Ultra-Low-Power Smart Electronic Nose System Based on Three-Dimensional Tin Oxide Nanotube Arrays

Non-Invasive Diagnostic Approaches for Kidney Disease: The Role of Electronic Nose Systems

Kidney diseases are a group of conditions related to the functioning of kidneys, which are in turn unable to properly filter waste and excessive fluids from the blood, resulting in the presence of dangerous levels of electrolytes, fluids, and waste substances in the human body, possibly leading to significant health effects. At the same time, the toxins amassing in the organism can lead to significant changes in breath composition, resulting in halitosis with peculiar features like the popular ammonia breath. Starting from this evidence, scientists have started to work on systems that can detect the presence of kidney diseases using a minimally invasive approach, minimizing the burden to the individuals, albeit providing clinicians with useful information about the disease's presence or its main related features. The electronic nose (e-nose) is one of such tools, and its applications in this specific domain represent the core of the present review, performed on articles published in the last 20 years on humans to stay updated with the latest technological advancements, and conducted under the PRISMA guidelines. This review focuses not only on the chemical and physical principles of detection of such compounds (mainly ammonia), but also on the most popular data processing approaches adopted by the research community (mainly those relying on Machine Learning), to draw exhaustive conclusions about the state of the art and to figure out possible cues for future developments in the field.

Nano-Schottky-junction-engineered Pd/SnO2 nanotube array for ultrasensitive hydrogen sensing at room temperature

Detecting H2 at low concentrations is important due to it being a major safety concern in practical applications. However, semiconductor chemiresistive gas sensors always suffer from high operating temperatures and power consumption, as well as a limited concentration detection range, which restricts their widespread use. Herein, we developed a 3D nanostructured gas sensor employing a Pd-nanocluster-decorated SnO2 nanotube array as the sensing layer. The sensor showed sensitive and selective properties for detecting low concentrations of H2 at room temperature, with a low limit of detection of 1.6 ppb. It also showed good long-term stability, as long as 100 days. Moreover, systematical characterizations were performed in conjunction with density functional theory (DFT) calculations to determine the ability of Pd/SnO2 junctions to improve the gas-sensing properties. The engineering of the nano-Schottky junction allows us to expand the library for designing low-power-consumption H2 sensors for widespread applications.

Perovskite Light-Emitting Diodes with Quantum Wires and Nanorods

Perovskite materials, celebrated for their exceptional optoelectronic properties, have seen extensive application in the field of light-emitting diodes (LEDs), where research is as abundant as the proverbial "carloads of books." In this review, the research of perovskite materials is delved into from a dimensional perspective, with a focus on the exemplary performance of low-dimensional perovskite materials in LEDs. This discussion predominantly revolves around perovskite quantum wires and perovskite nanorods. Perovskite quantum wires are versatile in their growth, compatible with both solution-based and vapor-phase growth, and can be deposited over large areas-even on spherical substrates-to achieve commendable electroluminescence (EL). Perovskite nanorods, on the other hand, boast a suite of superior characteristics, such as polarization properties and tunability of the transition dipole moment, endowing them with the great potential to enhance light extraction efficiency. Furthermore, zero-dimensional (0D) perovskite materials like nanocrystals (NCs) are also the subject of widespread research and application. This review reflects on and synthesizes the unique qualities of the aforementioned materials while exploring their vital roles in the development of high-efficiency perovskite LEDs (PeLEDs).

Ultralow-Power Single-Sensor-Based E-Nose System Powered by Duty Cycling and Deep Learning for Real-Time Gas Identification

This study presents a novel, ultralow-power single-sensor-based electronic nose (e-nose) system for real-time gas identification, distinguishing itself from conventional sensor-array-based e-nose systems, whose power consumption and cost increase with the number of sensors. Our system employs a single metal oxide semiconductor (MOS) sensor built on a suspended 1D nanoheater, driven by duty cycling─characterized by repeated pulsed power inputs. The sensor's ultrafast thermal response, enabled by its small size, effectively decouples the effects of temperature and surface charge exchange on the MOS nanomaterial's conductivity. This provides distinct sensing signals that alternate between responses coupled with and decoupled from the thermally enhanced conductivity, all within a single time domain during duty cycling. The magnitude and ratio of these dual responses vary depending on the gas type and concentration, facilitating the early stage gas identification of five gas types within 30 s via a convolutional neural network (classification accuracy = 93.9%, concentration regression error = 19.8%). Additionally, the duty-cycling mode significantly reduces power consumption by up to 90%, lowering it to 160 μW to heat the sensor to 250 °C. Manufactured using only wafer-level batch microfabrication processes, this innovative e-nose system promises the facile implementation of battery-driven, long-term, and cost-effective IoT monitoring systems.

Electronic Noses: From Gas-Sensitive Components and Practical Applications to Data Processing

Artificial olfaction, also known as an electronic nose, is a gas identification device that replicates the human olfactory organ. This system integrates sensor arrays to detect gases, data acquisition for signal processing, and data analysis for precise identification, enabling it to assess gases both qualitatively and quantitatively in complex settings. This article provides a brief overview of the research progress in electronic nose technology, which is divided into three main elements, focusing on gas-sensitive materials, electronic nose applications, and data analysis methods. Furthermore, the review explores both traditional MOS materials and the newer porous materials like MOFs for gas sensors, summarizing the applications of electronic noses across diverse fields including disease diagnosis, environmental monitoring, food safety, and agricultural production. Additionally, it covers electronic nose pattern recognition and signal drift suppression algorithms. Ultimately, the summary identifies challenges faced by current systems and offers innovative solutions for future advancements. Overall, this endeavor forges a solid foundation and establishes a conceptual framework for ongoing research in the field.

