Sniffing Entrapped Humans with Sensor Arrays

Graphene-based nanotechnology in the Internet of Things: a mini review

Graphene, a 2D nanomaterial, has garnered significant attention in recent years due to its exceptional properties, offering immense potential for revolutionizing various technological applications. In the context of the Internet of Things (IoT), which demands seamless connectivity and efficient data processing, graphene's unique attributes have positioned it as a promising candidate to prevail over challenges and optimize IoT systems. This review paper aims to provide a brief sketch of the diverse applications of graphene in IoT, highlighting its contributions to sensors, communication systems, and energy storage devices. Additionally, it discusses potential challenges and prospects for the integration of graphene in the rapidly evolving IoT landscape.

Fully Transient 3D Origami Paper-Based Ammonia Gas Sensor Obtained by Facile MXene Spray Coating

Developing high-performance chemiresistive gas sensors with mechanical compliance for environmental or health-related biomarker monitoring has recently drawn increasing research attention. Among them, two-dimensional MXene materials hold great potential for room-temperature hazardous gas (e.g., NH3) monitoring regardless of the complicated fabrication process, insufficient 2D/3D flexibilities, and poor environmental sustainability. Herein, a Ti3C2Tx MXene/gelatin ink was developed for patterning electrodes through a facile spray coating. Particularly, the patterned Ti3C2Tx-based coating exhibited good adhesion on the paper substrate against repeated peeling-off and excellent mechanical flexibility against 1000 cyclic stretching. The porous morphology of the coating facilitated the NH3 sensing ability. As a result, the 2D kirigami-shaped NH3 sensor exhibited a good response of 7% to 50 ppm of NH3 with detectable concentrations ranging from 5-500 ppm, decent selectivity over interferences, etc., which could be well-maintained even at 50% stretched state. In addition, with the help of mechanically guided compressive buckling, 3D mesostructured MXene origamis could be obtained, holding promise for detecting the coming direction and height distribution of hazardous gas, e.g., the NH3. More importantly, the as-fabricated MXene/gelatin origami paper could be fully degraded in PBS/H2O2/cellulase solution within 19 days, demonstrating its potential as a high-performance, shape morphable, and environmentally friendly wearable gas sensor.

Structure-Function Relationship of Highly Reactive CuOx Clusters on Co3 O4 for Selective Formaldehyde Sensing at Low Temperatures

Designing reactive surface clusters at the nanoscale on metal-oxide supports enables selective molecular interactions in low-temperature catalysis and chemical sensing. Yet, finding effective material combinations and identifying the reactive site remains challenging and an obstacle for rational catalyst/sensor design. Here, the low-temperature oxidation of formaldehyde with CuOx clusters on Co3 O4 nanoparticles is demonstrated yielding an excellent sensor for this critical air pollutant. When fabricated by flame-aerosol technology, such CuOx clusters are finely dispersed, while some Cu ions are incorporated into the Co3 O4 lattice enhancing thermal stability. Importantly, infrared spectroscopy of adsorbed CO, near edge X-ray absorption fine structure spectroscopy and temperature-programmed reduction in H2 identified Cu+ and Cu2+ species in these clusters as active sites. Remarkably, the Cu+ surface concentration correlated with the apparent activation energy of formaldehyde oxidation (Spearman's coefficient ρ = 0.89) and sensor response (0.96), rendering it a performance descriptor. At optimal composition, such sensors detected even the lowest formaldehyde levels of 3 parts-per-billion (ppb) at 75°C, superior to state-of-the-art sensors. Also, selectivity to other aldehydes, ketones, alcohols, and inorganic compounds, robustness to humidity and stable performance over 4 weeks are achieved, rendering such sensors promising as gas detectors in health monitoring, air and food quality control.

Online mass spectrometry of exhaled breath with a modified ambient ion source

Exhaled breath (EB) may contain metabolites that are closely related to human health conditions. Real time analysis of EB is important to study its true composition, however, it has been difficult. A robust ambient ionization mass spectrometry method using a modified direct analysis in real time (DART) ion source was developed for the online analysis of breath volatiles. The modified DART ion source can provide a confined region for direct sampling, rapid transmission and efficient ionization of exhaled breath. With different sampling methods, offline analysis and near real-time evaluation of exhaled breath were also achieved, and their unique molecular features were characterized. High resolution MS data aided the putative metabolite identification in breath samples, resulting in hundreds of volatile organic compounds being identified in the exhalome. The method was sensitive enough to be used for monitoring the breath feature changes after taking different food and over-the-counter medicine. Quantification was performed for pyridine and valeric acid with fasting and after ingesting different food. The developed method is fast, simple, versatile, and potentially useful for evaluating the true state of human exhaled breath.

Machine Learning-Assisted Sensor Based on CsPbBr3@ZnO Nanocrystals for Identifying Methanol in Mixed Environments

Methanol is a respiratory biomarker for pulmonary diseases, including COVID-19, and is a common chemical that may harm people if they are accidentally exposed to it. It is significant to effectively identify methanol in complex environments, yet few sensors can do so. In this work, the strategy of coating perovskites with metal oxides is proposed to synthesize core-shell CsPbBr₃@ZnO nanocrystals. The CsPbBr₃@ZnO sensor displays a response/recovery time of 3.27/3.11 s to 10 ppm methanol at room temperature, with a detection limit of 1 ppm. Using machine learning algorithms, the sensor can effectively identify methanol from an unknown gas mixture with 94% accuracy. Meanwhile, density functional theory is used to reveal the formation process of the core-shell structure and the target gas identification mechanism. The strong adsorption between CsPbBr₃ and the ligand zinc acetylacetonate lays the foundation for the formation of the core-shell structure. The crystal structure, density of states, and band structure were influenced by different gases, which results in different response/recovery behaviors and makes it possible to identify methanol from mixed environments. Furthermore, due to the formation of type II band alignment, the gas response performance of the sensor is further improved under UV light irradiation.

