Toward breath analysis on a chip for disease diagnosis using semiconductor-based chemiresistors: recent progress and future perspectives

Leather-Based Shoe Soles for Real-Time Gait Recognition and Automatic Remote Assistance Using Machine Learning

Real-time monitoring of gait characteristics is crucial for applications in health monitoring, patient rehabilitation feedback, and telemedicine. However, the effective and stable acquisition and automatic analysis of gait information remain significant challenges. In this study, we present a flexible sensor based on a carbon nanotube/graphene composite conductive leather (CGL), which uses collagen fiber with a three-dimensional network structure as the flexible substrate. The CGL-based sensor demonstrates a high dynamic range, with notable pressure responses ranging from 0.6 to 14.5 kPa and high sensitivity (S = 0.2465 kPa-1). We further developed a device incorporating the CGL-based sensor to collect foot characteristic signals from human motion and designed smart sports shoes to facilitate effective human-computer interaction. Machine learning was employed to collect and process gait characteristic information in various states, including standing, sitting, walking, and falling. For real-time monitoring of falls, we optimized the K-Nearest Time Series Classifier (KNTC) algorithm, achieving an accuracy of 0.99 and a prediction time of only 13 ms, which highlights the system's excellent intelligent response capabilities. The system maintained a gait recognition accuracy of 90% across diverse populations, with low false-positive (3.3%) and false-negative (3.3%) rates. This work demonstrates stable gait recognition capabilities and provides valuable methods and insights for plantar behavior monitoring and data analysis, contributing to the development of advanced real-time gait monitoring systems.

A Facile Way to Simultaneously Improve Humidity-Immunity and Gas Response in Semiconductor Metal Oxide Sensors

The metal-oxide-based gas sensors show great potential in exhaled breath analysis owing to their simple, fast, and noninvasive characteristics. However, the exhaled breath contains moisture, and the surface-active sites of metal oxides are easily poisoned by water molecules, leading to degradation of the sensor performance, particularly the gas response and selectivity. Therefore, it is essential to develop oxide sensors that can reliably sense target gases over a wide humidity range without sacrificing the gas response. In this study, a facile strategy was proposed to incorporate hydrophobic La into an oxide sensor to simultaneously improve the humidity-stability and sensitivity of NH3 detection for early prediction of kidney failure. WO3 sensors doped with various concentrations of La were successfully synthesized, and their gas-sensing performances under various humid conditions were systematically investigated. Interestingly, a small amount of La doping (1 at. %) effectively prevented water poisoning and improved the gas response simultaneously. This sensor was able to selectively detect NH3 up to 200 ppb with a limit of detection (LOD) of ∼780 ppt over a wide range of humidity. The concurrent enhancement in gas response and humidity-immunity was attributed to the surface hydrophobicity and increased specific surface area caused by the incorporation of La.

Multipressure Sampling for Improving the Performance of MOF-based Electronic Noses

Metal-organic frameworks (MOFs) are a promising class of porous materials for the design of gas sensing arrays, which are often called electronic noses. Due to their chemical and structural tunability, MOFs are a highly diverse class of materials that align well with the similarly diverse class of volatile organic compounds (VOCs) of interest in many gas detection applications. In principle, by choosing the right combination of cross-sensitive MOFs, layered on appropriate signal transducers, one can design an array that yields detailed information about the composition of a complex gas mixture. However, despite the vast number of MOFs from which one can choose, gas sensing arrays that rely too heavily on distinct chemistries can be impractical from the cost and complexity perspective. On the other hand, it is difficult for small arrays to have the desired selectivity and sensitivity for challenging sensing applications, such as detecting weakly adsorbing gases with weak signals, or conversely, strongly adsorbing gases that readily saturate MOF pores. In this work, we employed gas adsorption simulations to explore the use of a variable pressure sensing array as a means of improving both sensitivity and selectivity as well as increasing the information content provided by each array. We studied nine different MOFs (HKUST-1, IRMOF-1, MgMOF-74, MOF-177, MOF-801, NU-100, NU-125, UiO-66, and ZIF-8) and four different gas mixtures, each containing nitrogen, oxygen, carbon dioxide, and exactly one of the hydrogen, methane, hydrogen sulfide, or benzene. We found that by lowering the pressure, we can limit the saturation of MOFs, and by raising the pressure, we can concentrate weakly adsorbing gases, in both cases, improving gas detection with the resulting arrays. In many cases, changing the system pressure yielded a better improvement in performance (as measured by the Kullback-Liebler divergence of gas composition probability distributions) than including additional MOFs. We thus demonstrated and quantified how sensing at multiple pressures can increase information content and cross-sensitivity in MOF-based arrays while limiting the number of unique materials needed in the device.

Graphene-based chemiresistive gas sensors

Gas sensors allow the monitoring of the chemical environment of humans, which is often crucial for their wellbeing or even survival. Miniaturization, reversibility, and selectivity are some of the key challenges for serial use of chemical sensors. This tutorial review describes critical aspects when using nanomaterials as sensing substrates for the application in chemiresistive gas sensors. Graphene has been shown to be a promising candidate, as it allows gas sensors to be operated at room temperature, possibly saving large amounts of energy. In this review, an overview is given on the general mechanisms for gas-sensitive semiconducting materials and the implications of doping and functionalization on the sensing parameters of chemiresistive devices. It shows in detail how different challenges, like sensitivity, response time, reversibility and selectivity have been approached by material development and operation modes. In addition, perspectives from the area of data analysis and intelligent algorithms are presented, which can further enhance these sensors' usability in the field.

Research progress of electronic nose technology in exhaled breath disease analysis

Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages, such as convenience, safety, simplicity, and avoidance of discomfort. Based on many studies, exhaled breath analysis is a promising medical detection technology capable of diagnosing different diseases by analyzing the concentration, type and other characteristics of specific gases. In the existing gas analysis technology, the electronic nose (eNose) analysis method has great advantages of high sensitivity, rapid response, real-time monitoring, ease of use and portability. Herein, this review is intended to provide an overview of the application of human exhaled breath components in disease diagnosis, existing breath testing technologies and the development and research status of electronic nose technology. In the electronic nose technology section, the three aspects of sensors, algorithms and existing systems are summarized in detail. Moreover, the related challenges and limitations involved in the abovementioned technologies are also discussed. Finally, the conclusion and perspective of eNose technology are presented.

