An Easy to Manufacture Micro Gas Preconcentrator for Chemical Sensing Applications

Synergistic energy-efficient capture of VOCs and metal-free catalytic conversion using magneto-inductive Guefoams: Proof-of-concept in n-hexane-enriched nitrogen streams

Addressing contemporary environmental and health concerns requires reducing pollutant emissions and converting them into less harmful or valuable compounds within the framework of the circular economy. Guefoam materials offer a promising solution by enabling the capture and pre-concentration of volatile organic compounds (VOCs), while facilitating the structuring of active phases for heterogeneous catalytic conversions. This study demonstrates the benefits of merging two newly designed electromagnetic induction-assisted ceramic matrix Guefoams into a portable integrated unit, synergizing the pre-concentration and chemical transformation of n-hexane, a VOC with special challenges. One Guefoam serves as an adsorbent, whereas the other plays a catalytic role. These Guefoams host guest phases, which consist of composite materials combining a steel core with magneto-inductive properties encased in a highly porous carbonaceous layer. This carbonaceous material undertakes a dual mission: adsorbing n-hexane from a nitrogen stream within the adsorptive Guefoam and, upon phosphorus doping in the catalytic Guefoam, orchestrating the metal-free selective dehydroaromatization of n-hexane into benzene. The design and integration of these novel Guefoam materials into a unified functional entity prove highly effective in pre-concentrating (enrichment factors up to 275) and catalyzing n-hexane with up to 84 % conversion and 94 % benzene selectivity while remaining energy-efficient and environmentally sustainable.

Data-Driven Approach to Modeling Microfabricated Chemical Sensor Manufacturing

We have developed a statistical model-based approach to the quality analysis (QA) and quality control (QC) of a gas micro pre-concentrator chip (μPC) performance when manufactured at scale for chemical and biochemical analysis of volatile organic compounds (VOCs). To test the proposed model, a medium-sized university-led production batch of 30 wafers of chips were subjected to rigorous chemical performance testing. We quantitatively report the outcomes of each manufacturing process step leading to the final functional chemical sensor chip. We implemented a principal component analysis (PCA) model to score individual chip chemical performance, and we observed that the first two principal components represent 74.28% of chemical testing variance with 111 of 118 viable chips falling into the 95% confidence interval. Chemical performance scores and chip manufacturing data were analyzed using a multivariate regression model to determine the most influential manufacturing parameters and steps. In our analysis, we find the amount of sorbent mass present in the chip (variable importance score = 2.6) and heater and the RTD resistance values (variable importance score = 1.1) to be the manufacturing parameters with the greatest impact on chemical performance. Other non-obvious latent manufacturing parameters also had quantified influence. Statistical distributions for each manufacturing step will allow future large-scale production runs to be statistically sampled during production to perform QA/QC in a real-time environment. We report this study as the first data-driven, model-based production of a microfabricated chemical sensor.

Control Software Design for a Multisensing Multicellular Microscale Gas Chromatography System

Microscale gas chromatography (μGC) systems are miniaturized instruments that typically incorporate one or several microfabricated fluidic elements; such systems are generally well suited for the automated sampling and analysis of gas-phase chemicals. Advanced μGC systems may incorporate more than 15 elements and operate these elements in different coordinated sequences to execute complex operations. In particular, the control software must manage the sampling and analysis operations of the μGC system in a time-sensitive manner; while operating multiple control loops, it must also manage error conditions, data acquisition, and user interactions when necessary. To address these challenges, this work describes the investigation of multithreaded control software and its evaluation with a representative μGC system. The μGC system is based on a progressive cellular architecture that uses multiple μGC cells to efficiently broaden the range of chemical analytes, with each cell incorporating multiple detectors. Implemented in Python language version 3.7.3 and executed by an embedded single-board computer, the control software enables the concurrent control of heaters, pumps, and valves while also gathering data from thermistors, pressure sensors, capacitive detectors, and photoionization detectors. A graphical user interface (UI) that operates on a laptop provides visualization of control parameters in real time. In experimental evaluations, the control software provided successful operation and readout for all the components, including eight sets of thermistors and heaters that form temperature feedback loops, two sets of pressure sensors and tunable gas pumps that form pressure head feedback loops, six capacitive detectors, three photoionization detectors, six valves, and an additional fixed-flow gas pump. A typical run analyzing 18 chemicals is presented. Although the operating system does not guarantee real-time operation, the relative standard deviations of the control loop timings were <0.5%. The control software successfully supported >1000 μGC runs that analyzed various chemical mixtures.