Breath VOC analysis and machine learning approaches for disease screening: a review

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

The development progress of multi-array colourimetric sensors based on the M13 bacteriophage

Techniques for detecting chemicals dispersed at low concentrations in air continue to evolve. These techniques can be applied not only to manage the quality of agricultural products using a post-ripening process but also to establish a safety prevention system by detecting harmful gases and diagnosing diseases. Recently, techniques for rapid response to various chemicals and detection in complex and noisy environments have been developed using M13 bacteriophage-based sensors. In this review, M13 bacteriophage-based multi-array colourimetric sensors for the development of an electronic nose is discussed. The self-templating process was adapted to fabricate a colour band structure consisting of an M13 bacteriophage. To detect diverse target chemicals, the colour band was utilised with wild and genetically engineered M13 bacteriophages to enhance their sensing abilities. Multi-array colourimetric sensors were optimised for application in complex and noisy environments based on simulation and deep learning analysis. The development of a multi-array colourimetric sensor platform based on the M13 bacteriophage is likely to result in significant advances in the detection of various harmful gases and the diagnosis of various diseases based on exhaled gas in the future.

Green syntheses of graphene and its applications in internet of things (IoT)-a status review

Internet of Things (IoT) is a trending technological field that converts any physical object into a communicable smarter one by converging the physical world with the digital world. This innovative technology connects the device to the internet and provides a platform to collect real-time data, cloud storage, and analyze the collected data to trigger smart actions from a remote location via remote notifications, etc. Because of its wide-ranging applications, this technology can be integrated into almost all the industries. Another trending field with tremendous opportunities is Nanotechnology, which provides many benefits in several areas of life, and helps to improve many technological and industrial sectors. So, integration of IoT and Nanotechnology can bring about the very important field of Internet of Nanothings (IoNT), which can re-shape the communication industry. For that, data (collected from trillions of nanosensors, connected to billions of devices) would be the 'ultimate truth', which could be generated from highly efficient nanosensors, fabricated from various novel nanomaterials, one of which is graphene, the so-called 'wonder material' of the 21st century. Therefore, graphene-assisted IoT/IoNT platforms may revolutionize the communication technologies around the globe. In this article, a status review of the smart applications of graphene in the IoT sector is presented. Firstly, various green synthesis of graphene for sustainable development is elucidated, followed by its applications in various nanosensors, detectors, actuators, memory, and nano-communication devices. Also, the future market prospects are discussed to converge various emerging concepts like machine learning, fog/edge computing, artificial intelligence, big data, and blockchain, with the graphene-assisted IoT field to bring about the concept of 'all-round connectivity in every sphere possible'.

The Combination of Two-Dimensional Nanomaterials with Metal Oxide Nanoparticles for Gas Sensors: A Review

Metal oxide nanoparticles have been widely utilized for the fabrication of functional gas sensors to determine various flammable, explosive, toxic, and harmful gases due to their advantages of low cost, fast response, and high sensitivity. However, metal oxide-based gas sensors reveal the shortcomings of high operating temperature, high power requirement, and low selectivity, which limited their rapid development in the fabrication of high-performance gas sensors. The combination of metal oxides with two-dimensional (2D) nanomaterials to construct a heterostructure can hybridize the advantages of each other and overcome their respective shortcomings, thereby improving the sensing performance of the fabricated gas sensors. In this review, we present recent advances in the fabrication of metal oxide-, 2D nanomaterials-, as well as 2D material/metal oxide composite-based gas sensors with highly sensitive and selective functions. To achieve this aim, we firstly introduce the working principles of various gas sensors, and then discuss the factors that could affect the sensitivity of gas sensors. After that, a lot of cases on the fabrication of gas sensors by using metal oxides, 2D materials, and 2D material/metal oxide composites are demonstrated. Finally, we summarize the current development and discuss potential research directions in this promising topic. We believe in this work is helpful for the readers in multidiscipline research fields like materials science, nanotechnology, chemical engineering, environmental science, and other related aspects.

First-principles calculations on the resistance and electronic properties of H2 adsorption on a CoO-SnO2 heterojunction surface

Compared with pure metal oxides, heterojunctions greatly change the response to gas by the synergistic effect of the interface. In this work, density functional theory was used to reveal the adsorption performance of H₂ on the heterojunction under oxygen conditions. First, we determined the most reasonable heterojunction structure based on the adhesion work. According to the adsorption energy, the presence of SnO₂₍100)(I)/CoO(110)(II) made the adsorption of H₂ more stable. The DOS results showed that the resistance of the heterojunction increased with H₂ adsorption, following the same trend as that of CoO(110) with H₂ adsorption, although that of the heterojunction increased more. The electron density and electron density difference indicated that the heterojunction improved the reaction between H₂ and oxygen ions on CoO(110). However, the resistance of CoO(110)(II)/SnO₂(100)(II) increased after H₂ adsorption, contrary to the resistance change of SnO₂(100). Besides, the bonding energy between H₂ and the adsorption site became worse. The above results demonstrated that the presence of the heterojunction could indeed change the response trend and the adsorption behavior of H₂. Interestingly, the adsorption sites and effects of H₂ were different when two metal oxides were used as the substrate of the heterojunction, respectively.

Neural mechanism mimetic selective electronic nose based on programmed M13 bacteriophage

The electronic nose is a reliable practical sensor device that mimics olfactory organs. Although numerous studies have demonstrated excellence in detecting various target substances with the help of ideal models, biomimetic approaches still suffer in practical realization because of the inability to mimic the signal processing performed by olfactory neural systems. Herein, we propose an electronic nose based on the programable surface chemistry of M13 bacteriophage, inspired by the neural mechanism of the mammalian olfactory system. The neural pattern separation (NPS) was devised to apply the pattern separation that operates in the memory and learning process of the brain to the electronic nose. We demonstrate an electronic nose in a portable device form, distinguishing polycyclic aromatic compounds (harmful in living environment) in an atomic-level resolution (97.5% selectivity rate) for the first time. Our results provide practical methodology and inspiration for the second-generation electronic nose development toward the performance of detection dogs (K9).