MOF-Based Chemiresistive Gas Sensors: Toward New Functionalities

The sensing performances of gas sensors must be improved and diversified to enhance quality of life by ensuring health, safety, and convenience. Metal-organic frameworks (MOFs), which exhibit an extremely high surface area, abundant porosity, and unique surface chemistry, provide a promising framework for facilitating gas-sensor innovations. Enhanced understanding of conduction mechanisms of MOFs has facilitated their use as gas-sensing materials, and various types of MOFs have been developed by examining the compositional and morphological dependences and implementing catalyst incorporation and light activation. Owing to their inherent separation and absorption properties and catalytic activity, MOFs are applied as molecular sieves, absorptive filtering layers, and heterogeneous catalysts. In addition, oxide- or carbon-based sensing materials with complex structures or catalytic composites can be derived by the appropriate post-treatment of MOFs. This review discusses the effective techniques to design optimal MOFs, in terms of computational screening and synthesis methods. Moreover, the mechanisms through which the distinctive functionalities of MOFs as sensing materials, heterostructures, and derivatives can be incorporated in gas-sensor applications are presented.

Handheld device quantifies breath acetone for real-life metabolic health monitoring

Non-invasive breath analysis with mobile health devices bears tremendous potential to guide therapeutic treatment and personalize lifestyle changes. Of particular interest is the breath volatile acetone, a biomarker for fat burning, that could help in understanding and treating metabolic diseases. Here, we report a hand-held (6 × 10 × 19.5 cm³), light-weight (490 g), and simple device for rapid acetone detection in breath. It comprises a tailor-made end-tidal breath sampling unit, connected to a sensor and a pump for on-demand breath sampling, all operated using a Raspberry Pi microcontroller connected with a HDMI touchscreen. Accurate acetone detection is enabled by introducing a catalytic filter and a separation column, which remove and separate undesired interferents from acetone upstream of the sensor. This way, acetone is detected selectively even in complex gas mixtures containing highly concentrated interferents. This device accurately tracks breath acetone concentrations in the exhaled breath of five volunteers during a ketogenic diet, being as high as 26.3 ppm. Most importantly, it can differentiate small acetone changes during a baseline visit as well as before and after an exercise stimulus, being as low as 0.5 ppm. It is stable for at least four months (122 days), and features excellent bias and precision of 0.03 and 0.6 ppm at concentrations below 5 ppm, as validated by proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). Hence, this detector is highly promising for simple-in-use, non-invasive, and routine monitoring of acetone to guide therapeutic treatment and track lifestyle changes.

Synthesis and Sensing Performance of Chitin Fiber/MoS2 Composites

In this study, chitin fibers (CFs) were combined with molybdenum sulfide (MoS₂) to develop high-performance sensors, and chitin carbon materials were innovatively introduced into the application of gas sensing. MoS₂/CFs composites were synthesized via a one-step hydrothermal method. The surface properties of the composites were greatly improved, and the fire resistance effect was remarkable compared with that of the chitin monomer. In the gas-sensitive performance test, the overall performance of the MoS₂/CFs composite was more than three times better than that of the MoS₂ monomer and showed excellent long-term stability, with less than 10% performance degradation in three months. Extending to the field of strain sensing, MoS₂/CFs composites can realize real-time signal conversion in tensile and motion performance tests, which can help inspectors make analytical judgments in response to the analysis results. The extensive application of sensing materials in more fields is expected to be further developed. Based on the recycling of waste chitin textile materials, this paper expands the potential applications of chitin materials in the fields of gas monitoring, biomedicine, behavioral discrimination and intelligent monitoring.

Advances in Noble Metal-Decorated Metal Oxide Nanomaterials for Chemiresistive Gas Sensors: Overview

Highly sensitive gas sensors with remarkably low detection limits are attractive for diverse practical application fields including real-time environmental monitoring, exhaled breath diagnosis, and food freshness analysis. Among various chemiresistive sensing materials, noble metal-decorated semiconducting metal oxides (SMOs) have currently aroused extensive attention by virtue of the unique electronic and catalytic properties of noble metals. This review highlights the research progress on the designs and applications of different noble metal-decorated SMOs with diverse nanostructures (e.g., nanoparticles, nanowires, nanorods, nanosheets, nanoflowers, and microspheres) for high-performance gas sensors with higher response, faster response/recovery speed, lower operating temperature, and ultra-low detection limits. The key topics include Pt, Pd, Au, other noble metals (e.g., Ag, Ru, and Rh.), and bimetals-decorated SMOs containing ZnO, SnO2, WO3, other SMOs (e.g., In2O3, Fe2O3, and CuO), and heterostructured SMOs. In addition to conventional devices, the innovative applications like photo-assisted room temperature gas sensors and mechanically flexible smart wearable devices are also discussed. Moreover, the relevant mechanisms for the sensing performance improvement caused by noble metal decoration, including the electronic sensitization effect and the chemical sensitization effect, have also been summarized in detail. Finally, major challenges and future perspectives towards noble metal-decorated SMOs-based chemiresistive gas sensors are proposed.

Highly Sensitive and Selective Real-Time Breath Isoprene Detection using the Gas Reforming Reaction of MOF-Derived Nanoreactors

Real-time breath isoprene sensing provides noninvasive methods for monitoring human metabolism and early diagnosis of cardiovascular diseases. Nonetheless, the stable alkene structure and high humidity of the breath hinder sensitive and selective isoprene detection. In this work, we derived well-defined Co₃O₄@polyoxometalate yolk-shell structures using a metal-organic framework template. The inner space, including highly catalytic Co₃O₄ yolks surrounded by a semipermeable polyoxometalate shell, enables stable isoprene to be reformed to reactive intermediate species by increasing the gas residence time and the reaction with the inner catalyst. This sensor exhibited selective isoprene detection with an extremely high chemiresistive response (180.6) and low detection limit (0.58 ppb). The high sensing performance can be attributed to electronic sensitization and catalytic promotion effects. In addition, the reforming reaction of isoprene is further confirmed by the proton transfer reaction-quadrupole mass spectrometry analysis. The practical feasibility of this sensor in smart healthcare applications is exhibited by monitoring muscle activity during the workout.