Metal-organic framework-based high-performance column chip for micro gas chromatography: hybrid function for simultaneous preconcentration and separation of volatile organic compounds

Numerous attempts have been made to replace commercial bulky gas chromatography (GC) systems with compact GC systems for monitoring volatile organic compounds in indoor air. However, recently developed compact GC systems are still too bulky in terms of user convenience, portability, and on-site analysis. Hence, an advanced miniaturization of compact GC systems is needed. Importantly, the small and high-performance gas pretreatment chip devices should be developed for compact GC systems. This paper reports the development of a metal-organic framework (MOF)-coated hybrid micro gas chromatography column chip (hybrid GC chip) capable of preconcentration and separation on harmful volatile organic compounds at low-concentration in one single chip device. The hybrid GC chip, 2 cm × 2 cm in size, was fabricated using a microelectromechanical systems process. The synthesized MOF-5 particles were coated on the inner wall of the fabricated hybrid GC chip and acted as an adsorbent and a stationary phase. The developed hybrid GC chip afforded high preconcentration factors with 1033-1237 and high separation resolutions with 3.8-13.3. The developed column showed good performance as a gas preconcentrator and separation column, and is the first device to perform both roles in one single chip device.

Active sampling of volatile chemicals for non-invasive classification of chicken eggs by sex early in incubation

According to industry estimates, approximately 7 billion day-old male chicks are disposed of annually worldwide because they are not of use to the layer industry. A practical process to identify the sex of the egg early in incubation without penetrating the egg would improve animal welfare, reduce food waste and mitigate environmental impact. We implemented a moderate vacuum pressure system through commercial egg-handling suction cups to collect volatile organic compounds (VOCs). Three separate experiments were set up to determine optimal conditions to collect eggs VOCs to discriminate male from female embryos. Optimal extraction time (2 min), storage conditions (short period of incubation during egg storage (SPIDES) at days 8-10 of incubation), and sampling temperature (37.5°C) were determined. Our VOC-based method could correctly differentiate male from female embryos with more than 80% accuracy. These specifications are compatible with the design of specialized automation equipment capable of high-throughput, in-ovo sexing based on chemical sensor microchips.

Controlled air exchange rate method to evaluate reduction of volatile organic compounds by indoor air cleaners

Air cleaning technologies are needed to reduce indoor concentrations and exposure to volatile organic compounds (VOCs). Currently, air cleaning technologies lack an accepted test standard to evaluate their VOC removal performance. A protocol to evaluate the VOC removal performance of air cleaning devices was developed and piloted with two devices. This method injects a VOC mixture and carbon dioxide into a test chamber, supplies outdoor air at a standard building ventilation rate, periodically measures the VOC concentrations in the chamber using solid phase microextraction-gas chromatography-mass spectrometry over a 3-h decay period, and compares the decay rate of VOCs to carbon dioxide to measure the VOC removal air cleaning performance. The method was demonstrated with both a hydroxyl radical generator and an activated carbon air cleaner. It was shown that the activated carbon air cleaner device tested had a clean air delivery rate an order of magnitude greater than the hydroxyl radical generator device (72.10 vs 6.32 m3/h).

Development of a Low-Cost Electronic Nose with an Open Sensor Chamber: Application to Detection of Ciboria batschiana

In the construction of electronic nose devices, two groups of measurement setups could be distinguished when we take into account the design of electronic nose chambers. The simpler one consists of placing the sensors directly in the environment of the measured gas, which has an important advantage, in that the composition of the gas is not changed as the gas is not diluted. However, that has an important drawback in that it is difficult to clean sensors between measurement cycles. The second, more advanced construction, contains a pneumatic system transporting the gas inside a specially designed sensor chamber. A new design of an electronic nose gas sensor chamber is proposed, which consists of a sensor chamber with a sliding chamber shutter, equipped with a simple pneumatic system for cleaning the air. The proposal combines the advantages of both approaches to the sensor chamber designs. The sensors can be effectively cleared by the flow of clean air, while the measurements are performed in the open state when the sensors are directly exposed to the measured gas. Airflow simulations were performed to confirm the efficiency of clean air transport used for sensors' cleaning. The demonstrated electronic nose applies eight Figaro Co. MOS TGS series sensors, in which a transient response caused by a change of the exposition to measured gas, and change of heater voltage, was collected. The new electronic nose was tested as applied to the differentiation between the samples of Ciboria batschiana fungi, which is one of the most harmful pathogens of stored acorns. The samples with various coverage, thus various concentrations of the studied odor, were measured. The tested device demonstrated low noise and a good level of repetition of the measurements, with stable results during several hours of repetitive measurements during an experiment lasting five consecutive days. The obtained data allowed complete differentiation between healthy and infected samples.