Autonomous Artificial Olfactory Sensor Systems with Homeostasis Recovery via a Seamless Neuromorphic Architecture

Neuromorphic olfactory systems have been actively studied in recent years owing to their considerable potential in electronic noses, robotics, and neuromorphic data processing systems. However, conventional gas sensors typically have the ability to detect hazardous gas levels but lack synaptic functions such as memory and recognition of gas accumulation, which are essential for realizing human-like neuromorphic sensory system. In this study, a seamless architecture for a neuromorphic olfactory system capable of detecting and memorizing the present level and accumulation status of nitrogen dioxide (NO2) during continuous gas exposure, regulating a self-alarm implementation triggered after 147 and 85 s at a continuous gas exposure of 20 and 40 ppm, respectively. Thin-film-transistor type gas sensors utilizing carbon nanotube semiconductors detect NO2 gas molecules through carrier trapping and exhibit long-term retention properties, which are compatible with neuromorphic excitatory applications. Additionally, the neuromorphic inhibitory performance is also characterized via gas desorption with programmable ultraviolet light exposure, demonstrating homeostasis recovery. These results provide a promising strategy for developing a facile artificial olfactory system that demonstrates complicated biological synaptic functions with a seamless and simplified system architecture.

On-Chip Annealing Using Embedded Micro-Heater for Highly Sensitive and Selective Gas Detection

The demand for gas sensing systems that enable fast and precise gas recognition is growing rapidly. However, substantial challenges arise from the complex fabrication process of sensor arrays, time-consuming data transmission to an external processor, and high energy consumption in multi-stage data processing. In this study, a gas sensing system using on-chip annealing for fast and power-efficient gas detection is proposed. By utilizing a micro-heater embedded in the gas sensor, the sensing material of adjacent sensors in the same substrate can be easily varied without further fabrication steps. The response to oxidizing gas is constrained in metal oxide (MOX) sensing material with small grain sizes, as the depletion width of grain cannot extend beyond the grain size during the gas reaction. On the other hand, the response to reducing gases and humidity, which decrease the depletion width, is less affected by grain sizes. A readout circuit integrating a differential amplifier and dual FET-type gas sensors effectively emphasizes the response to oxidizing gases by canceling the response to reducing gases and humidity. The selective on-chip annealing method is applicable to various MOX sensing materials, demonstrating its potential for application in commercial fields due to its simplicity and expandability.

Advancement of metal oxide nanomaterials on agri-food fronts

The application of metal oxide nanomaterials (MOx NMs) in the agrifood industry offers innovative solutions that can facilitate a paradigm shift in a sector that is currently facing challenges in meeting the growing requirements for food production, while safeguarding the environment from the impacts of current agriculture practices. This review comprehensively illustrates recent advancements and applications of MOx for sustainable practices in the food and agricultural industries and environmental preservation. Relevant published data point out that MOx NMs can be tailored for specific properties, enabling advanced design concepts with improved features for various applications in the agrifood industry. Applications include nano-agrochemical formulation, control of food quality through nanosensors, and smart food packaging. Furthermore, recent research suggests MOx's vital role in addressing environmental challenges by removing toxic elements from contaminated soil and water. This mitigates the environmental effects of widespread agrichemical use and creates a more favorable environment for plant growth. The review also discusses potential barriers, particularly regarding MOx toxicity and risk evaluation. Fundamental concerns about possible adverse effects on human health and the environment must be addressed to establish an appropriate regulatory framework for nano metal oxide-based food and agricultural products.

Mesoporous supraparticles with a tailored solid-liquid-gas interface for visual indication of H2 gas and NH3 vapours

Dual-gasochromic supraparticles that undergo rapid eye-readable and gas-specific colour changes upon reaction with hydrogen or ammonia are reported. This functionality is achieved by tailoring the solid-liquid-gas interface within the mesoporous framework of supraparticles via spray-drying.

Highly Sensitive, Low-Energy-Consumption Biomimetic Olfactory Synaptic Transistors Based on the Aggregation of the Semiconductor Films

Artificial olfactory synaptic devices with low energy consumption and low detection limits are important for the further development of neuromorphic computing and intelligent robotics. In this work, an ultralow energy consumption and low detection limit imitation olfactory synaptic device based on organic field-effect transistors (OFETs) was prepared. The aggregation state of poly(diketopyrrolopyrrole-selenophene) (PTDPP) semiconductor films is modulated by adding unfavorable solvents and annealing treatments to obtain excellent charge transfer and gas synaptic properties. The regulated OFET device can execute basic biological synaptic functions, including excitatory postsynaptic currents (EPSCs), paired-pulse facilitation (PPF), and the transition from short-term to long-term plasticity, at an ultralow operating voltage of -0.0005 V. The ultralow energy consumption during the biomimetic simulation is in the range of 8.94-88 fJ per spike. Noteworthily, the gas detection limit of the device is as low as 50 ppb, well below normal human NO2 gas perception limits (100-1000 ppb). Additionally, high-pass filtering, Pavlovian conditioned reflexes, and decoding of "Morse code" were simulated. Finally, a grid-free conformal device with outstanding flexibility and stability was fabricated. In conclusion, the control of semiconductor thin-film aggregation provides effective guidance for preparing low-energy-consumption, highly sensitive olfactory nerve-mimicking devices and promoting the development of wearable electronics.

Emerging trends in metal oxide-based electronic noses for healthcare applications: a review

An electronic nose (E-nose) is a technology fundamentally inspired by the human nose, designed to detect, recognize, and differentiate specific odors or volatile components in complex and chaotic environments. Comprising an array of sensors with meticulously designed nanostructured architectures, E-noses translate the chemical information captured by these sensors into useful metrics using complex pattern recognition algorithms. E-noses can significantly enhance the quality of life by offering preventive point-of-care devices for medical diagnostics through breath analysis, and by monitoring and tracking hazardous and toxic gases in the environment. They are increasingly being used in defense and surveillance, medical diagnostics, agriculture, environmental monitoring, and product validation and authentication. The major challenge in developing a reliable E-nose involves miniaturization and low power consumption. Various sensing materials are employed to address these issues. This review presents the key advancements over the last decade in E-nose technology, specifically focusing on chemiresistive metal oxide sensing materials. It discusses their sensing mechanisms, integration into portable E-noses, and various data analysis techniques. Additionally, we review the primary metal oxide-based E-noses for disease detection through breath analysis. Finally, we address the major challenges and issues in developing and implementing a portable metal oxide-based E-nose.

Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments

Formaldehyde, a known human carcinogen, is a common indoor air pollutant. However, its real-time and selective recognition from interfering gases remains challenging, especially for low-power sensors suffering from noise and baseline drift. We report a fully 3D-printed quantum dot/graphene-based aerogel sensor for highly sensitive and real-time recognition of formaldehyde at room temperature. By optimizing the morphology and doping of printed structures, we achieve a record-high and stable response of 15.23% for 1 part per million formaldehyde and an ultralow detection limit of 8.02 parts per billion consuming only ∼130-microwatt power. On the basis of measured dynamic response snapshots, we also develop intelligent computational algorithms for robust and accurate detection in real time despite simulated substantial noise and baseline drift, hitherto unachievable for room temperature sensors. Our framework in combining materials engineering, structural design, and computational algorithm to capture dynamic response offers unprecedented real-time identification capabilities of formaldehyde and other volatile organic compounds at room temperature.

Temperature-modulated sensing characteristics of ultrafine Au nanoparticle-loaded porous ZnO nanobelts for identification and determination of BTEX

The identification and determination of benzene, toluene, ethylbenzene, and xylene (BTEX) has always been a formidable challenge for chemiresistive metal oxide sensors owing to their structural similarity and low reactivity, as well as the intrinsic cross sensitivity of metal oxides. In this paper, a temperature-modulated sensing strategy is proposed for the identification and determination of BTEX using a high-performance chemiresistive sensor. Ultrafine Au nanoparticle-loaded porous ZnO nanobelts as sensing materials were synthesized through an exchange reaction followed by thermal oxidation, which exhibited high response toward BTEX. Under dynamic modulation of working temperature, the distinguishable characteristic curves were demonstrated for each BTEX compound. By employing the linear discrimination and convolutional neural network analyses, highly effective BTEX identification was achieved among all investigated volatile organic compounds, which is difficult to realize for single chemiresistive sensors at constant working temperatures. Furthermore, quantitative analysis of BTEX concentrations was accomplished by establishing the relationship between concentration and response at specific points on their response curves. This developed strategy is expected to pave a new way for constructing highly sensitive gas sensors for the identification and analysis of hazardous gases, thereby enhancing their applicability in environmental monitoring.

Achieving Molecular-Level Selective Detection of Volatile Organic Compounds through a Strong Coupling Effect of Ultrathin Nanosheets and Au Nanoparticles

The high density of surface active sites, high efficiency of interfacial carrier transport, and molecular diffusion path determine the efficiency of the electrochemical sensors. The ultrathin structures have atomic-level thickness, carrier migration and heat diffusion are limited in the two-dimensional plane, resulting in excellent conductivity and high carrier concentration. A one-step chemical method is applied to synthesize defect-rich Au-SnO2 in an ultrathin nanosheet form (thickness of 2-3 nm). The strong interaction between Au and SnO2 via the Au-O-Sn bonding and the catalytic effect of Au can prolong the service life via decreasing the optimal operating temperature (55 °C) and promote the Au-SnO2 sensor to exclusively detect formaldehyde at the ppb level (300 ppb). The experimental findings along with theoretical study reveal that Au nanoparticles have a different effect on the competitive adsorption and chemical reaction over the surface of the Au-SnO2 with formaldehyde and other interfering VOC gases, such as methanol, ethanol, and acetone. This study provides mechanistic insights into the correlation between operating temperature and the performance of the Au-SnO2 chemiresistive sensor. This work allows the development of highly efficient and stable electrochemical sensors to detect VOC gases at room temperature in the future.

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.

Large-Area Printed Oxide Film Sensors Enabling Ultrasensitive and Dual Electrical/Colorimetric Detection of Hydrogen at Room Temperature

Commercial hydrogen (H2) sensors operate at high temperatures, which increases power consumption and poses a safety risk owing to the flammable nature of H2. Here, a polymer-noble metal-metal oxide film is fabricated using the spin-coating and printing methods to realize a highly sensitive, low-voltage operation, wide-operating-concentration, and near-monoselective H2 sensor at room temperature. The H2 sensors with an optimized thickness of Pd nanoparticles and SnO2 showed an extremely high response of 16,623 with a response time of 6 s and a recovery time of 5 s at room temperature and 2% H2. At the same time, printed flexible sensors demonstrate excellent sensitivity, with a response of 2300 at 2% H2. The excellent sensing performance at room temperature is due to the optimal SnO2 thickness, corresponding to the Debye length and the oxygen and H2 spillover caused by the optimized coverage of the Pd catalyst. Furthermore, multistructures of WO3 and SnO2 films are used to fabricate a new type of dual-signal sensor, which demonstrated simultaneous conductance and transmittance, i.e., color change. This work provides an effective strategy to develop robust, flexible, transparent, and long-lasting H2 sensors through large-area printing processes based on polymer-metal-metal oxide nanostructures.

Deep-learning-based gas identification by time-variant illumination of a single micro-LED-embedded gas sensor

Electronic nose (e-nose) technology for selectively identifying a target gas through chemoresistive sensors has gained much attention for various applications, such as smart factory and personal health monitoring. To overcome the cross-reactivity problem of chemoresistive sensors to various gas species, herein, we propose a novel sensing strategy based on a single micro-LED (μLED)-embedded photoactivated (μLP) gas sensor, utilizing the time-variant illumination for identifying the species and concentrations of various target gases. A fast-changing pseudorandom voltage input is applied to the μLED to generate forced transient sensor responses. A deep neural network is employed to analyze the obtained complex transient signals for gas detection and concentration estimation. The proposed sensor system achieves high classification (~96.99%) and quantification (mean absolute percentage error ~ 31.99%) accuracies for various toxic gases (methanol, ethanol, acetone, and nitrogen dioxide) with a single gas sensor consuming 0.53 mW. The proposed method may significantly improve the efficiency of e-nose technology in terms of cost, space, and power consumption.

Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics

Cancers, chronic diseases and respiratory infections are major causes of mortality and present diagnostic and therapeutic challenges for health care. There is an unmet medical need for non-invasive, easy-to-use biomarkers for the early diagnosis, phenotyping, predicting and monitoring of the therapeutic responses of these disorders. Exhaled breath sampling is an attractive choice that has gained attention in recent years. Exhaled nitric oxide measurement used as a predictive biomarker of the response to anti-eosinophil therapy in severe asthma has paved the way for other exhaled breath biomarkers. Advances in laser and nanosensor technologies and spectrometry together with widespread use of algorithms and artificial intelligence have facilitated research on volatile organic compounds and artificial olfaction systems to develop new exhaled biomarkers. We aim to provide an overview of the recent advances in and challenges of exhaled biomarker measurements with an emphasis on the applicability of their measurement as a non-invasive, point-of-care diagnostic and monitoring tool.

Temperature-Modulated Selective Detection of Part-per-Trillion NO2 Using Platinum Nanocluster Sensitized 3D Metal Oxide Nanotube Arrays

Semiconductor chemiresistive gas sensors play critical roles in a smart and sustainable city where a safe and healthy environment is the foundation. However, the poor limits of detection and selectivity are the two bottleneck issues limiting their broad applications. Herein, a unique sensor design with a 3D tin oxide (SnO₂ ) nanotube array as the sensing layer and platinum (Pt) nanocluster decoration as the catalytic layer, is demonstrated. The Pt/SnO₂ sensor significantly enhances the sensitivity and selectivity of NO₂ detection by strengthening the adsorption energy and lowering the activation energy toward NO₂ . It not only leads to ultrahigh sensitivity to NO₂ with a record limit of detection of 107 parts per trillion, but also enables selective NO₂ sensing while suppressing the responses to interfering gases. Furthermore, a wireless sensor system integrated with sensors, a microcontroller, and a Bluetooth unit is developed for the practical indoor and on-road NO₂ detection applications. The rational design of the sensors and their successful demonstration pave the way for future real-time gas monitoring in smart home and smart city applications.

Heteronanostructural metal oxide-based gas microsensors

The development of high-performance, portable and miniaturized gas sensors has aroused increasing interest in the fields of environmental monitoring, security, medical diagnosis, and agriculture. Among different detection tools, metal oxide semiconductor (MOS)-based chemiresistive gas sensors are the most popular choice in commercial applications and have the advantages of high stability, low cost, and high sensitivity. One of the most important ways to further enhance the sensor performance is to construct MOS-based nanoscale heterojunctions (heteronanostructural MOSs) from MOS nanomaterials. However, the sensing mechanism of heteronanostructural MOS-based sensors is different from that of single MOS-based gas sensors in that it is fairly complex. The performance of the sensors is influenced by various parameters, including the physical and chemical properties of the sensing materials (e.g., grain size, density of defects, and oxygen vacancies of materials), working temperatures, and device structures. This review introduces several concepts in the design of high-performance gas sensors by analyzing the sensing mechanism of heteronanostructural MOS-based sensors. In addition, the influence of the geometric device structure determined by the interconnection between the sensing materials and the working electrodes is discussed. To systematically investigate the sensing behavior of the sensor, the general sensing mechanism of three typical types of geometric device structures based on different heteronanostructural materials are introduced and discussed in this review. This review will provide guidelines for readers studying the sensing mechanism of gas sensors and designing high-performance gas sensors in the future.

Microheater Integrated Nanotube Array Gas Sensor for Parts-Per-Trillion Level Gas Detection and Single Sensor-Based Gas Discrimination

Real-time monitoring of health threatening gases for chemical safety and human health protection requires detection and discrimination of trace gases with proper gas sensors. In many applications, costly, bulky, and power-hungry devices, normally employing optical gas sensors and electrochemical gas sensors, are used for this purpose. Using a single miniature low-power semiconductor gas sensor to achieve this goal is hardly possible, mostly due to its selectivity issue. Herein, we report a dual-mode microheater integrated nanotube array gas sensor (MINA sensor). The MINA sensor can detect hydrogen, acetone, toluene, and formaldehyde with the lowest measured limits of detection (LODs) as 40 parts-per-trillion (ppt) and the theoretical LODs of ∼7 ppt, under the continuous heating (CH) mode, owing to the nanotubular architecture with large sensing area and excellent surface catalytic activity. Intriguingly, unlike the conventional electronic noses that use arrays of gas sensors for gas discrimination, we discovered that when driven by the pulse heating (PH) mode, a single MINA sensor possesses discrimination capability of multiple gases through a transient feature extraction method. These above features of our MINA sensors make them highly attractive for distributed low-power sensor networks and battery-powered mobile sensing systems for chemical/environmental safety and healthcare applications.

Low-Dimensional Nanomaterial Systems Formed by IVA Group Elements Allow Energy Conversion Materials to Flourish

In response to the exhaustion of traditional energy, green and efficient energy conversion has attracted growing attention. The IVA group elements, especially carbon, are widely distributed and stable in the earth’s crust, and have received a lot of attention from scientists. The low-dimensional structures composed of IVA group elements have special energy band structure and electrical properties, which allow them to show more excellent performance in the fields of energy conversion. In recent years, the diversification of synthesis and optimization of properties of IVA group elements low-dimensional nanomaterials (IVA-LD) contributed to the flourishing development of related fields. This paper reviews the properties and synthesis methods of IVA-LD for energy conversion devices, as well as their current applications in major fields such as ion battery, moisture electricity generation, and solar-driven evaporation. Finally, the prospects and challenges faced by the IVA-LD in the field of energy conversion are discussed.

An Integrated Food Freshness Sensor Array System Augmented by a Metal-Organic Framework Mixed-Matrix Membrane and Deep Learning

The static labels presently prevalent on the food market are confronted with challenges due to the assumption that a food product only undergoes a limited range of predefined conditions, which cause elevated safety risks or waste of perishable food products. Hence, integrated systems for measuring food freshness in real time have been developed for improving the reliability, safety, and sustainability of the food supply. However, these systems are limited by poor sensitivity and accuracy. Here, a metal-organic framework mixed-matrix membrane and deep learning technology were combined to tackle these challenges. UiO-66-OH and polyvinyl alcohol were impregnated with six chromogenic indicators to prepare sensor array composites. The sensors underwent color changes after being exposed to ammonia at different pH values. The limit of detection of 80 ppm for trimethylamine was obtained, which was practically acceptable in the food industry. Four state-of-the-art deep convolutional neural networks were applied to recognize the color change, endowing it with high-accuracy freshness estimation. The simulation test for chicken freshness estimation achieved accuracy up to 98.95% by the WISeR-50 algorithm. Moreover, 3D printing was applied to create a mold for possible scale-up production, and a portable food freshness detector platform was conceptually built. This approach has the potential to advance integrated and real-time food freshness estimation.