A Dual Sensing Platform for Human Exhaled Breath Enabled by Fe-MIL-101-NH2 Metal-Organic Frameworks and its Derived Co/Ni/Fe Trimetallic Oxides

Limited by the insufficient active sites and the interference from breath humidity, designing reliable gas sensing materials with high activity and moisture resistance remains a challenge to analyze human exhaled breath for the translational application of medical diagnostics. Herein, the dual sensing and cooperative diagnosis is achieved by utilizing metal-organic frameworks (MOFs) and its derivative. The Fe-MIL-101-NH₂ serves as the quartz crystal microbalance humidity sensing layer, which exhibits high selectivity and rapid response time (16 s/15 s) to water vapor. Then, the Co²⁺ and Ni²⁺ cations are further co-doped into Fe-MIL-101-NH₂ host to obtain the derived Co/Ni/Fe trimetallic  oxides (CoNiFe-MOS-n). The chemiresistive CoNiFe-MOS-n sensor displays the high sensitivity (560) and good selectivity to acetone, together with a lower original resistance compared with Fe₂ O₃ and NiFe₂ O₄ . Moreover, as a proof-of-concept application, synergistic integration of Fe-MIL-101-NH₂ and derived CoNiFe-MOS-n is carried out. The Fe-MIL-101-NH₂ is applied as moisture sorbent materials, which realize a sensitivity compensation of CoNiFe-MOS-n sensors for the detection of acetone (biomarker gas of diabetes). The findings provide an insight for effective utilization of MOFs and the derived materials to achieve a trace gas detection in exhaled breath analysis.

Development and validation of a screening model for lung cancer using machine learning: A large-scale, multi-center study of biomarkers in breath

Objectives

Lung cancer (LC) is the largest single cause of death from cancer worldwide, and the lack of effective screening methods for early detection currently results in unsatisfactory curative treatments. We herein aimed to use breath analysis, a noninvasive and very simple method, to identify and validate biomarkers in breath for the screening of lung cancer.

Materials and methods

We enrolled a total of 2308 participants from two centers for online breath analyses using proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS). The derivation cohort included 1007 patients with primary LC and 1036 healthy controls, and the external validation cohort included 158 LC patients and 107 healthy controls. We used eXtreme Gradient Boosting (XGBoost) to create a panel of predictive features and derived a prediction model to identify LC. The optimal number of features was determined by the greatest area under the receiver‐operating characteristic (ROC) curve (AUC).

Results

Six features were defined as a breath-biomarkers panel for the detection of LC. In the training dataset, the model had an AUC of 0.963 (95% CI, 0.941–0.982), and a sensitivity of 87.1% and specificity of 93.5% at a positivity threshold of 0.5. Our model was tested on the independent validation dataset and achieved an AUC of 0.771 (0.718–0.823), and sensitivity of 67.7% and specificity of 73.0%.

Conclusion

Our results suggested that breath analysis may serve as a valid method in screening lung cancer in a borderline population prior to hospital visits. Although our breath-biomarker panel is noninvasive, quick, and simple to use, it will require further calibration and validation in a prospective study within a primary care setting.

Recent Advances in Nanomechanical Membrane-Type Surface Stress Sensors towards Artificial Olfaction

Nanomechanical sensors have gained significant attention as powerful tools for detecting, distinguishing, and identifying target analytes, especially odors that are composed of a complex mixture of gaseous molecules. Nanomechanical sensors and their arrays are a promising platform for artificial olfaction in combination with data processing technologies, including machine learning techniques. This paper reviews the background of nanomechanical sensors, especially conventional cantilever-type sensors. Then, we focus on one of the optimized structures for static mode operation, a nanomechanical Membrane-type Surface stress Sensor (MSS), and discuss recent advances in MSS and their applications towards artificial olfaction.

Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers

Cancer is usually not symptomatic in its early stages. However, early detection can vastly improve prognosis. Liquid biopsy holds great promise for early detection, although it still suffers from many disadvantages, mainly searching for specific cancer biomarkers. Here, a new approach for liquid biopsies is proposed, based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray based on a varied set of chemi-sensitive nano-based structured films is developed and used to detect and stage cancer. As a proof-of-concept, three cancer models are tested showing high incidence and mortality rates in the population: breast cancer, ovarian cancer, and pancreatic cancer. The nanoarray has >84% accuracy, >81% sensitivity, and >80% specificity for early detection and >97% accuracy, 100% sensitivity, and >88% specificity for metastasis detection. Complementary mass spectrometry analysis validates these results. The ability to analyze such a complex biological fluid as blood, while considering data of many VOCs at a time using the artificially intelligent nanoarray, increases the sensitivity of predictive models and leads to a potential efficient early diagnosis and disease-monitoring tool for cancer.

Improving the air quality with Functionalized Carbon Nanotubes: Sensing and remediation applications in the real world

With the world developing exponentially every day, the collateral damage to air is incessant. There are many methods to purify the air but using carbon nanotubes (CNTs) as adsorbents remains one of the most efficient and reliable methods, due to their high maximum adsorption capacity which renders them extremely useful for removing pollutants from the air. The different types of CNTs, their synthesis, functionalization, purification, functioning, and advantages over conventional filters are deliberated along with diverse types of CNTs like single-walled (SWCNTs), multiwalled (MWCNTs), and others, which can be functionalized and deployed for the removal of harmful gases like oxides of nitrogen and sulphur, and ozone, and volatile organic compounds (VOCs), among others. A comprehensive description of CNTs is provided in this overview with illustrative examples from the past five years. The fabrication methods and target gases of many CNTs-based gas sensors are highlighted, in addition to the comparison of their properties, mainly sensitivity. The effect of functionalization on sensors has been discussed in detail for various composites targeting specific gases, including the future outlook of functionalized CNTs in assorted practical applications.

Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose

Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast, and low-cost method, has been continuously used for detecting human diseases, including the coronavirus disease 2019 (COVID-19). Nevertheless, having big data with several available features is not always beneficial because only a few of them will be relevant and useful to distinguish different breath samples (i.e., positive and negative COVID-19 samples). In this study, we develop a hybrid machine learning-based algorithm combining hierarchical agglomerative clustering analysis and permutation feature importance method to improve the data analysis of a portable e-nose for COVID-19 detection (GeNose C19). Utilizing this learning approach, we can obtain an effective and optimum feature combination, enabling the reduction by half of the number of employed sensors without downgrading the classification model performance. Based on the cross-validation test results on the training data, the hybrid algorithm can result in accuracy, sensitivity, and specificity values of (86 ± 3)%, (88 ± 6)%, and (84 ± 6)%, respectively. Meanwhile, for the testing data, a value of 87% is obtained for all the three metrics. These results exhibit the feasibility of using this hybrid filter-wrapper feature-selection method to pave the way for optimizing the GeNose C19 performance.

State of the Art of Chemosensors in a Biomedical Context

Healthcare is undergoing large transformations, and it is imperative to leverage new technologies to support the advent of personalized medicine and disease prevention. It is now well accepted that the levels of certain biological molecules found in blood and other bodily fluids, as well as in exhaled breath, are an indication of the onset of many human diseases and reflect the health status of the person. Blood, urine, sweat, or saliva biomarkers can therefore serve in early diagnosis of diseases such as cancer, but also in monitoring disease progression, detecting metabolic disfunctions, and predicting response to a given therapy. For most point-of-care sensors, the requirement that patients themselves can use and apply them is crucial not only regarding the diagnostic part, but also at the sample collection level. This has stimulated the development of such diagnostic approaches for the non-invasive analysis of disease-relevant analytes. Considering these timely efforts, this review article focuses on novel, sensitive, and selective sensing systems for the detection of different endogenous target biomarkers in bodily fluids as well as in exhaled breath, which are associated with human diseases.

Emerging roles of cystathionine β-synthase in various forms of cancer

The expression of the reverse transsulfuration enzyme cystathionine-β-synthase (CBS) is markedly increased in many forms of cancer, including colorectal, ovarian, lung, breast and kidney, while in other cancers (liver cancer and glioma) it becomes downregulated. According to the clinical database data in high-CBS-expressor cancers (e.g. colon or ovarian cancer), high CBS expression typically predicts lower survival, while in the low-CBS-expressor cancers (e.g. liver cancer), low CBS expression is associated with lower survival. In the high-CBS expressing tumor cells, CBS, and its product hydrogen sulfide (H₂S) serves as a bioenergetic, proliferative, cytoprotective and stemness factor; it also supports angiogenesis and epithelial-to-mesenchymal transition in the cancer microenvironment. The current article reviews the various tumor-cell-supporting roles of the CBS/H₂S axis in high-CBS expressor cancers and overviews the anticancer effects of CBS silencing and pharmacological CBS inhibition in various cancer models in vitro and in vivo; it also outlines potential approaches for biomarker identification, to support future targeted cancer therapies based on pharmacological CBS inhibition.

Stabilization and Specification in Polymer Field-Effect Transistor Semiconductors

The strong and varied chemical interactions between polymer semiconductors and small molecules, and the electronic consequences of these interactions, make polymer organic field-effect transistors (OFETs) attractive as vapor sensing elements. Two hindrances to their wider acceptance and use are their environmental drift and the poor specificity of individual OFETs. Approaches to addressing these two present drawbacks are presented in this Spotlight on Applications. They include the use of semiconducting polymers with greater inherent stability, circuits that add further stability, and arrays that generate patterns that are much more specific to analyte vapors of interest than the individual responses.

Simultaneous Biomechanical and Biochemical Monitoring for Self-Powered Breath Analysis

The high moisture level of exhaled gases unavoidably limits the sensitivity of breath analysis via wearable bioelectronics. Inspired by pulmonary lobe expansion/contraction observed during respiration, a respiration-driven triboelectric sensor (RTS) was devised for simultaneous respiratory biomechanical monitoring and exhaled acetone concentration analysis. A tin oxide-doped polyethyleneimine membrane was devised to play a dual role as both a triboelectric layer and an acetone sensing material. The prepared RTS exhibited excellent ability in measuring respiratory flow rate (2-8 L/min) and breath frequency (0.33-0.8 Hz). Furthermore, the RTS presented good performance in biochemical acetone sensing (2-10 ppm range at high moisture levels), which was validated via finite element analysis. This work has led to the development of a novel real-time active respiratory monitoring system and strengthened triboelectric-chemisorption coupling sensing mechanism.

Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors

Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.

Paving the Way for a Green Transition in the Design of Sensors and Biosensors for the Detection of Volatile Organic Compounds (VOCs)

The efficient and selective detection of volatile organic compounds (VOCs) provides key information for various purposes ranging from the toxicological analysis of indoor/outdoor environments to the diagnosis of diseases or to the investigation of biological processes. In the last decade, different sensors and biosensors providing reliable, rapid, and economic responses in the detection of VOCs have been successfully conceived and applied in numerous practical cases; however, the global necessity of a sustainable development, has driven the design of devices for the detection of VOCs to greener methods. In this review, the most recent and innovative VOC sensors and biosensors with sustainable features are presented. The sensors are grouped into three of the main industrial sectors of daily life, including environmental analysis, highly important for toxicity issues, food packaging tools, especially aimed at avoiding the spoilage of meat and fish, and the diagnosis of diseases, crucial for the early detection of relevant pathological conditions such as cancer and diabetes. The research outcomes presented in the review underly the necessity of preparing sensors with higher efficiency, lower detection limits, improved selectivity, and enhanced sustainable characteristics to fully address the sustainable manufacturing of VOC sensors and biosensors.

