Sensing and computing are two important ways in which humans attempt to perceive and understand the analog world through digital devices. Analog-to-digital converters (ADCs) discretize analog signals while the data bus transmits digital data between the components of a computer. With the increase in sensor nodes and the application of deep neural networks, the energy and time consumption limit the increment of data throughput. In-sensor computing is a computing paradigm that integrates sensing, storage, and processing in one device without ADCs and data transfer. According to the integration degree, herein, we summarize four levels of in-sensor computing in the field of artificial olfactory. In the first level, we show that different functions are conducted by using discrete components. Next, the data conversion and transfer are exempt within the in-memory computing architecture with necessary data encoding. Subsequently, in-sensor computing is integrated into a single device. Finally, multi-modal in-sensor computing is proposed to improve the quality and reliability of the classification results. At the end of this minireview, we provide an outlook on the use of metal nanoparticle devices to achieve such in-sensor computing for bionic olfaction.

Functionalized Hydrogel-Based Wearable Gas and Humidity Sensors

Breathing is an inherent human activity; however, the composition of the air we inhale and gas exhale remains unknown to us. To address this, wearable vapor sensors can help people monitor air composition in real time to avoid underlying risks, and for the early detection and treatment of diseases for home healthcare. Hydrogels with three-dimensional polymer networks and large amounts of water molecules are naturally flexible and stretchable. Functionalized hydrogels are intrinsically conductive, self-healing, self-adhesive, biocompatible, and room-temperature sensitive. Compared with traditional rigid vapor sensors, hydrogel-based gas and humidity sensors can directly fit human skin or clothing, and are more suitable for real-time monitoring of personal health and safety. In this review, current studies on hydrogel-based vapor sensors are investigated. The required properties and optimization methods of wearable hydrogel-based sensors are introduced. Subsequently, existing reports on the response mechanisms of hydrogel-based gas and humidity sensors are summarized. Related works on hydrogel-based vapor sensors for their application in personal health and safety monitoring are presented. Moreover, the potential of hydrogels in the field of vapor sensing is elucidated. Finally, the current research status, challenges, and future trends of hydrogel gas/humidity sensing are discussed.

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.

Instant Fingerprint Discrimination for Military Explosive Vapors by Dy3+ Doping a La2O3-Based Cataluminescence Sensor System

With the intensification of explosive-based terrorism attack and environmental concerns, the innovation of high-efficiency and portable sensors for facile, rapid, and reliable monitoring of explosives has become one of the major demands in societies. Herein, a reliable and easy-to-use cataluminescence sensor system based on Dy³⁺ doping La₂O₃ nanorod catalysts has been developed for the identification and detection of six types of military explosive vapors, including homologous compounds and even isomers. The efficient discrimination is to make full use of the thermodynamic and kinetic information that can be extracted from the catalytic oxidation process of explosive molecules on various sensing materials, that is, the response signal and response time to generate the fingerprint of each target compound, while the rapid detection of the strategy can be manifested in response toward six military explosive vapors within 2.5 s and recover within 4 s. Meanwhile, the quantitative analysis of the explosives by the sensor system was realized based on 0.8%Dy:La₂O₃ with optimal catalytic activity, and the detection limits of NB, m-MNT, m-DNB, PNT, DNT, and TNT can reach 0.62, 0.49, 0.63, 0.38, 0.023, and 0.067 μg mL^-1. In this research, we also constructed a novel sensor device and detection platform for explosive monitoring, which is of great significance for providing a new sensing principle for the efficient identification of explosives.

Visual-Olfactory Synergistic Perception Based on Dual-Focus Imaging and a Bionic Learning Architecture

The synergistic interaction of vision and olfaction is critical for both natural and artificial intelligence systems to recognize and adapt to complex environments. However, current bioinspired systems with visual and olfactory sensations are mostly assembled with separate and heterogeneous sensors, inevitably leading to bulky systems and incompatible datasets. Here, we demonstrate on-chip integration of visual and olfactory sensations through a dual-focus imaging approach. By combining lens-based visual imaging and lensless colorimetric imaging, a target object and its odor fingerprint can be captured with a single complementary metal-oxide-semiconductor imager, and the obtained multimodal images are analyzed with a bionic learning architecture for information fusion and perception. To demonstrate the capability of this system, we adapted it to food detection and achieved 100% accuracy in identifying meat freshness and category with a 10 s sampling time. In addition to the highly integrated sensor design, our approach exhibits superior accuracy and efficiency in object recognition, providing a promising approach for robotic sensing and perception.