Designing oxide chemiresistors for detecting volatile aromatic compounds: recent progresses and future perspectives

Oxide chemiresistors have mostly been used to detect reactive gases such as ethanol, acetone, formaldehyde, nitric dioxide, and carbon monoxide. However, the selective and sensitive detection of volatile aromatic compounds such as benzene, toluene, and xylene, which are extremely toxic and harmful, using oxide chemiresistors remains challenging because of the molecular stability of benzene rings containing chemicals. Moreover, the performance of the sensing materials is insufficient to detect trace concentration levels of volatile aromatic compounds, which lead to harmful effects on human beings. Here, the strategies for designing highly selective and sensitive volatile aromatic compound gas sensors using oxide chemiresistors were suggested and reviewed. Key approaches include the use of thermal activation, design of sensing materials with high catalytic activity, the utilization of catalytic microreactors and bilayer structures with catalytic overlayer, and the pretreatment of analyte gases or post analysis of sensing signals. In addition, future perspectives from the viewpoint of designing sensing materials and sensor structures for high-performance and robust volatile aromatic compounds gas sensors are provided. Finally, we discuss possible applications of the sensors and sensor arrays.

Surfactant-like Peptide Self-Assembled into Hybrid Nanostructures for Electronic Nose Applications

An electronic nose (e-nose) utilizes a multisensor array, which relies on the vector contrast of combinatorial responses, to effectively discriminate between volatile organic compounds (VOCs). In recent years, hierarchical structures made of nonbiological materials have been used to achieve the required sensor diversity. With the advent of self-assembling peptides, the ability to tune nanostructuration, surprisingly, has not been exploited for sensor array diversification. In this work, a designer surfactant-like peptide sequence, CG₇-NH₂, is used to fabricate morphologically and physicochemically heterogeneous "biohybrid" surfaces on Au-covered chips. These multistructural sensing surfaces, containing immobilized hierarchical nanostructures surrounded by self-assembled monolayers, are used for the detection and discrimination of VOCs. Through a simple and judicious design process, involving changes in pH and water content of peptide solutions, a five-element biohybrid sensor array coupled with a gas-phase surface plasmon resonance imaging system is shown to achieve sufficient discriminatory capabilities for four VOCs. Moreover, the limit of detection of the multiarray system is bench-marked at <1 and 6 ppbv for hexanoic acid and phenol (esophago-gastric biomarkers), respectively. Finally, the humidity effects are characterized, identifying the dissociation rate constant as a robust descriptor for classification, further exemplifying their efficacy as biomaterials in the field of artificial olfaction.

Impact of Lateral SnO2 Nanofilm Channel Geometry on a 1024 Crossbar Chemical Sensor Array

We propose a rational strategy to fabricate thermally robust, highly integrated molecular and gas sensors utilizing a lateral SnO₂ nanofilm channel geometry on a 1024 crossbar sensor array. The proposed lateral channel geometry substantially suppresses the detrimental effects of parasitic interconnect wire resistances compared with those of a conventional vertical sandwich-type crossbar array because of its excellent resistance controllability. A conductive oxide top-contact electrode on the lateral SnO₂ nanofilm channel enhances the thermal stability at temperatures of up to 500 °C in ambient air. Integrating this lateral SnO₂ nanofilm geometry with analog circuits enables the operation of a 1024 crossbar sensor array without selector devices to avoid sneak currents. The developed 1024 crossbar sensor array system detects the local spatial distribution of the molecular gas concentration. The spatial data of molecular concentrations include molecule-specific data to distinguish various volatile molecules based on their vapor pressures. Thus, this integrated crossbar sensor array system using lateral nanofilm geometry offers a platform for robust, reliable, highly integrated molecular and gas sensors.

Bimetallic Two-Dimensional Metal-Organic Frameworks for the Chemiresistive Detection of Carbon Monoxide

This paper describes the demonstration of a series of heterobimetallic, isoreticular 2D conductive metal-organic frameworks (MOFs) with metallophthalocyanine (MPc, M=Co and Ni) units interconnected by Cu nodes towards low-power chemiresistive sensing of ppm levels of carbon monoxide (CO). Devices achieve a sub-part-per-million (ppm) limit of detection (LOD) of 0.53 ppm toward CO at a low driving voltage of 0.1 V. MPc-based Cu-linked MOFs can continuously detect CO at 50 ppm, the permissible exposure limit required by the Occupational Safety and Health Administration (OSHA), for multiple exposures, and realize CO detection in air and in humid environment. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), density functional theory (DFT) calculations, and comparison experiments suggest the contribution of Cu nodes to CO binding and the essential role of MPc units in tuning and amplifying the sensing response.

Conductive Stimuli-Responsive Coordination Network Linked with Bismuth for Chemiresistive Gas Sensing

This paper describes the design, synthesis, characterization, and performance of a novel semiconductive crystalline coordination network, synthesized using 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) ligands interconnected with bismuth ions, toward chemiresistive gas sensing. Bi(HHTP) exhibits two distinct structures upon hydration and dehydration of the pores within the network, Bi(HHTP)-α and Bi(HHTP)-β, respectively, both with unprecedented network topology (2,3-c and 3,4,4,5-c nodal net stoichiometry, respectively) and unique corrugated coordination geometries of HHTP molecules held together by bismuth ions, as revealed by a crystal structure resolved via microelectron diffraction (MicroED) (1.00 Å resolution). Good electrical conductivity (5.3 × 10^-3 S·cm^-1) promotes the utility of this material in the chemical sensing of gases (NH₃ and NO) and volatile organic compounds (VOCs: acetone, ethanol, methanol, and isopropanol). The chemiresistive sensing of NO and NH₃ using Bi(HHTP) exhibits limits of detection 0.15 and 0.29 parts per million (ppm), respectively, at low driving voltages (0.1-1.0 V) and operation at room temperature. This material is also capable of exhibiting unique and distinct responses to VOCs at ppm concentrations. Spectroscopic assessment via X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopic methods (i.e., attenuated total reflectance-infrared spectroscopy (ATR-IR) and diffuse reflectance infrared Fourier transformed spectroscopy (DRIFTS)), suggests that the sensing mechanisms of Bi(HHTP) to VOCs, NO, and NH₃ comprise a complex combination of steric, electronic, and protic properties of the targeted analytes.