Nanomaterials for IoT Sensing Platforms and Point-of-Care Applications in South Korea

Herein, state-of-the-art research advances in South Korea regarding the development of chemical sensing materials and fully integrated Internet of Things (IoT) sensing platforms were comprehensively reviewed for verifying the applicability of such sensing systems in point-of-care testing (POCT). Various organic/inorganic nanomaterials were synthesized and characterized to understand their fundamental chemical sensing mechanisms upon exposure to target analytes. Moreover, the applicability of nanomaterials integrated with IoT-based signal transducers for the real-time and on-site analysis of chemical species was verified. In this review, we focused on the development of noble nanostructures and signal transduction techniques for use in IoT sensing platforms, and based on their applications, such systems were classified into gas sensors, ion sensors, and biosensors. A future perspective for the development of chemical sensors was discussed for application to next-generation POCT systems that facilitate rapid and multiplexed screening of various analytes.

Breath odor-based individual authentication by an artificial olfactory sensor system and machine learning

The potential feasibility of breath odor sensing-based individual authentication was demonstrated by a 16-channel chemiresistive sensor array and machine learning.

Computational Design of MOF-Based Electronic Noses for Dilute Gas Species Detection: Application to Kidney Disease Detection

The diverse chemical composition of exhaled human breath contains a vast amount of information about the health of the body, and yet this is seldom taken advantage of for diagnostic purposes due to the lack of appropriate gas-sensing technologies. In this work, we apply computational methods to design mass-based gas sensor arrays, often called electronic noses, that are optimized for detecting kidney disease from breath, for which ammonia is a known biomarker. We define combined linear adsorption coefficients (CLACs), which are closely related to Henry's law coefficients, for calculating gas adsorption in metal-organic frameworks (MOFs) of gases commonly found in breath (i.e., carbon dioxide, argon, and ammonia). These CLACs were determined computationally using classical atomistic molecular simulation techniques and subsequently used to design and evaluate gas sensor arrays. We also describe a novel numerical algorithm for determining the composition of a breath sample given a set of sensor outputs and a library of CLACs. After identifying an optimal array of five MOFs, we screened a set of 100 simplified computer-generated, water-free breath samples for kidney disease and were able to successfully quantify the amount of ammonia in all samples within the tolerances needed to classify them as either healthy or diseased, demonstrating the promise of such devices for disease detection applications.

Highly Selective and Sensitive Detection of Volatile Sulfur Compounds by Ionically Conductive Metal-Organic Frameworks

High selectivity to specific analyte is essential for chemical sensors but difficult to achieve. For most chemical sensors, although the response to the target analyte can be more significant than interference analytes, they still show obvious responses to the interference analytes. Here, highly selective chemical sensors are developed with negligible responses to other interference vapors. Instead of the widely investigated electronically conductive metal-organic frameworks (EC-MOFs), ionically conductive MOFs (IC-MOFs) are used as the sensing materials, and the unique interaction between the ion charge carrier and the analyte is utilized to achieve high sensing selectivity. Through the modulation of the metal nodes (Cu, Co, Ni, Zn, Mg) and organic ligands (H₂ TCPP, H₂ THPP, H₄ BTEC), sensor arrays based on a set of IC-MOFs are fabricated and achieve highly selective detection toward volatile sulfur compounds (VSCs). H₂ S and CH₃ SH can be selectively detected at concentrations down to 1 ppb and 1 ppm, respectively. The facile preparation and low cost endow the device with disposability. These results suggest new approaches for the development of highly selective chemical sensors.

Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

Assessment of Occlusal Force and Local Gas Release Using Degradable Bacterial Cellulose/Ti3C2Tx MXene Bioaerogel for Oral Healthcare

Dental diseases resulting from movement disorders and volatile gases are very common. The classic method for detecting occlusal force is effective; however, its function is one-time rather than real-time monitoring, and the technology is very time-consuming. Herein, we report a multifunctional, flexible, and degradable bacterial cellulose/Ti₃C₂T_x MXene bioaerogel for the accurate detection of occlusal force and early diagnosis of periodontal diseases. Combining the mechanical properties of MXene and the abundant functional groups of bacterial cellulose, 3D porous bioaerogels exhibit both pressure-sensitive and ammonia (NH₃)-sensitive responses. By integrating these substances into a flexible array, the resulting device can distinguish the intensity, location, and even the time sequence of the occlusion force; moreover, it can provide NH₃ gas and occlusion force response signals. Therefore, this technology is promising for both disease diagnosis and oral health. In addition, the introduction of a renewable biomaterial allows the bioaerogel to degrade completely using a low-concentration hydrogen peroxide solution, making the device environmentally friendly and satisfying the demands for sustainable development.

Selectivity of a ZnO@ZIF-71@PDMS Nanorod Array Gas Sensor Enhanced by Coating a Polymer Selective Separation Membrane

It is important for noninvasive diagnosis of diabetes to develop acetone gas sensors with high selectivity. ZnO@ZIF-71 has been reported as a highly sensitive and selective gas sensor on acetone detection. However, it is difficult to exclude the interference with similar molecular sizes gas in the gas-sensing process, like ethanol. To solve this problem, polydimethylsiloxane (PDMS) was synthesized on the surface of ZnO@ZIF-71 to form a ZnO@ZIF-71@PDMS sensor by vapor deposition. The new sensor shows inert response to ethanol and effective response to acetone simultaneously. The PDMS membrane acts as a molecular sieve, which shows the acetone selectivity performance and can totally eliminate the response to low concentration ethanol at low temperature. Theory calculations and solubility test are also employed to prove the role PDMS plays in this process. It demonstrated that the acetone selectivity performance comes from the hydrogen bond interaction between the ethanol gas molecules and PDMS, which increases difficulty for ethanol gas molecules to penetrate the PDMS membrane. Further, this work provides a new method for enhancing gas-sensing selectivity and promoting for miniaturization of gas sensors.