A Short Review on Various Engineering Applications of Electrospun One-Dimensional Metal Oxides

The growing scientific interest in one-dimensional (1D) nanostructures based on metal-oxide semiconductors (MOS) resulted in the analysis of their structure, properties and fabrication methods being the subject of many research projects and publications all over the world, including in Poland. The application of the method of electrospinning with subsequent calcination for the production of these materials is currently very popular, which results from its simplicity and the possibility to control the properties of the obtained materials. The growing trend of industrial application of electrospun 1D MOS and the progress in modern technologies of nanomaterials properties investigations indicate the necessity to maintain the high level of research and development activities related to the structure and properties analysis of low-dimensional nanomaterials. Therefore, this review perfectly fits both the global trends and is a summary of many years of research work in the field of electrospinning carried out in many research units, especially in the Department of Engineering Materials and Biomaterials of the Faculty of Mechanical Engineering and Technology of Silesian University of Technology, as well as an announcement of further activities in this field.

Transdermal sensing: in-situ non-invasive techniques for monitoring of human biochemical status

Improving life expectancy necessitates prevention and early diagnosis of any disease state based on active self-monitoring of symptoms and longitudinal biochemical profiling. Non-invasive and continuous measurement of molecular biomarkers that reflect metabolism and health must however be established to realize this plan. Human samples non-invasively obtained via the skin are suitable in this context for in-situ biochemical monitoring. We present a brief classification of transdermal sampling in aqueous and gaseous phases and then introduce a new generation of transdermal monitoring devices for rapid and accurate assessment of important parameters. Finally, we have summarized the diversity of body-wide skin characteristics that have possible effects for transdermal sampling. Because of its passive nature, in-situ biochemical monitoring via transdermal sampling will potentially lead to a greater understanding of important biochemical markers and their temporal variation.

Room-Temperature Catalyst Enables Selective Acetone Sensing

Catalytic packed bed filters ahead of gas sensors can drastically improve their selectivity, a key challenge in medical, food and environmental applications. Yet, such filters require high operation temperatures (usually some hundreds °C) impeding their integration into low-power (e.g., battery-driven) devices. Here, we reveal room-temperature catalytic filters that facilitate highly selective acetone sensing, a breath marker for body fat burn monitoring. Varying the Pt content between 0-10 mol% during flame spray pyrolysis resulted in Al2O3 nanoparticles decorated with Pt/PtOx clusters with predominantly 5-6 nm size, as revealed by X-ray diffraction and electron microscopy. Most importantly, Pt contents above 3 mol% removed up to 100 ppm methanol, isoprene and ethanol completely already at 40 °C and high relative humidity, while acetone was mostly preserved, as confirmed by mass spectrometry. When combined with an inexpensive, chemo-resistive sensor of flame-made Si/WO3, acetone was detected with high selectivity (≥225) over these interferants next to H2, CO, form-/acetaldehyde and 2-propanol. Such catalytic filters do not require additional heating anymore, and thus are attractive for integration into mobile health care devices to monitor, for instance, lifestyle changes in gyms, hospitals or at home.

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.

Detecting methanol in hand sanitizers

The coronavirus disease 2019 (COVID-19) pandemic has increased dramatically the demand for hand sanitizers. A major concern is methanol adulteration that caused more than 700 fatalities in Iran and U.S.A. (since February 2020). In response, the U.S. Food and Drug Administration has restricted the methanol content in sanitizers to 0.063 vol% and blacklisted 212 products (as of November 20, 2020). Here, we present a low-cost, handheld, and smartphone-assisted device that detects methanol selectively in sanitizers between 0.01 and 100 vol% within two minutes. It features a nanoporous polymer column that separates methanol selectively from confounders by adsorption. A chemoresistive gas sensor detects the methanol. When tested on commercial sanitizers (total 76 samples), methanol was quantified in excellent (R2 = 0.99) agreement to "gold standard" gas chromatography. Importantly, methanol quantification was hardly interfered by sanitizer composition and viscosity. This device meets an urgent need for on-site methanol screening by authorities, health professionals, and even laymen.

High-Performance Ketone Sensing in Vapor Phase Enabled by o-Carborane-Modified Cyclometalated Alkynyl-Gold(III) Complex-Based Fluorescent Films

Development of high-performance, low-power-consumption, small-sized detectors is a key issue for fabricating specific miniaturized chromatographs (GCs). Herein, we report, for the first-time, utilization of a film-based fluorescent sensor as a GC detector. In the studies, we designed a new o-carborane derivative of a known cyclometalated alkynyl-gold(III) complex, Au-CB. Unlike the parent gold(III) complex, the newly synthesized Au-CB depicted a remarkable aggregation-induced emission (AIE) property, enabling fabrication of a fluorescent film. The film emission is highly sensitive to the presence of ketones such as acetone, 2-pentanone, 3-pentanone, cyclopentanone, etc., in the air. It was demonstrated that the sensing performance of the film could be further improved by changing the film from a planar structure to a tubular one. Via combination with an earlier reported homemade sensory device, a conceptual film-based fluorescent sensor was developed, which demonstrated instant and fully reversible response to the ketones. The experimental detection limits for cyclohexanone and acetone could be lower than 0.08 and 13.0 ppm, respectively. Moreover, the sensor is super stable, as 24 h continuous illumination resulted in less than 1.0% reduction of the fluorescence emission, 50 successive sensings showed no observable decay in the performance, and more than 1 year of storage had no effect upon the property. Further studies demonstrated that the film sensor could be used as a GC detector with performance comparable to the commercial flame ionization detector (FID), which lays the foundation for future applications in specific miniaturized GCs because of its merits in size, power consumption, carrier gas, etc.