Flexible Aggregation-Induced Emission-Active Hydrogel for On-Site Monitoring of Pesticide Degradation

Benefiting from the stimuli-responsive property and powerful loading capacity, functionalized hydrogels are favorable for the fabrication of sensing devices. Herein, we design aggregation-induced emission (AIE)-active hydrogel discs by embedding gold nanoclusters@zeolite-like imidazole framework (AuNCs@ZIF) composites in double-network hydrogels to build a sensitive pesticide biosensor. The hydrogel discs integrate an AIE effect of AuNCs, a stimuli-responsive property of ZIF, and a porous network structure of the hydrogel, which enhances the sensing sensitivity via boosting the stable fluorescent signal and antifouling performance. In conjunction with a homemade device, the fluorescence images of hydrogel discs could be transduced into data information for accurate quantification of chlorpyrifos pesticide with a detection limit of 0.2 ng/mL. The dynamic degradation of chlorpyrifos in Chinese cabbage is demonstrated to confirm the practical application of hydrogel discs. Such AIE-active hydrogel discs could be a plant health sensor for the on-site quantification of pesticide residues on crops, holding great promise for precision agriculture.

Polyethyleneimine-capped copper nanoclusters for detection and discrimination of 2,4,6-trinitrotoluene and 2,4,6-trinitrophenol

The detection and discrimination of 2,4,6-trinitrotoluene (TNT) and 2,4,6-trinitrophenol (TNP) from analogues are of great importance to global security and are full of challenges in the field of trace sensing. Here, benefitting from the strong electrophilicity of TNT, a sensing strategy is established by synthesizing polyethyleneimine capped copper nanoclusters (PEI-Cu NCs) with abundant -NH₂ groups. By carefully controlling the size and structure of PEI-Cu NCs, Förster resonance energy transfer (FRET) from PEI-Cu NCs to the Meisenheimer complex occurs resulting from their spectral overlap when detecting TNT, while, due to the energy level match of TNP with PEI-Cu NCs, as well as the strong affinity between its -OH and -NH₂ in PEI-Cu NCs, photo-induced electron transfer (PET) is feasibly expected. As a result, TNT and TNP could be detected from 26 types of analogues and cations with a limit of detection (LOD) of 26.57 and 12.82 nM, respectively. Besides, owing to the brown color of the Meisenheimer complex, the discrimination of TNT and TNP could be additionally realized by colorimetric detection. We expect that the proposed methodology would not only shine light on the detection and discrimination of TNT and TNP that mitigate against public security concerns, but also pave a way for the deep understanding of FRET and PET related fluorescence quenching mechanisms from the aspect of controllable sensing material design and synthesis.

Humidity-Independent Artificial Olfactory Array Enabled by Hydrophobic Core-Shell Dye/MOFs@COFs Composites for Plant Disease Diagnosis

As a class of important artificial olfactory system, the colorimetric sensor array possesses great potential for commercialization due to its cost-effectiveness and portability. However, when applied to practical applications, the humidity interference from ambient environment and dissatisfactory sensitivity for trace target VOCs are largely unsolved problems. To overcome the problems, we developed a series of dye/MOFs@COFs gas-sensing materials with core-shell structure using a hydrophobization strategy by encapsulation of dye/metal-organic frameworks (MOFs) into hydrophobic covalent organic frameworks (COFs). Benefiting from the hydrophobic property of the COF shell, the dye/MOFs@COFs composites were endowed with excellent humidity-resistance even under 100% relative humidity (RH). Moreover, due to the uniform distribution of dyes on the porous MOFs, the dye/MOFs@COFs sensors also exhibited improved sensitivity at the sub-ppm level, compared with conventional dye sensors. On basis of the excellent humidity-resistance and improved sensitivity, an artificial olfactory array based on dye/MOFs@COFs composites was proven to be a successful practical application in early and accurate detection of wheat scab (1 day after inoculation) by monitoring its released VOC markers. The synthetic strategy for core-shell dye/MOFs@COFs is applicable to a wide range of colorimetric sensor arrays, endowing them with excellent humidity-resistance and sensitivity for the feasibility of practical applications.