Highly sensitive and chemically stable NH3 sensors based on an organic acid-sensitized cross-linked hydrogel for exhaled breath analysis

Due to interference by the high moisture content and complicated compositions of human exhaled breath, the trace-level detection of ammonia (NH₃) with desirable selectivity and stability is a large challenge for exhaled breath analysis. Carboxyl-sensitized hydrogels can be activated by moisture to exhibit a significant response and excellent selectivity to NH₃. However, the high activity of carboxyl groups in hydrogels is a double-edged sword, resulting in poor chemical stability during NH₃ detection. Herein, organic acids were embedded into a cross-linked poly(ethylene glycol) diacrylate (PEGDA) hydrogel via thiol-ene photochemistry to form stable hydrogels for NH₃ detection in a humid atmosphere. As a result, under high humidity conditions (80% RH), the optimal sensors exhibited superior selectivity to NH₃ among various interfering gas species, a remarkably high NH₃ response (Z_a/Z_g=6.20) towards 20 ppm NH₃, and an extremely low actual detection limit (50 ppb) at room temperature. Moreover, the sensors exhibited excellent chemical stability due to the moderate equilibrium water content of the hydrogel composites and acid dissociation constant of the acid groups. The moisture-activated NH₃ sensing mechanism was thoroughly investigated by complex impedance spectroscopy (CIS), quartz crystal microbalance (QCM) measurements, Fourier transform infrared (FT-IR) spectroscopy and X-ray photoelectron spectroscopy (XPS). To explore the application prospects of cross-linked hydrogel sensors for detecting NH₃ in exhaled breath, a simulated exhaled breath test was also performed.

Beyond liquid biopsy: Toward non-invasive assays for distanced cancer diagnostics in pandemics

Liquid biopsy technologies have seen a significant improvement in the last decade, offering the possibility of reliable analysis and diagnosis from several biological fluids. The use of these technologies can overcome the limits of standard clinical methods, related to invasiveness and poor patient compliance. Along with this there are now mature examples of lab-on-chips (LOC) which are available and could be an emerging and breakthrough technology for the present and near-future clinical demands that provide sample treatment, reagent addition and analysis in a sample-in/answer-out approach. The possibility of combining non-invasive liquid biopsy and LOC technologies could greatly assist in the current need for minimizing exposure and transmission risks. The recent and ongoing pandemic outbreak of SARS-CoV-2, indeed, has heavily influenced all aspects of life worldwide. Ordinary tasks have been forced to switch from “in presence” to “distanced”, limiting the possibilities for a large number of activities in all fields of life outside of the home. Unfortunately, one of the settings in which physical distancing has assumed noteworthy consequences is the screening, diagnosis and follow-up of diseases.

In this review, we analyse biological fluids that are easily collected without the intervention of specialized personnel and the possibility that they may be used -or not-for innovative diagnostic assays. We consider their advantages and limitations, mainly due to stability and storage and their integration into Point-of-Care diagnostics, demonstrating that technologies in some cases are mature enough to meet current clinical needs.

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.

Fluorination vs. Chlorination: Effect on the Sensor Response of Tetrasubstituted Zinc Phthalocyanine Films to Ammonia

In this work, the effect of fluorine and chlorine substituents in tetrasubstituted zinc phthalocyanines, introduced into the non-peripheral (ZnPcR4-np, R = F, Cl) and peripheral (ZnPcR4-p, R = F, Cl) positions of macrocycle, on their structure and chemiresistive sensor response to low concentration of ammonia is studied. The structure and morphology of the zinc phthalocyanines films (ZnPcR4) were investigated by X-ray diffraction and atomic force microscopy methods. To understand different effects of chlorine and fluorine substituents, the strength and nature of the bonding of ammonia and ZnPcHal4 molecules were studied by quantum chemical simulation. It was shown on the basis of comparative analysis that the sensor response to ammonia was found to increase in the order ZnPcCl4-np < ZnPcF4-np < ZnPcF4-p < ZnPcCl4-p, which is in good agreement with the values of bonding energy between hydrogen atoms of NH3 and halogen substituents in the phthalocyanine rings. ZnPcCl4-p films demonstrate the maximal sensor response to ammonia with the calculated detection limit of 0.01 ppm; however, they are more sensitive to humidity than ZnPcF4-p films. It was shown that both ZnPcF4-p and ZnPcCl4-p and can be used for the selective detection of NH3 in the presence of carbon dioxide, dichloromethane, acetone, toluene, and ethanol.

SERS-based test strips: Principles, designs and applications

Test strips represent a class of point-of-care testing (POCT) tools for analysis of a variety of biomarkers towards diagnostics. Conventional test strips offer benefits of simple operation, visualization, and short detection time, along with the drawbacks of relatively low sensitivity and unavailability of quantitative analysis. Recently, the combination of surface-enhanced Raman scattering (SERS) and test strips have evolved to provide a powerful platform capable of ultrasensitive and multiplex detection of extensive analytes of interest. In this review, we focus on the working principles, design strategies and POCT applications of SERS-based test strips. Initially, both lateral and vertical flow test strips are briefly introduced, followed by presentation of various strategies for reforming SERS-based test strips with better detection performance. Applications of SERS-based test strips in diagnosis of disease biomarkers, nucleic acids and toxins are reviewed, with an emphasis on SERS tag design, sensitivity and analytical applicability. Finally, conclusions are made and perspectives on futuristic research directions are given.

Superior Room-Temperature Ammonia Sensing Using a Hydrothermally Synthesized MoS2/SnO2 Composite

Layered two-dimensional transition metal dichalcogenides, due to their semiconducting nature and large surface-to-volume ratio, have created their own niche in the field of gas sensing. Their large recovery time and accompanied incomplete recovery result in inferior sensing properties. Here, we report a composite-based strategy to overcome these issues. In this study, we report a facile double-step synthesis of a MoS₂/SnO₂ composite and its successful use as a superior room-temperature ammonia sensor. Contrary to the pristine nanosheet-based sensors, the devices made using the composite display superior gas sensing characteristics with faster response. Specifically, at room temperature (30° C), the composite-based sensor exhibited excellent sensitivity (10%) at an ammonia concentration down to 0.4 ppm along with the response and recovery times of 2 and 10 s, respectively. Moreover, the device also exhibited long-term durability, reproducibility, and selectivity toward ammonia against hydrogen sulfide, methanol, ethanol, benzene, acetone, and formaldehyde. Sensor devices made on quartz and alumina substrates with different roughnesses have yielded almost an identical response, except for slight variations in response and recovery transients. Further, to shed light on the underlying adsorption energetics and selectivity, density functional theory simulations were employed. The improved response and enhanced selectivity of the composite were explicitly discussed in terms of adsorption energy. Lowdin charge analysis was performed to understand the charge transfer mechanism between NH₃, H₂S, CH₃OH, HCHO, and the underlying MoS₂/SnO₂ composite surface. The long-term durability of the sensor was evident from the stable response curves even after 2 months. These results indicate that hydrothermally synthesized MoS₂/SnO₂ composite-based gas sensors can be used as a promising sensing material for monitoring ammonia gas in real fields.

