Belt-Mounted Micro-Gas-Chromatograph Prototype for Determining Personal Exposures to Volatile-Organic-Compound Mixture Components

Identification of Different Classes of VOCs Based on Optical Emission Spectra Using a Dielectric Barrier Helium Plasma Coupled with a Mini Spectrometer

In this study, a micro helium dielectric barrier discharge (μHDBD) plasma device fabricated using 3D printing and molding techniques was coupled with a mini spectrometer to detect and identify different classes of volatile organic compounds (VOCs) using optical emission spectrometry (OES). We tested 11 VOCs belonging to three different classes (straight-chain alkanes, aromatics, and polar organic compounds). Our results clearly demonstrate that the optical emission spectra of different classes of VOCs show clear differences, and therefore, can be used for identification. Additionally, the emission spectra of VOCs with a similar structure (such as n-pentane, n-hexane, n-heptane, n-octane, and n-nonane) have similar optical emission spectrum shape. Acetone and ethanol also have similar emission wavelengths, but they show different line intensities for the same concentrations. We also found that the side-chain group of aromatics will also affect the emission spectra even though they have a similar structure (all have a benzene ring). Moreover, our μHDBD-OES system can also identify multiple compounds in VOC mixtures. Our work also demonstrates the possibility of identifying different classes of VOCs by the OES shape.

Automatic peak detection algorithm based on continuous wavelet transform for complex chromatograms from multi-detector micro-scale gas chromatographs

Peak detection for chromatograms, including the detection of peak retention times, peak start locations, and peak end locations, is an important processing step for extracting peak information that is used for chemical recognition. Compared to benchtop gas chromatographs, the chromatograms generated by microscale gas chromatographs (µGCs) often contain higher noise levels, peak overlap, peak asymmetry, and both positive and negative chromatographic peaks, increasing the challenges for peak detection. This paper reports an automatic peak detection algorithm based on continuous wavelet transform (CWT) for chromatograms generated by multi-detector µGCs. The relationship between chemical retention time and peak width is leveraged to differentiate chromatographic peaks from noise and baseline drift. Special features in the CWT coefficients are leveraged to detect peak overlap and asymmetry. For certain detectors that may generate positive and negative chromatographic peaks, the peaks cannot be independently detected reliably, but the peak information can be well extracted using peak information generated by other in-line single-polarity detectors. The implemented algorithm provided a true positive rate of 97.2 % and false discovery rate of 7.8 % for chromatograms generated by a µGC with three integrated detectors, two capacitive and one photoionization. The chromatograms included complex scenarios with positive and negative chromatographic peaks, up to five consecutive overlapping peaks, peak asymmetry factor up to 24, and signal-to-noise ratios spanning 9-2800.

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.

On-Site Detection of Volatile Organic Compounds (VOCs)

Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.

Highly Integrated μGC Based on a Multisensing Progressive Cellular Architecture with a Valveless Sample Inlet

Microscale gas chromatographs (μGCs) promise in-field analysis of volatile organic compounds (VOCs) in environmental and industrial monitoring, healthcare, and homeland security applications. As a step toward addressing challenges with performance and manufacturability, this study reports a highly integrated monolithic chip implementing a multisensing progressive cellular architecture. This architecture incorporates three μGC cells that are customized for different ranges of analyte volatility; each cell includes a preconcentrator and separation column, two complementary capacitive detectors, and a photoionization detector (PID). An on-chip carrier gas filter scrubs ambient air for the analysis. The monolithic chip, with all 16 components, is 40.3 × 55.7 mm² in footprint. To accommodate surface adsorptive and low-volatility analytes, the architecture eliminates the commonly used inlet valve, eliminating the need for chemically inactive surfaces in the valves and pumps, allowing the use of standard parts. Representative analysis is demonstrated from a nonpolar 14-analyte mixture, a polar 12-analyte mixture, and a 3-phosphonate ester mixture, covering a wide vapor pressure range (0.005-68.5 kPa) and dielectric constant range (1.8-23.2). The three types of detectors show highly complementary responses. Quantitative analysis is shown in the tens to hundreds ppb range. With 200 mL samples, the projected detection limits reach 0.12-4.7 ppb. Limited tests performed at 80% humidity showed that the analytes with vapor pressures <12 kPa were unaffected. A typical full run takes 28 min and consumes 2.3 kJ energy for the fluidic elements (excluding electronics). By eliminating chip-to-chip fluidic interconnections and requiring just one custom-fabricated element, this work presents a path toward high-performance and highly manufacturable μGCs.