Screening Methanol Poisoning with a Portable Breath Detector

Methanol poisoning outbreaks after consumption of adulterated alcohol frequently overwhelm health care facilities in developing countries. Here, we present how a recently developed low-cost and handheld breath detector can serve as a noninvasive and rapid diagnostic tool for methanol poisoning. The detector combines a separation column and a micromachined chemoresistive gas sensor fully integrated into a device that communicates wirelessly with a smartphone. The performance of the detector is validated with methanol-spiked breath of 20 volunteers (105 breath samples) after consumption of alcoholic beverages. Breath methanol concentrations were quantified accurately within 2 min in the full breath-relevant range (10-1000 ppm) in excellent agreement (R² = 0.966) with benchtop mass spectrometry. Bland-Altman analysis revealed sufficient limits of agreement (95% confidence intervals), promising to indicate reliably the clinical need for antidote and hemodialysis treatment. This simple-in-use detector features high diagnostic capability for accurate measurement of methanol in spiked breath, promising for rapid screening of methanol poisoning and assessment of severity. It can be applied readily by first responders to distinguish methanol from ethanol poisoning and monitor in real time the subsequent hospital treatment.

The Ketogenic Diet: Breath Acetone Sensing Technology

The ketogenic diet, while originally thought to treat epilepsy in children, is now used for weight loss due to increasing evidence indicating that fat is burned more rapidly when there is a low carbohydrate intake. This low carbohydrate intake can lead to elevated ketone levels in the blood and breath. Breath and blood ketones can be measured to gauge the level of ketosis and allow for adjustment of the diet to meet the user’s needs. Blood ketone levels have been historically used, but now breath acetone sensors are becoming more common due to less invasiveness and convenience. New technologies are being researched in the area of acetone sensors to capitalize on the rising popularity of the diet. Current breath acetone sensors come in the form of handheld breathalyzer devices. Technologies in development mostly consist of semiconductor metal oxides in different physio-chemical formations. These current devices and future technologies are investigated here with regard to utility and efficacy. Technologies currently in development do not have extensive testing of the selectivity of the sensors including the many compounds present in human breath. While some sensors have undergone human testing, the sample sizes are very small, and the testing was not extensive. Data regarding current devices is lacking and more research needs to be done to effectively evaluate current devices if they are to have a place as medical devices. Future technologies are very promising but are still in early development stages.

Morphological Effects in SnO2 Chemiresistors for Ethanol Detection: A Review in Terms of Central Performances and Outliers

SnO₂ is one of the most studied materials in gas sensing and is often used as a benchmark for other metal oxide-based gas sensors. To optimize its structural and functional features, the fine tuning of the morphology in nanoparticles, nanowires, nanosheets and their eventual hierarchical organization has become an active field of research. In this paper, the different SnO₂ morphologies reported in literature in the last five years are systematically compared in terms of response amplitude through a statistical approach. To have a dataset as homogeneous as possible, which is necessary for a reliable comparison, the analysis is carried out on sensors based on pure SnO₂, focusing on ethanol detection in a dry air background as case study. Concerning the central performances of each morphology, results indicate that none clearly outperform the others, while a few individual materials emerge as remarkable outliers with respect to the whole dataset. The observed central performances and outliers may represent a suitable reference for future research activities in the field.

Stretchable gas sensors for detecting biomarkers from humans and exposed environments

The recent advent of stretchable gas sensors demonstrates their capabilities to detect not only gaseous biomarkers from the human body but also toxic gas species from the exposed environment. To ensure accurate gas detection without device breakdown from the mechanical deformations, the stretchable gas sensors often rely on the direct integration of gas-sensitive nanomaterials on the stretchable substrate or fibrous network, as well as being configured into stretchable structures. The nanomaterials in the forms of nanoparticles, nanowires, or thin-films with nanometer thickness are explored for a variety of sensing materials. The commonly used stretchable structures in the stretchable gas sensors include wrinkled structures from a pre-strain strategy, island-bridge layouts or serpentine interconnects, strain isolation approaches, and their combinations. This review aims to summarize the recent advancement in novel nanomaterials, sensor design innovations, and new fabrication approaches of stretchable gas sensors.

Selective formaldehyde detection at ppb in indoor air with a portable sensor

Formaldehyde is a carcinogenic indoor air pollutant emitted from wood-based furniture, building materials, paints and textiles. Yet, no low-cost sensor exists for on-site monitoring to fulfill stringent current and upcoming (e.g., 8 parts-per-billion by volume, ppb, in France by 2023) exposure guidelines. Here, we present an inexpensive and handheld formaldehyde detector with proven performance in real indoor air. Selectivity is achieved by a compact packed bed column of nanoporous polymer sorbent that separates formaldehyde from interferants present in ambient air. Downstream, a highly sensitive nanoparticle-based chemoresistive Pd-doped SnO₂ sensor detects formaldehyde in the relevant concentration range down to 5 ppb within 2 min. As a proof-of-concept, we measured formaldehyde in indoor air and from different wood product emissions, in excellent agreement (R² > 0.98) with high-resolution proton-transfer-reaction time-of-flight mass spectrometry. This detector is simple-in-use and readily applicable for on-site formaldehyde exposure monitoring at home or work. It is promising for internet-of-things (IOT) sensing networks or even wearables for personal exposure assessment.