Complete Inhibition of the Rotation in a Barrierless TICT Probe for Fluorescence-On Qualitative Analysis

Inhibition of twisting intramolecular charge transfer (TICT) is one of the most attractive methods for fluorescence-on analysis, whereas it remains enigmatic whether the fluorescence in a TICT-based probe could be thoroughly lightened. Here, for maximizing the fluorescence-on signal of the TICT-based probe, we develop a model by employing chemical reaction to directly cleave the linkage between the rotational electron donor and acceptor with a predisposed fluorescent signal close to zero. To validate this assumption, a nonfluorescent probe with barrierless rotation is successfully achieved by grafting acryloyl with -C═C- recognition sites onto coumarin, and 7-hydroxycoumarin with bright blue fluorescence could be released within 3 s upon probing KMnO₄ with an amount as low as 0.95 nM and 6.6 pg. We believe that the present strategy could not only deepen the insights of photochemistry but also facilitate the development of a theranostic drug delivery system, energy conversion, pollution control, and health risk reduction.

Electronic Tuning in Reaction-Based Fluorescent Sensing for Instantaneous and Ultrasensitive Visualization of Ethylenediamine

Manipulation of a multi-physical quantity to steer a molecular photophysical property is of great significance in improving sensing performance. Here, an investigation on how a physical quantity rooted in the molecular structure induces an optical behavior change to facilitate ultrasensitive detection of ethylenediamine (EDA) is performed by varying a set of thiols. The model molecule consisting of a thiol with dual-carboxyl exhibits the strongest fluorescence, which is ascribed to the electron-donating ability and prompted larger orbital overlap and oscillator strength. The elevated fluorescence positively corelated to the increased EDA, endowing an ultrasensitive response to the nanomolar-liquid/ppm-vapor. A gas detector with superior performance fulfills a contactless and real-time management of EDA. We envisage this electron-tuning strategy-enabled fluorescence enhancement can offer in-depth insight in advancing molecule-customized design, further paving the way to widening applications.

Recent Advances in Transistor-Based Bionic Perceptual Devices for Artificial Sensory Systems

The sensory nervous system serves as the window for human beings to perceive the outside world by converting external stimuli into distinctive spiking trains. The sensory neurons in this system can process multimodal sensory signals with extremely low power consumption. Therefore, new-concept devices inspired by the sensory neuron are promising candidates to address energy issues in nowadays’ robotics, prosthetics and even computing systems. Recent years have witnessed rapid development in transistor-based bionic perceptual devices, and it is urgent to summarize the research and development of these devices. In this review, the latest progress of transistor-based bionic perceptual devices for artificial sense is reviewed and summarized in five aspects, i.e., vision, touch, hearing, smell, and pain. Finally, the opportunities and challenges related to these areas are also discussed. It would have bright prospects in the fields of artificial intelligence, prosthetics, brain-computer interface, robotics, and medical testing.

A novel colorimetric sensor array for real-time and on-site monitoring of meat freshness

Food quality control is essential in industry and daily life. In this work, we developed a novel colorimetric sensor array composed of several pH-sensitive dyes for monitoring meat freshness. A color change in the sensor array was seen after exposure to volatile organic compounds (VOCs), and the images were captured for precise quantification of the VOCs. In conjunction with pattern recognition, meat freshness at different storage periods was readily discerned, revealing that the as-fabricated colorimetric sensor array possessed excellent discrimination ability. The linear range for quantitative analysis of volatiles related to meat spoilage was from 5 ppm to 100 ppm, with a limit of detection at the ppb level (S/N = 3). Furthermore, the testing results obtained by the sensor in assessing meat freshness were validated by a standard method for measuring the total volatile basic nitrogen (TVB-N). The sensing signals showed good agreement with the results obtained in TVB-N when measuring real food samples. The sensor also displayed good reproducibility (RSD < 5%) and long-term stability. The sensor was successfully used for on-site and real-time determination of volatiles emitted from rotting meat, demonstrating its potential application in monitoring the quality and safety of meat products.