Recent Progress of Nanostructured Sensing Materials from 0D to 3D: Overview of Structure-Property-Application Relationship for Gas Sensors

Along with the progress of nanoscience and nanotechnology, nanomaterials with attractive structural and functional properties have gained more attention than ever before, especially in the field of electronic sensors. In recent years, the gas sensing devices have made great achievement and also created wide application prospects, which leads to a new wave of research for designing advanced sensing materials. There is no doubt that the characteristics are highly governed by the sensitive layers. For this reason, important advances for the outstanding, novel sensing materials with different dimensional structures including 0D, 1D, 2D, and 3D are reported and summarized systematically. The sensing materials cover noble metals, metal oxide semiconductors, carbon nanomaterials, metal dichalcogenides, g-C₃ N₄ , MXenes, and complex composites. Discussion is also extended to the relation between sensing performances and their structure, electronic properties, and surface chemistry. In addition, some gas sensing related applications are also highlighted, including environment monitoring, breath analysis, food quality and safety, and flexible wearable electronics, from current situation and the facing challenges to the future research perspectives.

Gas Sensor Array Using a Hybrid Structure Based on Zeolite and Oxide Semiconductors for Multiple Bio-Gas Detection

Semiconductor-type gas sensors, composed of metal-oxide semiconductors and porous zeolite materials, are attractive devices for bio-gas detection, particularly when used as bio-gas sensors such as electronic nose application. Previous studies have shown such detection can be obtained with a separate gas concentrator and a sensor device using zeolites and oxide semiconductors of WO₃ nanoparticles. By applying the gas concentrator, porous molecular structures alter both the gas sensitivity and the selectivity, and even can be used to define the sensor characteristics. Based on such a gas sensor design, we investigated the properties of an array of three sensors made of a layer of WO₃ nanoparticles coated with zeolites with different interactions between gas molecule adsorption and desorption. The array was tested with four volatile organic compounds, each measured at different concentrations. The results confirm that the features of individual zeolites combined with the hybrid gas sensor behavior, along with the differences among the sensors, are sufficient for enabling the discrimination of volatile compounds when disregarding their concentration.

Few-Layer MoS2 Photodetector Arrays for Ultrasensitive On-Chip Enzymatic Colorimetric Analysis

Enzymatic colorimetric analysis of metabolites provides signatures of energy conversion and biosynthesis associated with disease onsets and progressions. Miniaturized photodetectors based on emerging two-dimensional transition metal dichalcogenides (TMDCs) promise to advance point-of-care diagnosis employing highly sensitive enzymatic colorimetric detection. Reducing diagnosis costs requires a batched multisample assay. The construction of few-layer TMDC photodetector arrays with consistent performance is imperative to realize optical signal detection for a miniature batched multisample enzymatic colorimetric assay. However, few studies have promoted an optical reader with TMDC photodetector arrays for on-chip operation. Here, we constructed 4 × 4 pixel arrays of miniaturized molybdenum disulfide (MoS₂) photodetectors and integrated them with microfluidic enzyme reaction chambers to create an optoelectronic biosensor chip device. The fabricated device allowed us to achieve arrayed on-chip enzymatic colorimetric detection of d-lactate, a blood biomarker signifying the bacterial translocation from the intestine, with a limit of detection that is 1000-fold smaller than the clinical baseline, a 10 min assay time, high selectivity, and reasonably small variability across the entire arrays. The enzyme (Ez)/MoS₂ optoelectronic biosensor unit consistently detected d-lactate in clinically important biofluids, such as saliva, urine, plasma, and serum of swine and humans with a wide detection range (10^-3-10³ μg/mL). Furthermore, the biosensor enabled us to show that high serum d-lactate levels are associated with the symptoms of systemic infection and inflammation. The lensless, optical waveguide-free device architecture should readily facilitate development of a monolithically integrated hand-held module for timely, cost-effective diagnosis of metabolic disorders in near-patient settings.

Wireless Self-Powered High-Performance Integrated Nanostructured-Gas-Sensor Network for Future Smart Homes

The accelerated evolution of communication platforms including Internet of Things (IoT) and the fifth generation (5G) wireless communication network makes it possible to build intelligent gas sensor networks for real-time monitoring chemical safety and personal health. However, this application scenario requires a challenging combination of characteristics of gas sensors including small formfactor, low cost, ultralow power consumption, superior sensitivity, and high intelligence. Herein, self-powered integrated nanostructured-gas-sensor (SINGOR) systems and a wirelessly connected SINGOR network are demonstrated here. The room-temperature operated SINGOR system can be self-driven by indoor light with a Si solar cell, and it features ultrahigh sensitivity to H₂, formaldehyde, toluene, and acetone with the record low limits of detection (LOD) of 10, 2, 1, and 1 ppb, respectively. Each SINGOR consisting of an array of nanostructured sensors has the capability of gas pattern recognition and classification. Furthermore, multiple SINGOR systems are wirelessly connected as a sensor network, which has successfully demonstrated flammable gas leakage detection and alarm function. They can also achieve gas leakage localization with satisfactory precision when deployed in one single room. These successes promote the development of using nanostructured-gas-sensor network for wide range applications including smart home/building and future smart city.