Breath acetone change during aerobic exercise is moderated by cardiorespiratory fitness

Exhaled breath acetone (BrAce) was investigated during and after submaximal aerobic exercise as a volatile biomarker for metabolic responsiveness in high and lower-fit individuals in a prospective cohort pilot-study. Twenty healthy adults (19-39 years) with different levels of cardiorespiratory fitness (VO_2peak), determined by spiroergometry, were recruited. BrAce was repeatedly measured by proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) during 40-55 min submaximal cycling exercise and a post-exercise period of 180 min. Activity of ketone and fat metabolism during and after exercise were assessed by indirect calorimetric calculation of fat oxidation rate and by measurement of venous β-hydroxybutyrate (βHB). Maximum BrAce ratios were significantly higher during exercise in the high-fit individuals compared to the lower-fit group (t-test; p= 0.03). Multivariate regression showed 0.4% (95%-CI = -0.2%-0.9%, p= 0.155) higher BrAce change during exercise for every ml kg^-1 min^-1 higher VO_2peak. Differences of BrAce ratios during exercise were similar to fat oxidation rate changes, but without association to respiratory minute volume. Furthermore, the high-fit group showed higher maximum BrAce increase rates (46% h^-1) in the late post-exercise phase compared to the lower-fit group (29% h^-1). As a result, high-fit young, healthy individuals have a higher increase in BrAce concentrations related to submaximal exercise than lower-fit subjects, indicating a stronger exercise-related activation of fat metabolism.

Superior Acetone Selectivity in Gas Mixtures by Catalyst-Filtered Chemoresistive Sensors

Acetone is a toxic air pollutant and a key breath marker for non-invasively monitoring fat metabolism. Its routine detection in realistic gas mixtures (i.e., human breath and indoor air), however, is challenging, as low-cost acetone sensors suffer from insufficient selectivity. Here, a compact detector for acetone sensing is introduced, having unprecedented selectivity (>250) over the most challenging interferants (e.g., alcohols, aldehydes, aromatics, isoprene, ammonia, H2, and CO). That way, acetone is quantified with fast response (<1 min) down to, at least, 50 parts per billion (ppb) in gas mixtures with such interferants having up to two orders of magnitude higher concentration than acetone at realistic relative humidities (RH = 30-90%). The detector consists of a catalytic packed bed (30 mg) of flame-made Al2O3 nanoparticles (120 m2 g-1) decorated with Pt nanoclusters (average size 9 nm) and a highly sensitive chemo-resistive sensor made by flame aerosol deposition and in situ annealing of nanostructured Si-doped ε-WO3 (Si/WO3). Most importantly, the catalytic packed bed converts interferants continuously enabling highly selective acetone sensing even in the exhaled breath of a volunteer. The detector exhibits stable performance over, at least, 145 days at 90% RH, as validated by mass spectrometry.

Thickness Optimization of Highly Porous Flame-Aerosol Deposited WO3 Films for NO2 Sensing at ppb

Nitrogen dioxide (NO2) is a major air pollutant resulting in respiratory problems, from wheezing, coughing, to even asthma. Low-cost sensors based on WO3 nanoparticles are promising due to their distinct selectivity to detect NO2 at the ppb level. Here, we revealed that controlling the thickness of highly porous (97%) WO3 films between 0.5 and 12.3 μm altered the NO2 sensitivity by more than an order of magnitude. Therefore, films of WO3 nanoparticles (20 nm in diameter by N2 adsorption) with mixed γ- and ε-phase were deposited by single-step flame spray pyrolysis without affecting crystal size, phase composition, and film porosity. That way, sensitivity and selectivity effects were associated unambiguously to thickness, which was not possible yet with other sensor fabrication methods. At the optimum thickness (3.1 μm) and 125 °C, NO2 concentrations were detected down to 3 ppb at 50% relative humidity (RH), and outstanding NO2 selectivity to CO, methanol, ethanol, NH3 (all > 105), H2, CH4, acetone (all > 104), formaldehyde (>103), and H2S (835) was achieved. Such thickness-optimized and porous WO3 films have strong potential for integration into low-power devices for distributed NO2 air quality monitoring.

A pocket-sized device enables detection of methanol adulteration in alcoholic beverages

Alcoholic drinks contaminated, either accidentally or deliberately, by methanol claimed at least 789 lives in 2019, mostly in Asia. Here, a palm-sized, multi-use sensor-smartphone system is presented for on-demand headspace analysis of beverages. The analyser quantified methanol concentrations in 89 pure and methanol-contaminated alcoholic drinks from 6 continents and performed accurately for 107 consecutive days. This device could help consumers, distillers, law-enforcing authorities and healthcare workers to easily screen methanol in alcoholic beverages.

Selective Detection of Target Volatile Organic Compounds in Contaminated Air Using Sensor Array with Machine Learning: Aging Notes and Mold Smells in Simulated Automobile Interior Contaminant Gases

We investigated the selective detection of target volatile organic compounds (VOCs) which are age-related body odors (namely, 2-nonenal, pelargonic acid, and diacetyl) and a fungal odor (namely, acetic acid) in the presence of interference VOCs from car interiors (namely, n-decane, and butyl acetate). We used eight semiconductive gas sensors as a sensor array; analyzing their signals using machine learning; principal-component analysis (PCA), and linear-discriminant analysis (LDA) as dimensionality-reduction methods; k-nearest-neighbor (kNN) classification to evaluate the accuracy of target-gas determination; and random forest and ReliefF feature selections to choose appropriate sensors from our sensor array. PCA and LDA scores from the sensor responses to each target gas with contaminant gases were generally within the area of each target gas; hence; discrimination between each target gas was nearly achieved. Random forest and ReliefF efficiently reduced the required number of sensors, and kNN verified the quality of target-gas discrimination by each sensor set.