Cobalt Metal-Organic Frameworks with Aggregation-Induced Emission Characteristics for Fluorometric/Colorimetric Dual Channel Detection of Nitrogen-Rich Heterocyclic Compounds

Nitrogen-rich heterocyclic compounds (NRHCs) are an emerging type of explosive, and their quantification is important in national security inspection and environmental monitoring. Up until now, designing an efficient NRHCs sensing strategy was still in the early stages. Herein, a new metal-organic framework (MOF) with aggregation-induced emission (AIE) characteristics is synthesized with fluorometric/colorimetric responses for rapid and selective detection of NRHCs. The nonemissive probe is designed with tetraphenylethylene derivative as the linker and Co as the node, quencher, and color-changing agent. Cobalt AIE-MOF exhibits a turn-on emission enhancement due to the competitive coordination substitution between NRHCs and the scaffold as well as the following AIE process of the liberative linkers. Meanwhile, the color appearance of the probe changes from blue to yellow based on the dissociation of the original Co coordinating system. Using this dual-mode probe, single- and dual-ring NRHCs are successfully detected from 5 μM to 7.5 mM within 25 s. The cobalt AIE-MOF exhibits excellent selectivity of NRHCs against a variety of interferences, providing a promising tool for designing a multichannel detection strategy.

A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments

Object recognition is among the basic survival skills of human beings and other animals. To date, artificial intelligence (AI) assisted high-performance object recognition is primarily visual-based, empowered by the rapid development of sensing and computational capabilities. Here, we report a tactile-olfactory sensing array, which was inspired by the natural sense-fusion system of star-nose mole, and can permit real-time acquisition of the local topography, stiffness, and odor of a variety of objects without visual input. The tactile-olfactory information is processed by a bioinspired olfactory-tactile associated machine-learning algorithm, essentially mimicking the biological fusion procedures in the neural system of the star-nose mole. Aiming to achieve human identification during rescue missions in challenging environments such as dark or buried scenarios, our tactile-olfactory intelligent sensing system could classify 11 typical objects with an accuracy of 96.9% in a simulated rescue scenario at a fire department test site. The tactile-olfactory bionic sensing system required no visual input and showed superior tolerance to environmental interference, highlighting its great potential for robust object recognition in difficult environments where other methods fall short.

A Bioinspired Adhesive-Integrated-Agent Strategy for Constructing Robust Gas-Sensing Arrays

Gas sensors based on organic molecules are attractive for their tailored molecular structures and controllable functions, but weak interfacial adhesion between sensing materials and supporting substrates has severely hampered their practical applications, particularly in harsh environments. Here, inspired by the combined anchoring-recognizing feature of natural olfactory systems, an adhesive-integrated-agent strategy to integrate the adhesive unit (poly(dimethylsiloxane)) with the sensing unit (organoplatinum(II)) into one chemistry entity, creating robust and sensitive nanobelt array gas sensors is demonstrated. Systematic theoretical and experimental studies reveal that incorporating adhesive units significantly enhances the interfacial adhesion of the array sensors and gas-bridged super-exchange electronic couplings of sensing units ensure their efficient gas-sensing performance. The high shear strength of ≈7.05 × 10⁶ N m^-2 allows these arrays to resist aggressive ultrasonication, tape peeling, or repeated bending without compromising their sensing performance. This molecular engineering strategy opens a new guideline to develop robust gas sensors.