Surface Functionalized Sensors for Humidity-Independent Gas Detection

Semiconducting metal oxides (SMOXs) are used widely for gas sensors. However, the effect of ambient humidity on the baseline and sensitivity of the chemiresistors is still a largely unsolved problem, reducing sensor accuracy and causing complications for sensor calibrations. Presented here is a general strategy to overcome water-sensitivity issues by coating SMOXs with a hydrophobic polymer separated by a metal-organic framework (MOF) layer that preserves the SMOX surface and serves a gas-selective function. Sensor devices using these nanoparticles display near-constant responses even when humidity is varied across a wide range [0-90 % relative humidity (RH)]. Furthermore, the sensor delivers notable performance below 20 % RH whereas other water-resistance strategies typically fail. Selectivity enhancement and humidity-independent sensitivity are concomitantly achieved using this approach. The reported tandem coating strategy is expected to be relevant for a wide range of SMOXs, leading to a new generation of gas sensors with excellent humidity-resistant performance.

Designing hierarchical porosity in tin oxide monoliths and their application as a solid acid catalyst

Hierarchically porous tin oxide monoliths were prepared through a sol–gel accompanied by phase separation for application as a solid acid catalyst.

Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks

Artificial scent screening systems (known as electronic noses, E-noses) have been researched extensively. A portable, automatic, and accurate, real-time E-nose requires both robust cross-reactive sensing and fingerprint pattern recognition. Few E-noses have been commercialized because they suffer from either sensing or pattern-recognition issues. Here, cross-reactive colorimetric barcode combinatorics and deep convolutional neural networks (DCNNs) are combined to form a system for monitoring meat freshness that concurrently provides scent fingerprint and fingerprint recognition. The barcodes-comprising 20 different types of porous nanocomposites of chitosan, dye, and cellulose acetate-form scent fingerprints that are identifiable by DCNN. A fully supervised DCNN trained using 3475 labeled barcode images predicts meat freshness with an overall accuracy of 98.5%. Incorporating DCNN into a smartphone application forms a simple platform for rapid barcode scanning and identification of food freshness in real time. The system is fast, accurate, and non-destructive, enabling consumers and all stakeholders in the food supply chain to monitor food freshness.

Recent Developments in the Field of Explosive Trace Detection

Explosive trace detection (ETD) technologies play a vital role in maintaining national security. ETD remains an active research area with many analytical techniques in operational use. This review details the latest advances in animal olfactory, ion mobility spectrometry (IMS), and Raman and colorimetric detection methods. Developments in optical, biological, electrochemical, mass, and thermal sensors are also covered in addition to the use of nanomaterials technology. Commercially available systems are presented as examples of current detection capabilities and as benchmarks for improvement. Attention is also drawn to recent collaborative projects involving government, academia, and industry to highlight the emergence of multimodal screening approaches and applications. The objective of the review is to provide a comprehensive overview of ETD by highlighting challenges in ETD and providing an understanding of the principles, advantages, and limitations of each technology and relating this to current systems.

Generic Approach to Boost the Sensitivity of Metal Oxide Sensors by Decoupling the Surface Charge Exchange and Resistance Reading Process

As one of the bottleneck parameters for practical applications of metal oxide semiconductor-based gas sensors, sensitivity enhancement has attracted significant attention in the past few decades. In this work, alternative to conventional strategies for designing sensitive surfaces via morphology/defect/heterojunction control (then operating at an optimized isothermal temperature with a maximal response), a facile enhancement approach by decoupling surface charge exchange and resistance reading process (possessing different temperature-dependent behaviors) through pulsed temperature modulation (PTM) is reported. Substantially magnifying electrical responses of a generic metal oxide (e.g., WO₃) micro-electromechanical systems sensor toward diverse analyte molecules are demonstrated. Under the optimal PTM condition, the response toward 10 ppm NO₂ can be boosted from (isothermal) 99.7 to 842.7, and the response toward 100 ppm acetone is increased from (isothermal) 2.7 to 425, which are comparable to or even better than most of the state-of-the-art WO₃-based sensors. In comparison to conventional (isothermal) operation, PTM allows to sequentially manipulate the physisorption/chemisorption of analyte molecules, generation of surface reactive oxygen species, and sensor resistance reading and thus provides additional opportunities in boosting the electrical response of oxide sensors for advanced health and/or environment monitoring in future.

Elevating Chemistry Research with a Modern Electronics Toolkit

With the rapid development of high technology, chemical science is not as it used to be a century ago. Many chemists acquire and utilize skills that are well beyond the traditional definition of chemistry. The digital age has transformed chemistry laboratories. One aspect of this transformation is the progressing implementation of electronics and computer science in chemistry research. In the past decade, numerous chemistry-oriented studies have benefited from the implementation of electronic modules, including microcontroller boards (MCBs), single-board computers (SBCs), professional grade control and data acquisition systems, as well as field-programmable gate arrays (FPGAs). In particular, MCBs and SBCs provide good value for money. The application areas for electronic modules in chemistry research include construction of simple detection systems based on spectrophotometry and spectrofluorometry principles, customizing laboratory devices for automation of common laboratory practices, control of reaction systems (batch- and flow-based), extraction systems, chromatographic and electrophoretic systems, microfluidic systems (classical and nonclassical), custom-built polymerase chain reaction devices, gas-phase analyte detection systems, chemical robots and drones, construction of FPGA-based imaging systems, and the Internet-of-Chemical-Things. The technology is easy to handle, and many chemists have managed to train themselves in its implementation. The only major obstacle in its implementation is probably one's imagination.

Indoor Air Pollution, Related Human Diseases, and Recent Trends in the Control and Improvement of Indoor Air Quality

Indoor air pollution (IAP) is a serious threat to human health, causing millions of deaths each year. A plethora of pollutants can result in IAP; therefore, it is very important to identify their main sources and concentrations and to devise strategies for the control and enhancement of indoor air quality (IAQ). Herein, we provide a critical review and evaluation of the major sources of major pollutant emissions, their health effects, and issues related to IAP-based illnesses, including sick building syndrome (SBS) and building-related illness (BRI). In addition, the strategies and approaches for control and reduction of pollutant concentrations are pointed out, and the recent trends in efforts to resolve and improve IAQ, with their respective advantages and potentials, are summarized. It is predicted that the development of novel materials for sensors, IAQ-monitoring systems, and smart homes is a promising strategy for control and enhancement of IAQ in the future.