A Transparent Nanopatterned Chemiresistor: Visible-Light Plasmonic Sensor for Trace-Level NO2 Detection at Room Temperature

The highly selective detection of trace gases using transparent sensors at room temperature remains challenging. Herein, transparent nanopatterned chemiresistors composed of aligned 1D Au-SnO₂ nanofibers, which can detect toxic NO₂ gas at room temperature under visible light illumination is reported. Ten straight Au-SnO₂ nanofibers are patterned on a glass substrate with transparent electrodes assisted by direct-write, near-field electrospinning, whose extremely low coverage of sensing materials (≈0.3%) lead to the high transparency (≈93%) of the sensor. The sensor exhibits a highly selective, sensitive, and reproducible response to sub-ppm levels of NO₂ , and its detection limit is as low as 6 ppb. The unique room-temperature NO₂ sensing under visible light emanates from the localized surface plasmonic resonance effect of Au nanoparticles, thereby enabling the design of new transparent oxide-based gas sensors without external heaters or light sources. The patterning of nanofibers with extremely low coverage provides a general strategy to design diverse compositions of gas sensors, which can facilitate the development of a wide range of new applications in transparent electronics and smart windows wirelessly connected to the Internet of Things.

Sensing gastric cancer via point-of-care sensor breath analyzer

BACKGROUND

Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening.

METHODS

A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant analysis (LDA) was used as a classifying model of the sensing signals obatined from the examined groups. For the testing step, an additional device was added. The study group included 274 patients: 94 with gastric cancer, 67 who were in the high-risk group, and 113 controls.

RESULTS

The results of the test set showed a clear discrimination between patients with gastric cancer and controls using the 2-device LDA model (area under the curve, 93.8%; sensitivity, 100%; specificity, 87.5%; overall accuracy, 91.1%), and acceptable results were also achieved for patients with high-risk lesions (the corresponding values for dysplasia were 84.9%, 45.2%, 87.5%, and 65.9%, respectively). The test-phase analysis showed lower accuracies, though still clinically useful.

CONCLUSION

Our results demonstrate that a portable breath sensor device could be useful in point-of-care settings. It shows a promise for detection of gastric cancer as well as for other types of disease.

LAY SUMMARY

A portable sensor-based breath analyzer for detection of gastric cancer can be used in point-of-care settings. The results are transferrable between devices via advanced IoT technology. Both the hardware and software of the reported breath analyzer could be easily modified to enable detection and monitirng of other disease states.

Metal Oxide Nanorods-Based Sensor Array for Selective Detection of Biomarker Gases

The breath gas analysis through gas phase chemical analysis draws attention in terms of non-invasive and real time monitoring. The array-type sensors are one of the diagnostic methods with high sensitivity and selectivity towards the target gases. Herein, we presented a 2 × 4 sensor array with a micro-heater and ceramic chip. The device is designed in a small size for portability, including the internal eight-channel sensor array. In₂O₃ NRs and WO₃ NRs manufactured through the E-beam evaporator's glancing angle method were used as sensing materials. Pt, Pd, and Au metal catalysts were decorated for each channel to enhance functionality. The sensor array was measured for the exhaled gas biomarkers CH₃COCH₃, NO₂, and H₂S to confirm the respiratory diagnostic performance. Through this operation, the theoretical detection limit was calculated as 1.48 ppb for CH₃COCH₃, 1.9 ppt for NO₂, and 2.47 ppb for H₂S. This excellent detection performance indicates that our sensor array detected the CH₃COCH₃, NO₂, and H₂S as biomarkers, applying to the breath gas analysis. Our results showed the high potential of the gas sensor array as a non-invasive diagnostic tool that enables real-time monitoring.

Highly selective gas sensing enabled by filters

Portable and inexpensive gas sensors are essential for the next generation of non-invasive medical diagnostics, smart air quality monitoring & control, human search & rescue and food quality assessment to name a few of their immediate applications. Therein, analyte selectivity in complex gas mixtures like breath or indoor air remains the major challenge. Filters are an effective and versatile, though often unrecognized, route to overcome selectivity issues by exploiting additional properties of target analytes (e.g., molecular size and surface affinity) besides reactivity with the sensing material. This review provides a tutorial for the material engineering of sorption, size-selective and catalytic filters. Of specific interest are high surface area sorbents (e.g., activated carbon, silica gels and porous polymers) with tunable properties, microporous materials (e.g., zeolites and metal-organic frameworks) and heterogeneous catalysts, respectively. Emphasis is placed on material design for targeted gas separation, portable device integration and performance. Finally, research frontiers and opportunities for low-cost gas sensing systems in emerging applications are highlighted.

Multifunctional Latex/Polytetrafluoroethylene-Based Triboelectric Nanogenerator for Self-Powered Organ-like MXene/Metal-Organic Framework-Derived CuO Nanohybrid Ammonia Sensor

Self-powered sensors are crucial in the field of wearable devices and the Internet of Things (IoT). In this paper, an organ-like Ti₃C₂T_x MXene/metal-organic framework-derived copper oxide (CuO) gas sensor was powered by a triboelectric nanogenerator (TENG) based on latex and polytetrafluoroethylene for the detection of ammonia (NH₃) at room temperature. The peak-to-peak value of open-circuit voltage and short-circuit current generated by the prepared TENG can reach up to 810 V and 34 μA, respectively. The TENG can support a maximum peak power density of 10.84 W·m^-2 and light at least 480 LEDs. Moreover, a flexible TENG under a single-electrode working mode was demonstrated for human movement stimulation, which exhibits great potential in wearable devices. The self-powered NH₃ sensor driven by TENG has an excellent response (V_g/V_a = 24.8 @ 100 ppm) at room temperature and exhibits a great potential in monitoring pork quality. Ti₃C₂T_x MXene and CuO were characterized by SEM, TEM, EDS, XRD, and XPS to analyze the properties of the materials. The NH₃ sensing performance of the self-powered sensor based on MXene/CuO was greatly improved, and the mechanism of the enhanced sensing properties was systematically discussed.