Catalytic Filter for Continuous and Selective Ethanol Removal Prior to Gas Sensing

Ethanol is a major confounder in gas sensing because of its omnipresence in indoor air and breath from disinfectants or alcoholic beverages. In fact, most modern gas sensors (e.g., graphene, carbon nanotubes, or metal oxides) are sensitive to ethanol. This is challenging because ethanol is often present at higher concentrations than target analytes. Here, a simple and modular packed bed filter is presented that selectively and continuously removes ethanol (and other alcohols like 1-butanol, isopropanol, and methanol) over critical acetone, CH₄, H₂, toluene, and benzene at 30-90% relative humidity. This filter consists of catalytically active ZnO nanoparticles (d_BET = 55 nm) made by flame aerosol technology and annealing. Continuous oxidation of ethanol to CO₂ and H₂ was observed at filter temperatures above 260 °C while below that, unwanted acetaldehyde was formed. Most remarkably, ethanol concentrations up to 185 ppm were removed from exhaled breath in preliminary tests with an alcohol intoxicated volunteer, as confirmed by mass spectrometry. At the same time, almost 4 orders of magnitude lower (e.g., 0.025 ppm) acetone concentrations were preserved. This was superior to previous catalyst filters (e.g., CuO, SnO₂, and Fe₂O₃) with overlapping ethanol and acetone conversions and related to ZnO's surface basicity. The ZnO filter performance was stable (±2.5% conversion variability) for, at least, 21 days. Finally, when combined with a Si-doped WO₃ sensor, the filter effectively mitigated ethanol interference when sensing acetone without compromising the sensor's fast response and recovery times. Such catalytic filters can be combined readily with all gas sensors.

Rapid and Selective NH3 Sensing by Porous CuBr

Fast and selective detection of NH3 at parts-per-billion (ppb) concentrations with inexpensive and low-power sensors represents a long-standing challenge. Here, a room temperature, solid-state sensor is presented consisting of nanostructured porous (78%) CuBr films. These are prepared by flame-aerosol deposition of CuO onto sensor substrates followed by dry reduction and bromination. Each step is monitored in situ through the film resistance affording excellent process control. Such porous CuBr films feature an order of magnitude higher NH3 sensitivity and five times faster response times than conventional denser CuBr films. That way, rapid (within 2.2 min) sensing of even the lowest (e.g., 5 ppb) NH3 concentrations at 90% relative humidity is attained with outstanding selectivity (30-260) over typical confounders including ethanol, acetone, H2, CH4, isoprene, acetic acid, formaldehyde, methanol, and CO, superior to state-of-the-art sensors. This sensor is ideal for hand-held and battery-driven devices or integration into wearable electronics as it does not require heating. From a broader perspective, the process opens exciting new avenues to also explore other bromides and classes of semiconductors (e.g., sulfides, nitrides, carbides) currently not accessible by flame-aerosol technology.

Palladium embedded in SnO2 enhances the sensitivity of flame-made chemoresistive gas sensors

Palladium is used commonly to enhance the performance of chemoresistive metal-oxide gas sensors. Typically, this enhancement is attributed to the presence of Pd clusters on the surface of their metal-oxide support (i.e. SnO₂). Possible Pd incorporation or embedding into the support rarely has been considered. Here, SnO₂ particles (15 - 21 nm in diameter measured by N₂ adsorption) with different Pd contents (0 - 3 mol%) were prepared by flame spray pyrolysis (FSP). Leaching these particles with HNO₃ and characterization by inductively coupled plasma - optical emission spectrometry (ICP-OES) indicated that only 36 - 60% of Pd have been removed (e.g., from the SnO₂ surface). The rest was embedded within the SnO₂ particles. Annealing prior to leaching decreased by ~30% that Pd surface content. Most interestingly, such SnO₂ particles (with only embedded Pd) show higher sensor response to acetone, ethanol and CO at 350 °C compared to SnO₂ particles containing both surface and embedded Pd (i.e. before leaching). As a result, such sensors can detect acetone with high (> 25) signal-to-noise ratio at levels down to 5 ppb at 50% relative humidity. Graphical abstractFlame-made SnO₂ nanoparticles with embedded and surface Pd (triangles) exhibit lower sensor response to acetone, ethanol and CO than SnO₂ from which the surface Pd had been removed by leaching (circles).

Nanomaterial-based gas sensors used for breath diagnosis

Gas-sensing applications commonly use nanomaterials (NMs) because of their unique physicochemical properties, including a high surface-to-volume ratio, enormous number of active sites, controllable morphology, and potential for miniaturisation.

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.

Highly selective detection of methanol over ethanol by a handheld gas sensor

Methanol poisoning causes blindness, organ failure or even death when recognized too late. Currently, there is no methanol detector for quick diagnosis by breath analysis or for screening of laced beverages. Typically, chemical sensors cannot distinguish methanol from the much higher ethanol background. Here, we present an inexpensive and handheld sensor for highly selective methanol detection. It consists of a separation column (Tenax) separating methanol from interferants like ethanol, acetone or hydrogen, as in gas chromatography, and a chemoresistive gas sensor (Pd-doped SnO2 nanoparticles) to quantify the methanol concentration. This way, methanol is measured within 2 min from 1 to 1000 ppm without interference of much higher ethanol levels (up to 62,000 ppm). As a proof-of-concept, we reliably measure methanol concentrations in spiked breath samples and liquor. This could enable the realization of highly selective sensors in emerging applications such as breath analysis or air quality monitoring.

On-Line Analysis of Exhaled Breath Focus Review

On-line analysis of exhaled breath offers insight into a person's metabolism without the need for sample preparation or sample collection. Due to its noninvasive nature and the possibility to sample continuously, the analysis of breath has great clinical potential. The unique features of this technology make it an attractive candidate for applications in medicine, beyond the task of diagnosis. We review the current methodologies for on-line breath analysis, discuss current and future applications, and critically evaluate challenges and pitfalls such as the need for standardization. Special emphasis is given to the use of the technology in diagnosing respiratory diseases, potential niche applications, and the promise of breath analysis for personalized medicine. The analytical methodologies used range from very small and low-cost chemical sensors, which are ideal for continuous monitoring of disease status, to optical spectroscopy and state-of-the-art, high-resolution mass spectrometry. The latter can be utilized for untargeted analysis of exhaled breath, with the capability to identify hitherto unknown molecules. The interpretation of the resulting big data sets is complex and often constrained due to a limited number of participants. Even larger data sets will be needed for assessing reproducibility and for validation of biomarker candidates. In addition, molecular structures and quantification of compounds are generally not easily available from on-line measurements and require complementary measurements, for example, a separation method coupled to mass spectrometry. Furthermore, a lack of standardization still hampers the application of the technique to screen larger cohorts of patients. This review summarizes the present status and continuous improvements of the principal on-line breath analysis methods and evaluates obstacles for their wider application.