Intra-workday fluctuations of airborne contaminant concentration and the time-weighted average

Air contaminant concentrations vary between and within workdays and are often measured across a workday by passing a known air volume through a collection device. Laboratory analysis determines the contaminant mass trapped, providing a time-weighted average air concentration (C_TWA). This approach was driven by the best technologies available as exposure measurement processes developed and accuracy and measurement precision were sought. However, all integrated concentration•time (C•t) values determining C_TWA are equally weighted in assessing exposures, intra-workday concentration variability is unknown, and results are available days later. At times inappropriately, an occupational exposure limit (OEL) expressed as a C_TWA also requires equal weighting of all C•t values across an exposure period following concepts of Haber's law. Continuous monitoring (real-time detection) informs both the C_TWA and the variability of C during sampling, which are needed for stressors where a ceiling or peak OEL exists, for dangerous exposures to permanent gas-type contaminants, and for immediately dangerous to life or health (IDLH) conditions. Selective and accurate real-time detection instruments are not available for all air contaminants, but exposure magnitude information may be provided. The large amounts of data from continuous monitoring and the ability to correlate exposure maxima to specific tasks are also important. An exposure assessment role exists for selective and nonselective monitors, and in some cases, similar accuracy and precision are provided compared to laboratory analyses. Continuous monitoring may be of value when the alternative is the collection of a few C_TWA data points. Digitized personal monitor data can support the automation of some exposure control decisions or allow such decisions to be made by people in near real-time. The emerging Internet of Things (IoT) offers opportunities to integrate digital exposure data into decision-making to increase both efficiency and safety. The perceived and real uncertainty associated with real-time exposure assessments may be lessened with work to rule out the presence of know interferents and confirm the presence of target analytes.

Progressive Cellular Architecture in Microscale Gas Chromatography for Broad Chemical Analyses

Gas chromatography is widely used to identify and quantify volatile organic compounds for applications ranging from environmental monitoring to homeland security. We investigate a new architecture for microfabricated gas chromatography systems that can significantly improve the range, speed, and efficiency of such systems. By using a cellular approach, it performs a partial separation of analytes even as the sampling is being performed. The subsequent separation step is then rapidly performed within each cell. The cells, each of which contains a preconcentrator and separation column, are arranged in progression of retentiveness. While accommodating a wide range of analytes, this progressive cellular architecture (PCA) also provides a pathway to improving energy efficiency and lifetime by reducing the need for heating the separation columns. As a proof of concept, a three-cell subsystem (PCA3mv) has been built; it incorporates a number of microfabricated components, including preconcentrators, separation columns, valves, connectors, and a carrier gas filter. The preconcentrator and separation column of each cell are monolithically implemented as a single chip that has a footprint of 1.8 × 5.2 cm2. This subsystem also incorporates two manifold arrays of microfabricated valves, each of which has a footprint of 1.3 × 1.4 cm2. Operated together with a commercial flame ionization detector, the subsystem has been tested against polar and nonpolar analytes (including alkanes, alcohols, aromatics, and phosphonate esters) over a molecular weight range of 32-212 g/mol and a vapor pressure range of 0.005-231 mmHg. The separations require an average column temperature of 63-68 °C within a duration of 12 min, and provide separation resolutions >2 for any two homologues that differ by one methyl group.

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.

Analytical Strategies for Fingerprinting of Antioxidants, Nutritional Substances, and Bioactive Compounds in Foodstuffs Based on High Performance Liquid Chromatography-Mass Spectrometry: An Overview

New technology development and globalisation have led to extreme changes in the agri-food sector in recent years that need an important food supply chain characterisation from plant materials to commercial productions. Many analytical strategies are commonly utilised in the agri-food industry, often using complementary technologies with different purposes. Chromatography on-line coupled to mass spectrometry (MS) is one of the most selective and sensitive analytical methodologies. The purpose of this overview is to present the most recent MS-based techniques applied to food analysis. An entire section is dedicated to the recent applications of high-resolution MS. Covered topics include liquid (LC)– and gas chromatography (GC)–MS analysis of natural bioactive substances, including carbohydrates, flavonoids and related compounds, lipids, phenolic compounds, vitamins, and other different molecules in foodstuffs from the perspectives of food composition, food authenticity and food adulteration. The results represent an important contribution to the utilisation of GC–MS and LC–MS in the field of natural bioactive compound identification and quantification.