Free-standing, thin-film sensors for the trace detection of explosives

In a world focused on the development of cybersecurity, many densely populated areas and transportation hubs are still susceptible to terrorist attacks via improvised explosive devices (IEDs). These devices frequently employ a combination of peroxide based explosives as well as nitramines, nitrates, and nitroaromatics. Detection of these explosives can be challenging due to varying chemical composition and the extremely low vapor pressures exhibited by some explosive compounds. No electronic trace detection system currently exists that is capable of continuously monitoring both peroxide based explosives and certain nitrogen based explosives, or their precursors, in the vapor phase. Recently, we developed a thermodynamic sensor that can detect a multitude of explosives in the vapor phase at the parts-per-trillion (ppt) level. The sensors rely on the catalytic decomposition of the explosive and specific oxidation–reduction reactions between the energetic molecule and metal oxide catalyst; i.e. the heat effects associated with catalytic decomposition and redox reactions between the decomposition products and catalyst are measured. Improved sensor response and selectivity were achieved by fabricating free-standing, ultrathin film (1 µm thick) microheater sensors for this purpose. The fabrication method used here relies on the interdiffusion mechanics between a copper (Cu) adhesion layer and the palladium (Pd) microheater sensor. A detailed description of the fabrication process to produce a free-standing 1 µm thick sensor is presented.

Ultrasensitive, Specific, and Rapid Fluorescence Turn-On Nitrite Sensor Enabled by Precisely Modulated Fluorophore Binding

The precise regulation of fluorophore binding sites in an organic probe is of great significance toward the design of fluorescent sensing materials with specific functions. In this study, a probe with specific fluorescence properties and nitrite detection ability is designed by precisely modulating benzothiazole binding sites. Only the fluorophore bond at the ortho-position of the aniline moiety can specifically recognize nitrite, which ensures that the reaction products displays a robust green emission. The unique 2-(2-amino-4-carboxyphenyl) benzothiazole (ortho-BT) shows superior nitrite detection performance, including a low detection limit (2.2 fg), rapid detection time (<5 s), and excellent specificity even in the presence of >40 types of strong redox active, colored substances, nitro compounds, and metal ions. Moreover, the probe is highly applicable for the rapid on-site and semiquantitative measurement of nitrite. The proposed probe design strategy is expected to start a new frontier for the exploration of probe design methodology.

Trace Detection and Chemical Analysis of Homemade Fuel-Oxidizer Mixture Explosives: Emerging Challenges and Perspectives

The chemical analysis of homemade explosives (HMEs) and improvised explosive devices (IEDs) remains challenging for fieldable analytical instrumentation and sensors. Complex explosive fuel-oxidizer mixtures, black and smokeless powders, flash powders, and pyrotechnics often include an array of potential organic and inorganic components that present unique interference and matrix effect difficulties. The widely varying physicochemical properties of these components as well as external environmental interferents and background challenge many sampling and sensing modalities. This review provides perspective on these emerging challenges, critically discusses developments in sampling, sensors, and instrumentation, and showcases advancements for the trace detection of inorganic-based explosives.

One-Step Instantaneous Detection of Multiple Military and Improvised Explosives Facilitated by Colorimetric Reagent Design

Although colorimetric detection based on reagents has been widely used in the fields of practical trace analysis, its versatility for detecting multitargets remains the most challenging problem. As a proof of concept, a general colorimetric reagent based on potassium isopropanol (C₃H₇KO) and dimethyl sulfoxide for one-step instantaneous detection and discrimination of typical military and improvised explosives was designed. Vivid colors from none to purple red, blue green, yellow green, and green were shown, respectively, when detecting 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), elemental sulfur (S), and potassium permanganate (KMnO₄). The unique design including the specific nucleophilic addition reaction and the base-catalyzed oxidation-induced electron transfer ensures perfect selectivity even upon facing more than 20 interferents. It is further experimentally demonstrated that the confinement effect introduced by Tween-20 plays an essential role in enhancing the color signal on the surface and thus boosts the detection performance even with a mass as low as 1.45 ng. The applicability of this versatile colorimetric reagent was further verified by integrating the reagent onto paper strips for the in-field identification of TNT, DNT, S, and KMnO₄ with the help of a portable smartphone-based microscope apparatus, and a practical detection mass of 10.3 ng could be realized. We expect the present colorimetric reagent design strategy would pave a way for one-step instantaneous visual detection toward trace multianalytes.