Nanocatalytic Interface to Decode the Phytovolatile Language for Latent Crop Diagnosis in Future Farms

Crop diseases cause the release of volatiles. Here, the use of an SnO₂-based chemoresistive sensor for early diagnosis has been attempted. Ionone is one of the signature volatiles released by the enzymatic and nonenzymatic cleavage of carotene at the latent stage of some biotic stresses. To our knowledge, this is the first attempt at sensing volatiles with multiple oxidation sites, i.e., ionone (4 oxidation sites), from the phytovolatile library, to derive stronger signals at minimum concentrations. Further, the sensitivity was enhanced on an interdigitated electrode by the addition of platinum as the dopant for a favorable space charge layer and for surface island formation for reactive interface sites. The mechanistic influence of oxygen vacancy formation was studied through detailed density functional theory (DFT) calculations and reactive oxygen-assisted enhanced binding through X-ray photoelectron spectroscopy (XPS) analysis.

A low cost, easy-to-assemble, open-source modular mobile sampler design for thermal desorption analysis of breath and environmental VOCs

Exhaled breath vapor contains hundreds of volatile organic compounds (VOCs), which are the byproducts of health and disease metabolism, and they have clinical and diagnostic potential. Simultaneous collection of breath VOCs and background environmental VOCs is important to ensure analyses eliminate exogenous compounds from clinical studies. We present a mobile sampling system to extract gaseous VOCs onto commercially available sorbent-packed thermal desorption tubes. The sampler can be connected to a number of commonly available disposable and reusable sampling bags, in the case of this study, a Tedlar bag containing a breath sample. Alternatively, the inlet can be left open to directly sample room or environmental air when obtaining a background VOC sample. The system contains a screen for the operator to input a desired sample volume. A needle valve allows the operator to control the sample flow rate, which operates with an accuracy of -1.52 ± 0.63% of the desired rate, and consistently generated that rate with 0.12 ± 0.06% error across repeated measures. A flow pump, flow sensor and microcontroller allow volumetric sampling, as opposed to timed sampling, with 0.06 ± 0.06% accuracy in the volume extracted. Four samplers were compared by sampling a standard chemical mixture, which resulted in 6.4 ± 4.7% error across all four replicate modular samplers to extract a given VOC. The samplers were deployed in a clinical setting to collect breath and background/environmental samples, including patients with active SARS-CoV-2 infections, and the device could easily move between rooms and can undergo required disinfection protocols to prevent transmission of pathogens on the case exterior. All components required for assembly are detailed and are made publicly available for non-commercial use, including the microcontroller software. We demonstrate the device collects volatile compounds, including use of chemical standards, and background and breath samples in real use conditions.

Micropreconcentrators: Recent Progress in Designs and Applications

The detection of chemicals is a fundamental issue of modern civilisation, however existing methods do not always achieve the desired sensitivity. Preconcentrators, which are devices that allow increasing the concentration of the intended analyte via e.g., adsorption/desorption, are one of the solutions for increasing the sensitivity of chemical detection. The increased detection sensitivity granted by preconcentration can be used to miniaturise detection instruments, granting them portability. The primary goal of this review is to report on and briefly explain the most relevant recent developments related to the design and applications of preconcentrators. The key design elements of preconcentrators and the emerging area of liquid-phase preconcentrators are briefly discussed, with the most significant applications of these devices being highlighted.

Selectivity in trace gas sensing: recent developments, challenges, and future perspectives

Selectivity is one of the most crucial figures of merit in trace gas sensing, and thus a comprehensive assessment is necessary to have a clear picture of sensitivity, selectivity, and their interrelations in terms of quantitative and qualitative views.