A micro passive preconcentrator for micro gas chromatography

We describe a microfabricated passive preconcentrator (μPP) intended for integration into gas chromatographic microsystems (μGC) for analyzing volatile/semi-volatile organic compounds (S/VOC). Devices (8 × 8 mm) were made from a silicon-on-insulator top layer and a glass bottom layer. The top layer has 237 apertures (47 × 47 μm) distributed around the periphery of a circular region (5.2 mm o.d.) through which ambient vapors diffuse at predictable rates. Two internal annular cavities offset from the apertures are packed with ∼800 μg each of commercial carbon adsorbents. Thin-film heaters thermally desorb captured vapors, which are drawn by a pump through a central exit port to a micro injector for analysis with a bench scale GC. The 15 test compounds spanned a vapor pressure range of 0.033 to 1.1 kPa. Effective (diffusional) μPP sampling rates ranged from 0.16 to 0.78 mL min-1 for short-duration exposures to ∼mg m-3 vapor concentrations. Observed and modeled sampling rates generally agreed within 15%. Sampling rates for two representative compounds declined by ≤30% between 0.25 and 24 h of continuous exposure. For one of these, the sampling rate declined by only 8% over a ∼2300-fold concentration range (0.25 h samples). Desorption (transfer) efficiencies were >95% for most compounds (250-275 °C, 60 s, 5 mL min-1). Sampling rates for mixtures matched those for the individual compounds. Dissipating no energy while sampling, additional advantages of this novel device include short- or long-term sampling, high capacity and transfer efficiency for a diverse set of S/VOCs, low transfer flow rate, and a robust fabrication process.

Complete capillary electrophoresis process on a drone: towards a flying micro-lab

Hazardous remote places exist in the world. Why should health or life be risked sending a scientist to the investigation site, as the remote analytical instrumentation exists? Different scientific fields require instruments that could be used on-site (in situ), therefore the purpose of this work was to design a fully automated chemical analysis system small enough to be mountable on a drone. Here we show an autonomous analytical system with sampling capability on a drone. The system is suited for the remote and autonomous analysis of volatile and non-volatile chemicals in the air. The designed system weighs less than 800 g. Data are transmitted wirelessly. Collected substances are separated automatically without the intervention of the operator using the method of capillary zone electrophoresis. The analytes are detected using a miniaturized contactless conductivity detector quantifying them down to less than 1 μM. In this work, we demonstrated sampling and separation of volatile amines (triethylamine and diethylamine) and organic acids (acetic and formic acids), non-volatile inorganic cations (K⁺, Ca²⁺, Na⁺), and protein (bovine serum albumin) in the aerosol state. It was shown that the capillary electrophoretic analysis can be performed on a hovering drone. We anticipate our work to be a starting point for more sophisticated, autonomous complex sample analysis. We believe that our designed instrument will enable the investigation of hazardous places in different research fields.

Bio-inspired gas sensing: boosting performance with sensor optimization guided by "machine learning"

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

Elevating Chemistry Research with a Modern Electronics Toolkit

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

Room-temperature-ionic-liquid coated graphitized carbons for selective preconcentration of polar vapors

Most adsorbent materials used for preconcentrating and thermally desorbing volatile and semi-volatile organic compounds (S/VOCs) in portable or "micro" gas chromatographic (GC/µGC) instruments preferentially capture non-polar or moderately polar compounds relative to more polar compounds. Here, we explore the use of a known trigonal-tripyramidal room-temperature ionic liquid (RTIL) as a surface modifier for the graphitized carbons, Carbopack B (C-B) and Carbopack X (C-X), with the goal of enhancing their capacity and selectivity for polar S/VOCs. Breakthrough tests were performed by challenging tubes packed with ∼2.5 mg of C-B or RTIL-coated C-B (RTIL/C-B) with 13 individual S/VOCs, including several organophosphorus compounds and reference alkyl and aromatic hydrocarbons of comparable vapor pressures, at concentrations ranging from 14 to 130 mg/m³. The 10% breakthrough volume, V_b10, was used as the measure of capacity. For the RTIL/C-B, the V_b10 values of the five organophosphorus vapors tested were consistently ∼2.5 times larger than those for the untreated C-B, and V_b10 values of the four non-polar reference vapors were 11-26 times smaller for the RTIL/C-B than for the untreated C-B. For compounds of similar vapor pressure the capacity ratios for polar vs. non-polar compounds with the RTIL/C-B ranged from 1.8 to 34. Similar results were obtained with C-X and RTIL/C-X on a smaller set of compounds. Tests at 70% relative humidity or with a binary mixture of a polar and non-polar compound had no effect on the capacity of the RTIL/C-B, and there were no changes in V_b10 values after several months of testing that included cycling from 25 to 250 °C. Capacity was strongly correlated with vapor pressure. Attempts to reconcile the selectivity using models based on linear-solvation-energy relationships were only partially successful. Nonetheless, these results indicate that RTIL coating of carbon adsorbents affords a simple, reliable means of rendering them selective for polar S/VOCs.