Gas sensors using ordered macroporous oxide nanostructures

Detection and monitoring of harmful and toxic gases have gained increased interest in relation to worldwide environmental issues. Semiconducting metal oxide gas sensors have been considered promising for the facile remote detection of gases and vapors over the past decades. However, their sensing performance is still a challenge to meet the demands for practical applications where excellent sensitivity, selectivity, stability, and response/recovery rate are imperative. Therefore, sensing materials with novel architectures and fabrication processes have been pursued with a flurry of research activity. In particular, the preparation of ordered macroporous metal oxide nanostructures is regarded as an intriguing candidate wherein ordered aperture sizes in the range from 50 nm to 1.5 μm can increase the chemical diffusion rate and considerably strengthen the performance stability and repeatability. This review highlights the recent advances in the fabrication of ordered macroporous nanostructures with different dimensions and compositions, discusses the sensing behavior evolution governed by structural layouts, hierarchy, doping, and heterojunctions, as well as considering their general principles and future prospects. This would provide a clear scale for others to tune the sensing performance of porous materials in terms of specific components and structural designs.

A Versatile Method to Enhance the Operational Current of Air-Stable Organic Gas Sensor for Monitoring of Breath Ammonia in Hemodialysis Patients

Point-of-care (POC) application for monitoring of breath ammonia (BA) in hemodialysis (HD) patients has emerged as a promising noninvasive health monitoring approach. In this context, many organic gas sensors have been reported for BA detection. However, one of the major challenges for its integration with affordable household POC application is to achieve stable performance for accuracy and high operational current at low voltage for low-cost read-out circuitry. Herein, we exploited the stability of the Donor-Acceptor polymer on the cylindrical nanopore structure to realize the sensors with a high sensitivity and stability. Then, we proposed a double active layer (DL) strategy that exploits an ultrathin layer of Poly(3-hexylthiophene-2,5-diyl) (P3HT) to serve as a work function buffer to enhance the operational current. The DL sensor exhibits a sustainable enhanced operational current of microampere level and a stable sensing response even with the presence of P3HT layer. This effect is carefully examined with different aspects, including vertical composition profile of DL configuration, lifetime testing on different sensing layer, morphological analysis, and the versatility of the DL strategy. Finally, we utilize the DL sensor to conduct a tracing of BA concentration in two HD patients before and after HD, and correlate it with the blood urea nitrogen (BUN) levels. A good correlation coefficient of 0.96 is achieved. Moreover, the feasibility of DL sensor integrated into a low-cost circuitry was also verified. The results demonstrate the potential of this DL strategy to be used to integrate organic sensor for affordable household POC devices.

Non-contact breath sampling for sensor-based breath analysis

Breath analysis holds great promise for real-time and non-invasive medical diagnosis. Thus, there is a considerable need for simple-in-use and portable analyzers for rapid detection of breath indicators for different diseases in their early stages. Sensor technology meets all of these demands. However, miniaturized breath analyzers require adequate breath sampling methods. In this context, we propose non-contact sampling; namely the collection of breath samples by exhalation from a distance into a miniaturized collector without bringing the mouth into direct contact with the analyzing device. To evaluate this approach different breathing maneuvers have been tested in a real-time regime on a cohort of 23 volunteers using proton transfer reaction mass spectrometry. The breathing maneuvers embraced distinct depths of respiration, exhalation manners, size of the mouth opening and different sampling distances. Two inhalation modes (normal, relaxed breathing and deep breathing) and two exhalation manners (via smaller and wider lips opening) forming four sampling scenarios were selected. A sampling distance of approximately 2 cm was found to be a reasonable trade-off between sample dilution and requirement of no physical contact of the subject with the analyzer. All four scenarios exhibited comparable measurement reproducibility spread of around 10%. For normal, relaxed inspiration both dead-space and end-tidal phases of exhalation lasted approximately 1.5 s for both expiration protocols. Deep inhalation prolongs the end-tidal phase to about 3 s in the case of blowing via a small lips opening, and by 50% when the air is exhaled via a wide one. In conclusion, non-contact breath sampling can be considered as a promising alternative to the existing breath sampling methods, being relatively close to natural spontaneous breathing.

In-Situ Analysis of Essential Fragrant Oils Using a Portable Mass Spectrometer

A portable mass spectrometer was coupled to a direct inlet membrane (DIM) probe and applied to the direct analysis of active fragrant compounds (3-methylbutyl acetate, 2-methyl-3-furanthiol, methyl butanoate, and ethyl methyl sulfide) in real time. These fragrant active compounds are commonly used in the formulation of flavours and fragrances. Results obtained show that the portable mass spectrometer with a direct membrane inlet can be used to detect traces of the active fragrant compounds in complex mixtures such as essential fragrant oils and this represents a novel in-situ analysis methodology. Limits of detection (LOD) in the sub-ppb range (< 2.5 pg) are demonstrated. Standard samples in the gaseous phase presented very good linearity with RSD % at 5 to 7 for the selected active fragrant compounds (i.e., isoamyl acetate, 2-methyl-3-furanthiol, methyl butanoate, and methyl ethyl sulphide). The rise and fall times of the DIM probe are in the ranges from 15 to 31 seconds and 23 to 41 seconds, respectively, for the standard model compounds analysed. The identities of the fragrance active compounds in essential oil samples (i.e., banana, tangerine, papaya, and blueberry muffin) were first identified by comparison with a standard fragrance compounds mixture using their major fragment peaks, the NIST standard reference library, and gas chromatography mass spectrometry (GC-MS) analysis. No sample preparation is required for analysis using a portable mass spectrometer coupled to a DIM probe, so the cycle time from ambient air sampling to the acquisition of the results is at least 65 seconds.