A MEMS µ-Preconcentrator Employing a Carbon Molecular Sieve Membrane for Highly Volatile Organic Compound Sampling

This paper presents the synthesis and evaluation of a carbon molecular sieve membrane (CMSM) grown inside a MEMS-fabricated μ-preconcentrator for sampling highly volatile organic compounds. An array of µ-pillars measuring 100 µm in diameter and 250 µm in height were fabricated inside a microfluidic channel to increase the attaching surface for the CMSM. The surface area of the CMSM was measured as high as 899 m2/g. A GC peak amplification factor >2 × 104 was demonstrated with gaseous ethyl acetate. Up to 1.4 L of gaseous ethanol at the 100 ppb level could be concentrated without exceeding the capacity of this microchip device. Sharp desorption chromatographic peaks (<3.5 s) were obtained while using this device directly as a GC injector. Less volatile compounds such as gaseous toluene, m-xylene, and mesitylene appeared to be adsorbed strongly on CMSM, showing a memory effect. Sampling parameters such as sample volatilities, sampling capacities, and compound residual issues were empirically determined and discussed.

Environmental sampling of volatile organic compounds during the 2018 Camp Fire in Northern California

Trace analysis of volatile organic compounds (VOCs) during wildfires is imperative for environmental and health risk assessment. The use of gas sampling devices mounted on unmanned aerial vehicles (UAVs) to chemically sample air during wildfires is of great interest because these devices move freely about their environment, allowing for more representative air samples and the ability to sample areas dangerous or unreachable by humans. This work presents chemical data from air samples obtained in Davis, CA during the most destructive wildfire in California's history - the 2018 Camp Fire - as well as the deployment of our sampling device during a controlled experimental fire while fixed to a UAV. The sampling mechanism was an in-house manufactured micro-gas preconcentrator (µPC) embedded onto a compact battery-operated sampler that was returned to the laboratory for chemical analysis. Compounds commonly observed in wildfires were detected during the Camp Fire using gas chromatography mass spectrometry (GC-MS), including BTEX (benzene, toluene, ethylbenzene, m+p-xylene, and o-xylene), benzaldehyde, 1,4-dichlorobenzene, naphthalene, 1,2,3-trimethylbenzene and 1-ethyl-3-methylbenzene. Concentrations of BTEX were calculated and we observed that benzene and toluene were highest with average concentrations of 4.7 and 15.1 µg/m³, respectively. Numerous fire-related compounds including BTEX and aldehydes such as octanal and nonanal were detected upon experimental fire ignition, even at a much smaller sampling time compared to samples taken during the Camp Fire. Analysis of the air samples taken both stationary during the Camp Fire and mobile during an experimental fire show the successful operation of our sampler in a fire environment.

Trends and applications in plant volatile sampling and analysis

Volatile organic compounds (VOCs) released by plants serve as information and defense chemicals in mutualistic and antagonistic interactions and mitigate effects of abiotic stress. Passive and dynamic sampling techniques combined with gas chromatography-mass spectrometry analysis have become routine tools to measure emissions of VOCs and determine their various functions. More recently, knowledge of the roles of plant VOCs in the aboveground environment has led to the exploration of similar functions in the soil and rhizosphere. Moreover, VOC patterns have been recognized as sensitive and time-dependent markers of biotic and abiotic stress. This focused review addresses these developments by presenting recent progress in VOC sampling and analysis. We show advances in the use of small, inexpensive sampling devices and describe methods to monitor plant VOC emissions in the belowground environment. We further address latest trends in real-time measurements of volatilomes in plant phenotyping and most recent developments of small portable devices and VOC sensors for non-invasive VOC fingerprinting of plant disease. These technologies allow for innovative approaches to study plant VOC biology and application in agriculture.

An environmental air sampler to evaluate personal exposure to volatile organic compounds

A micro fabricated chip-based wearable air sampler was used to monitor the personnel exposure of volatile chemical concentrations in microenvironments. Six teenagers participated in this study and 14 volatile organic compounds (VOCs) including naphthalene, 3-decen-1-ol, hexanal, nonanal, methyl salicylate and limonene gave the highest abundance during routine daily activity. VOC exposure associated with daily activities and the location showed strong agreements with two of the participant's results. One of these subjects had the highest exposure to methyl salicylate that was supported by the use of a topical analgesic balm containing this compound. Environmental based air quality monitoring followed by the personnel exposure studies provided additional evidence associated to the main locations where the participants traveled. Toluene concentrations observed at a gas station were exceptionally high, with the highest amount observed at 1213.1 ng m-3. One subject had the highest exposure to toluene and the GPS data showed clear evidence of activities neighboring a gas station. This study shows that this wearable air sampler has potential applications including hazardous VOC exposure monitoring in occupational hazard assessment for certain professions, for example in industries that involve direct handling of petroleum products.