Gas-propelled biosensors for quantitative analysis

Gas-propelled biosensors display a simple gas-based signal amplification with quantitative detection features based on the target recognition event in combination with gas propulsion. Due to the liquid-gas conversion, the gas not only pushes the ink bar forward in the microchannel, but also serves as the power to propel the micromotors in the liquid. Thus, this continuous motion leads to a shift in distances which is associated with the target amount. Therefore, gas-propelled biosensors provide a visual quantification based on distance or speed signals without the need for expensive instruments. In this review, we focus on current developments in gas-propelled biosensors for quantitative analysis. First, we list the types of gas utilized as actuators in biosensors. Second, we review the representative gas-propelled biosensors, including the propulsion mechanisms and fabrication methods. Moreover, gas-propelled quantification based on distance and speed is summarized. Finally, we cover applications and provide a future perspective of gas-propelled biosensors.

Tailored Graphene Micropatterns by Wafer-Scale Direct Transfer for Flexible Chemical Sensor Platform

2D materials, such as graphene, exhibit great potential as functional materials for numerous novel applications due to their excellent properties. The grafting of conventional micropatterning techniques on new types of electronic devices is required to fully utilize the unique nature of graphene. However, the conventional lithography and polymer-supported transfer methods often induce the contamination and damage of the graphene surface due to polymer residues and harsh wet-transfer conditions. Herein, a novel strategy to obtain micropatterned graphene on polymer substrates using a direct curing process is demonstrated. Employing this method, entirely flexible, transparent, well-defined self-activated graphene sensor arrays, capable of gas discrimination without external heating, are fabricated on 4 in. wafer-scale substrates. Finite element method simulations show the potential of this patterning technique to maximize the performance of the sensor devices when the active channels of the 2D material are suspended and nanoscaled. This study contributes considerably to the development of flexible functional electronic devices based on 2D materials.

Electrospun ZnO/Pd Nanofibers: CO Sensing and Humidity Effect

Variable air humidity affects the characteristics of semiconductor metal oxides, which complicates the reliable and reproducible determination of CO content in ambient air by resistive gas sensors. In this work, we determined the sensor properties of electrospun ZnO and ZnO/Pd nanofibers in the detection of CO in dry and humid air, and investigated the sensing mechanism. The microstructure of the samples, palladium content, and oxidation state, type, and concentration of surface groups were characterized using complementary techniques: X-ray fluorescent spectroscopy, XRD, high-resolution transmission electron microscopy (HRTEM), high angle annular dark field scanning transmission electron microscopy (HAADF-STEM), energy-dispersive X-ray (EDX) mapping, XPS, and FTIR spectroscopy. The sensor properties of ZnO and ZnO/Pd nanofibers were studied at 100-450 °C in the concentration range of 5-15 ppm CO in dry (RH₂₅ = 0%) and humid (RH₂₅ = 60%) air. It was found that under humid conditions, ZnO completely loses its sensitivity to CO, while ZnO/Pd retains a high sensor response. On the basis of in situ diffuse reflectance IR Fourier transform spectroscopy (DRIFTS) results, it was concluded that high sensor response of ZnO/Pd nanofibers in dry and humid air was due to the electronic sensitization effect, which was not influenced by humidity change.

Rational Design of Semiconductor-Based Chemiresistors and their Libraries for Next-Generation Artificial Olfaction

Artificial olfaction based on gas sensor arrays aims to substitute for, support, and surpass human olfaction. Like mammalian olfaction, a larger number of sensors and more signal processing are crucial for strengthening artificial olfaction. Due to rapid progress in computing capabilities and machine-learning algorithms, on-demand high-performance artificial olfaction that can eclipse human olfaction becomes inevitable once diverse and versatile gas sensing materials are provided. Here, rational strategies to design a myriad of different semiconductor-based chemiresistors and to grow gas sensing libraries enough to identify a wide range of odors and gases are reviewed, discussed, and suggested. Key approaches include the use of p-type oxide semiconductors, multinary perovskite and spinel oxides, carbon-based materials, metal chalcogenides, their heterostructures, as well as heterocomposites as distinctive sensing materials, the utilization of bilayer sensor design, the design of robust sensing materials, and the high-throughput screening of sensing materials. In addition, the state-of-the-art and key issues in the implementation of electronic noses are discussed. Finally, a perspective on chemiresistive sensing materials for next-generation artificial olfaction is provided.

Carbon nanotubes: functionalisation and their application in chemical sensors

Carbon nanotubes (CNTs) have been recognised as a promising material in a wide range of applications, from safety to energy-related devices. However, poor solubility in aqueous and organic solvents has hindered the utilisation and applications of carbon nanotubes. As studies progressed, the methodology for CNTs dispersion was established. The current state of research in CNTs either single wall or multiwall/polymer nanocomposites has been reviewed in context with the various types of functionalisation presently employed. Functionalised CNTs have been playing an increasingly central role in the research, development, and application of carbon nanotube-based nanomaterials and systems. The extremely high surface-to-volume ratio, geometry, and hollow structure of nanomaterials are ideal for the adsorption of gas molecules. This offers great potential applications, such as in gas sensor devices working at room temperature. Particularly, the advent of CNTs has fuelled the invention of CNT-based gas sensors which are very sensitive to the surrounding environment. The presence of O2, NH3, NO2 gases and many other chemicals and molecules can either donate or accept electrons, resulting in an alteration of the overall conductivity. Such properties make CNTs ideal for nano-scale gas-sensing materials. Conductive-based devices have already been demonstrated as gas sensors. However, CNTs still have certain limitations for gas sensor application, such as a long recovery time, limited gas detection, and weakness to humidity and other gases. Therefore, the nanocomposites of interest consisting of polymer and CNTs have received a great deal of attention for gas-sensing application due to higher sensitivity over a wide range of gas concentrations at room temperature compared to only using CNTs and the polymer of interest separately.