Breath Sensors for Health Monitoring

Breath sensors can revolutionize medical diagnostics by on-demand detection and monitoring of health parameters in a noninvasive and personalized fashion. Despite extensive research for more than two decades, however, only a few breath sensors have been translated into clinical practice. Actually, most never even left the scientific laboratories. Here, we describe key challenges that currently impede realization of breath sensors and highlight strategies to overcome them. Specifically, we start with breath marker selection (with emphasis on metabolic and inflammatory markers) and breath sampling. Next, the sensitivity, stability, and selectivity requirements for breath sensors are described. Concepts are elaborated to systematically address these requirements by material design (focusing on chemoresistive metal oxides), orthogonal arrays, and filters. Finally, aspects of portable device integration, user communication, and clinical applicability are discussed.

Manganese-doped zinc oxide hollow balls for chemiresistive sensing of acetone vapors

Both pure and Mn(II)-doped ZnO hollow structures were synthesized by a solvothermal reaction, and their phase structures, morphologies and elemental composition were characterized. SEM and TEM observations show the pure ZnO and the Mn(II)-doped ZnO balls to possess similar hollow structure with a particle size of about 1.5 μm. Their sensing properties were investigated, and the composite containing 1 atom% of Mn(II) (1% Mn-ZnO) is found be display the highest selectivity for acetone. The detection limit is 100 ppm acetone at 234 °C which is 4.6 times lower than that of the pure ZnO. In addition, the response time is shorter. Graphical abstract ZnO and Mn-doped ZnO hollow balls were prepared by a hydrothermal method, and their gas-sensing properties were investigated. Zinc(II) oxide doped with 1 atom% Mn(II) demonstrated an outstanding sensing behavior towards acetone vapors.

Volatolomics: A broad area of experimentation

Chemical analysis (detection and monitoring) of compounds associated with the metabolic activities of an organism is at the cutting edge of science. Volatile metabolomics (volatolomics) are applied in a broad range of applications including: biomedical research (e.g. disease diagnostic tools, personalized healthcare and nutrition, etc.), toxicological analysis (e.g. exposure tool to environmental pollutants, toxic and hazardous chemical environments, industrial accidents, etc.), molecular communications, forensics, safety and security (e.g. search and rescue operations). In the present review paper, an overview of recent advances and applications of volatolomics will be given. The main focus will be on volatile organic compounds (VOCs) originating from biological secretions of various organisms (e.g. microorganisms, insects, plants, humans) and resulting fusion of chemical information. Bench-top and portable or field-deployable technologies-systems will also be presented and discussed.

Orthogonal gas sensor arrays by chemoresistive material design

Gas sensor arrays often lack discrimination power to different analytes and robustness to interferants, limiting their success outside of research laboratories. This is primarily due to the widely sensitive (thus weakly-selective) nature of the constituent sensors. Here, the effect of orthogonality on array accuracy and precision by selective sensor design is investigated. Therefore, arrays of (2-5) selective and non-selective sensors are formed by systematically altering array size and composition. Their performance is evaluated with 60 random combinations of ammonia, acetone and ethanol at ppb to low ppm concentrations. Best analyte predictions with high coefficients of determination (R²) of 0.96 for ammonia, 0.99 for acetone and 0.88 for ethanol are obtained with an array featuring high degree of orthogonality. This is achieved by using distinctly selective sensors (Si:MoO₃ for ammonia and Si:WO₃ for acetone together with Si:SnO₂) that improve discrimination power and stability of the regression coefficients. On the other hand, arrays with collinear sensors (Pd:SnO₂, Pt:SnO₂ and Si:SnO₂) hardly improve gas predictions having R² of 0.01, 0.86 and 0.28 for ammonia, acetone and ethanol, respectively. Sometimes they even exhibited lower coefficient of determination than single sensors as a Si:MoO₃ sensor alone predicts ammonia better with a R² of 0.68. Graphical abstract Conventional arrays (red) with weakly-selective sensors span a significantly smaller volume in the analyte space than arrays containing distinctly-selective sensors (orthogonal array, green). Orthogonal arrays feature better accuracy and precision than conventional arrays in mixtures of ammonia, acetone and ethanol.

Guiding Ketogenic Diet with Breath Acetone Sensors

Ketogenic diet (KD; high fat, low carb) is a standard treatment for obesity, neurological diseases (e.g., refractory epilepsy) and a promising method for athletes to improve their endurance performance. Therein, the level of ketosis must be regulated tightly to ensure an effective therapy. Here, we introduce a compact and inexpensive breath sensor to monitor ketosis online and non-invasively. The sensor consists of Si-doped WO₃ nanoparticles that detect breath acetone selectively with non-linear response characteristics in the relevant range of 1 to 66 ppm, as identified by mass spectrometry. When tested on eleven subjects (five women and six men) undergoing a 36-h KD based on the Johns Hopkins protocol, this sensor clearly recognizes the onset and progression of ketosis. This is in good agreement to capillary blood β-hydroxybutyrate (BOHB) measurements. Despite similar dieting conditions, strong inter-subject differences in ketosis dynamics were observed and correctly identified by the sensor. These even included breath acetone patterns that could be linked to low tolerance to that diet. As a result, this portable breath sensor represents an easily applicable and reliable technology to monitor KD, possibly during medical treatment of epilepsy and weight loss.