Opto-Electronic Nose Coupled to a Silicon Micro Pre-Concentrator Device for Selective Sensing of Flavored Waters

Headspace analysis of highly humid samples remains a challenge for artificial olfaction. Based on surface plasmon resonance imaging and bio-based sensors, the NeOse Pro olfactive analyzer yields multivariate data and enhances the statistical discrimination capacity of odor patterns. However, the presence of a high background signal, such as water vapor from aqueous samples, may deteriorate its discriminant ability. Recently, miniaturized pre-concentrators packed with hydrophobic adsorbent have been developed to improve the detection limit of gas analysis methods and to enhance their selectivity by reducing the water’s background signal. This work presents, for the first time, the coupling of a miniaturized silicon micro pre-concentration unit (µPC) to a bio-based opto-electronic nose (NeOse Pro). The results showed that the coupling of a silicon µPC with the NeOse Pro led to an improvement in the detection limit of n-nonane by at least a factor of 125. Additionally, principal component analysis (PCA) of eight different flavored waters showed an enhanced discrimination ability of the coupled set-up in highly humid conditions.

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.

Towards Convergence: How to Do Transdisciplinary Environmental Health Disparities Research

Increasingly, funders (i.e., national, public funders, such as the National Institutes of Health and National Science Foundation in the U.S.) and scholars agree that single disciplines are ill equipped to study the pressing social, health, and environmental problems we face alone, particularly environmental exposures, increasing health disparities, and climate change. To better understand these pressing social problems, funders and scholars have advocated for transdisciplinary approaches in order to harness the analytical power of diverse and multiple disciplines to tackle these problems and improve our understanding. However, few studies look into how to conduct such research. To this end, this article provides a review of transdisciplinary science, particularly as it relates to environmental research and public health. To further the field, this article provides in-depth information on how to conduct transdisciplinary research. Using the case of a transdisciplinary, community-based, participatory action, environmental health disparities study in California's Central Valley provides an in-depth look at how to do transdisciplinary research. Working with researchers from the fields of social sciences, public health, biological engineering, and land, air, and water resources, this study aims to answer community residents' questions related to the health disparities they face due to environmental exposure. Through this case study, I articulate not only the logistics of how to conduct transdisciplinary research but also the logics. The implications for transdisciplinary methodologies in health disparity research are further discussed, particularly in the context of team science and convergence science.

Volatile organic compound (VOC) emissions of CHO and T cells correlate to their expansion in bioreactors

Volatile organic compound (VOC) emissions were measured from Chinese Hamster Ovary (CHO) cell and T cell bioreactor gas exhaust lines with the goal of non-invasively metabolically profiling the expansion process. Measurements of cellular 'breath' were made directly from the gas exhaust lines using polydimethylsiloxane (PDMS)-coated magnetic stir bars, which underwent subsequent thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) analysis. Baseline VOC profiles were observed from bioreactors filled with only liquid media. After inoculation, unique VOC profiles correlated to cell expansion over the course of 8 d. Partial least squares (PLS) regression models were built to predict cell culture density based on VOC profiles of CHO and T cells (R ² = 0.671 and R ² = 0.769, respectively, based on a validation data set). T cell runs resulted in 47 compounds relevant to expansion while CHO cell runs resulted in 45 compounds; the 20 most relevant compounds of each cell type were putatively identified. On the final experimental days, sorbent-covered stir bars were placed directly into cell-inoculated media and into media controls. Liquid-based measurements from spent media containing cells could be distinguished from media-only controls, indicating soluble VOCs excreted by the cells during expansion. A PLS-discriminate analysis (PLS-DA) was performed, and 96 compounds differed between T cell-inoculated media and media controls with 72 compounds for CHO cells; the 20 most relevant compounds of each cell line were putatively identified. This work demonstrates that the volatilome of cell cultures can be exploited by chemical detectors in bioreactor gas and liquid waste lines to non-invasively monitor cellular health and could possibly be used to optimize cell expansion conditions 'on-the-fly' with appropriate control loop systems. Although the basis for statistical models included compounds without certain identification, this work provides a foundation for future research of bioreactor emissions. Future studies must move towards identifying relevant compounds for understanding of underlying biochemistry.