Sn13-Oxo Clusters with an Open Hollow Structural Motif and Decorated by Different Functional Ligands

The first open hollow Sn₁₃-oxo cluster family has been successfully prepared and characterized. These Sn₁₃ clusters contain a {Sn₇} moiety that is similar to the basic structure unit of rutile SnO₂. Interestingly, the Sn₁₃ clusters show labile coordination sites on the edge, which could be functionalized by different ligands. With the different decorated types of functionalized ligands, the open hollow Sn₁₃ clusters present different structural details and framework diameters. The presented results provide a new open hollow structural motif of tin-oxo clusters and also a good platform for their ligand functionalization.

Cuprous Oxide Based Chemiresistive Electronic Nose for Discrimination of Volatile Organic Compounds

This paper reports a facile functionalization method on a metal-oxide semiconductor and a cuprous oxide (Cu₂O) based chemiresistive electronic nose for the detection of volatile organic compounds (VOCs). A library of functionalized Cu₂O nanospheres was developed through silanization using chemically diverse organosilanes. An electronic nose was fabricated with unmodified Cu₂O nanospheres and five types of functionalized Cu₂O nanospheres as the sensing elements. The electronic nose showed stable and rapid resistance responses to 25-200 ppm model VOCs, with the operating temperature of 180 °C. Single VOCs and ternary VOC mixtures could be discriminated by the electronic nose, and six types of tea leaves were also proved to be distinguishable as an illustration of the application of the electronic nose. We expected that the silanization could provide a simple approach for material diversification and the electronic nose would have further application in identification and discrimination of complex gas samples.

Hierarchical Nanoheterostructure of Tungsten Disulfide Nanoflowers Doped with Zinc Oxide Hollow Spheres: Benzene Gas Sensing Properties and First-Principles Study

This paper reports an original fabrication of a benzene gas sensor based on tungsten disulfide nanoflowers (WS₂ NFs)/zinc oxide hollow spheres (ZnO HMDs) hierarchical nanoheterostructure. The ZnO/WS₂ hierarchical composite was characterized for the inspection of its nanostructure, elementary composition, and surface morphology. The benzene-sensing properties of the ZnO/WS₂ nanofilm sensor were exactly investigated. The results illustrate that the ZnO/WS₂ sensor exhibits a remarkable sensing performance toward benzene gas, including good sensitivity, rapid detection, outstanding repeatability, and stability. This is attributed to the fact that the ZnO/WS₂ nanoheterostructure can dramatically enhance the benzene sensing performance. Furthermore, density functional theory was employed to construct the benzene gas adsorption model for the ZnO/WS₂ heterostructure, from which the determined parameters in geometry, energy, and charge provided a powerful support for the mechanism explanation. This work suggests that the ZnO/WS₂ nanoheterostructure is competent to detect trace benzene gas at room temperature.

Oxygen-Defective Ultrathin BiVO4 Nanosheets for Enhanced Gas Sensing

BiVO₄ nanomaterials are potentially applicable in gas sensing, but the sensing performance is limited by the less active sites on the BiVO₄ surface. In this work, we propose a strategy to improve the gas-sensing performance of BiVO₄ by forming ultrathin nanosheets and introducing oxygen vacancies, which increase the surface active sites. Two-dimensional (2D) BiVO₄ nanosheets with oxygen vacancies are prepared through a colloidal method with the assistance of nitric acid. Gas sensors based on the oxygen-defective 2D ultrathin BiVO₄ nanosheets exhibit an enhanced sensing response, which is 3.4 times higher than those of the sensors based on oxygen-abundant BiVO₄ nanosheets. The density functional theory calculation is employed to uncover the promoting effects of oxygen vacancies on enhancing the O₂ adsorption capability of BiVO₄ nanosheets. This work is not only expected to build a wide range of 2D metal oxide semiconductors with a high gas-sensing performance but also gives an insight into the mechanism of the enhanced response induced by the oxygen vacancies, which will be a guideline for further designing high-performance sensing materials.

Printable Fabrication of a Fully Integrated and Self-Powered Sensor System on Plastic Substrates

Wearable and portable devices with desirable flexibility, operational safety, and long cruising time, are in urgent demand for applications in wireless communications, multifunctional entertainments, personal healthcare monitoring, etc. Herein, a monolithically integrated self-powered smart sensor system with printed interconnects, printed gas sensor for ethanol and acetone detection, and printable supercapacitors and embedded solar cells as energy sources, is successfully demonstrated in a wearable wristband fashion by utilizing inkjet printing as a proof-of-concept. In such a "wearable wristband", the harvested solar energy can either directly drive the sensor and power up a light-emitting diode as a warning signal, or can be stored in the supercapacitors in a standby mode, and the energy released from supercapacitors can compensate the intermittency of light illumination. To the best of our knowledge, the demonstration of such a self-powered sensor system integrated onto a single piece of flexible substrate in a printable and additive manner has not previously been reported. Particularly, the printable supercapacitors deliver an areal capacitance of 12.9 mF cm^-2 and the printed SnO₂ gas sensor shows remarkable detection sensitivity under room temperature. The printable strategies for device fabrication and system integration developed here show great potency for scalable and facile fabrication of a variety of wearable devices.

Grain-Boundary-Induced Drastic Sensing Performance Enhancement of Polycrystalline-Microwire Printed Gas Sensors

The development of materials with high efficiency and stable signal output in a bent state is important for flexible electronics. Grain boundaries provide lasting inspiration and a promising avenue for designing advanced functionalities using nanomaterials. Combining bulk defects in polycrystalline materials is shown to result in rich new electronic structures, catalytic activities, and mechanical properties for many applications. However, direct evidence that grain boundaries can create new physicochemical properties in flexible electronics is lacking. Here, a combination of bulk electrosensitive measurements, density functional theory calculations, and atomic force microscopy technology with quantitative nanomechanical mapping is used to show that grain boundaries in polycrystalline wires are more active and mechanically stable than single-crystalline wires for real-time detection of chemical analytes. The existence of a grain boundary improves the electronic and mechanical properties, which activate and stabilize materials, and allow new opportunities to design highly sensitive, flexible chemical sensors.