Wearable Environmental Monitor To Quantify Personal Ambient Volatile Organic Compound Exposures

Air pollution can cause acute and chronic health problems. It has many components, and one component of interest is volatile organic compounds (VOCs). While the outdoor environment may have regulations regarding exposure limits, the indoor environment is often unregulated and VOCs often appear in greater concentrations in the indoor environment. Therefore, it is equally critical to monitor both the indoor and outdoor environments for ambient chemical levels that an individual person is exposed to. While a number of different chemical detectors exist, most lack the ability to provide portable monitoring. We have developed a portable and wearable sampler that collects environmental VOCs in a person's immediate "exposure envelope" onto custom micro-preconcentrator chips for later benchtop analysis. The system also records ambient temperature and humidity and the GPS location during sampling, and the chip cartridges can be used in sequence over time to complete a profile of individual chemical exposure over the course of hours/days/weeks/months. The system can be programmed to accumulate sample for various times with varying periodicity. We first tested our sampler in the laboratory by completing calibration curves and testing saturation times for various common chemicals. The sampler was also tested in the field by collecting both indoor and outdoor personal exposure samples. Additionally under IRB approval, a teenaged volunteer wore the sampler for 5 days during which it sampled periodically throughout a 12 h period each day and the volunteer replaced the micro-preconcentrator chip each day.

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.

Fluorescence response of cruciform D–π–A–π–D phenothiazine derivatives to mechanical force

Three kinds of crystals of two phenothiazine derivatives transformed into similar amorphous powders, in which the short-range π-stacking can be deduced by single-crystal structure.

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.

Miniaturization of breath sampling with silicon chip: application to volatile tobacco markers tracking

This work presents the performances of silicon micro-preconcentrators chips for breath sampling. The silicon chips were coupled to a handheld battery powered system for breath sampling and direct injection in a laboratory gas chromatography mass spectrometry system through thermal desorption (TD). Performances of micro-preconcentrators were first compared to commercial TD for benzene trapping. Similar chromatographic peaks after gas chromatographic separation were observed while the volume of sample needed was reduced by a factor of 5. Repeatability and day to day variability of the micro-preconcentrators were then studied for a 500 ppb synthetic model mixture injected three times a day four days in a row: 8% and 12% were measured respectively. Micro-preconcentrator to micro-preconcentrator variability was not significant compared to day to day variability. In addition, micro-preconcentrators were tested for breath samples collected in Tedlar® bags. Three analyses of the same breath sample displayed relative standard deviations values below 16% for eight of the ten most intense peaks. Finally, the performances of micro-preconcentrators for breath sampling on a single expiration were illustrated with the example of volatile tobacco markers tracking. The signals of three smoking markers in breath, benzene, 2,5-dimethylfuran, and toluene were studied. Concentrations of benzene and toluene were found to be 10 to 100 higher in the breath of smokers. 2,5-dimethylfuran was only found in the breath of smokers. The elimination kinetics of the markers were followed as well during 4 h: a fast decrease of the signal of the three markers in breath was observed 20 min after smoking in good agreement with what is described in the literature. Those results demonstrate the efficiency of silicon chips for breath sampling, compared to the state of the art techniques. Thanks to miniaturization and lower sample volumes needed, micro-preconcentrators could be in the future a key technology towards portable breath sampling and analysis.

Highly Selective and Rapid Breath Isoprene Sensing Enabled by Activated Alumina Filter

Isoprene is a versatile breath marker for noninvasive monitoring of high blood cholesterol levels as well as for influenza, end-stage renal disease, muscle activity, lung cancer, and liver disease with advanced fibrosis. Its selective detection in complex human breath by portable devices (e.g., metal-oxide gas sensors), however, is still challenging. Here, we present a new filter concept based on activated alumina powder enabling fast and highly selective detection of isoprene at the ppb level and high humidity. The filter contains high surface area adsorbents that retain hydrophilic compounds (e.g., ketones, alcohols, ammonia) representing major interferants in breath while hydrophobic isoprene is not affected. As a proof-of-concept, filters of commercial activated alumina powder are combined with highly sensitive but rather nonspecific, nanostructured Pt-doped SnO₂ sensors. This results in fast (10 s) measurement of isoprene down to 5 ppb at 90% relative humidity with outstanding selectivity (>100) to breath-relevant acetone, ammonia, ethanol, and methanol, superior to state-of-the-art isoprene sensors. Most importantly, when exposed continuously to simulated breath mixtures (four analytes) for 8 days, this filter-sensor system showed stable performance. It can be incorporated readily into a portable breath isoprene analyzer promising for simple-in-use monitoring of blood cholesterol or other patho/physiological conditions.