UV photoionization ion mobility spectrometry: Fundamentals and applications

Improving the Sensitivity and Linear Range of Photoionization Ion Mobility Spectrometry via Confining the Ion Recombination and Space Charge Effects Assisted by Theoretical Modeling

Photoionization (PI) is an efficient ionization source for ion mobility spectrometry (IMS) and mass spectrometry. Its hyphenation with IMS (PI-IMS) has been employed in various on-site analysis scenarios targeting a wide range of compounds. However, the signal intensity and linear dynamic range of PI-IMS at ambient pressure usually do not follow the Beer-Lambert law predictions, and the factors causing that negative deviation remain unclear. In this work, a variable pressure PI-IMS system was developed to examine the ion loss effects from factors like ion recombination and space charge by varying its working pressure from 1 to 0.1 bar. Assisted by theoretical modeling, it was found that ion recombination could contribute up to 90% of signal intensity loss for ambient pressure PI-IMS setups. Lowering the pressure and increasing the electric field in PI-IMS helped suppress the ion recombination process and thus an optimal pressure Poptimal appeared for best signal intensity, despite the decreased net ion number density and the increased space charge effect. A simplified theoretical equation taking ion recombination as the primary ion loss factor was derived to link Poptimal with analyte concentration and electric field in PI-IMS, enabling a swift optimization of the PI-IMS performance. For example, compared to ambient pressure, PI-IMS at a Poptimal of 0.4 bar provided a signal intensity increment of more than 400% for 0.716 ppmv toluene and also expanded the linear dynamic range by more than two times. Revealing factors influencing the PI-IMS response would also benefit the applications of other chemical ionization sources in IMS or mass spectrometry (MS).

Recent reports on the sensing strategy and the On-site detection of illegal drugs

In this review, works on the on-site detection of illegal drugs in recent years are summarised and discussed, most of which were published within the past five years. The detection methods are categorised as colourimetric, fluorescence, Raman spectrometry, ion mobility spectrometry, electrochemistry, and mass spectrometry. Also, strategies that are possibly suitable for on-site detection and the actual instrumentation to be used in the field are listed.

Recent development and trends in the detection of peroxide-based explosives

Peroxide-based explosives (PBEs) are increasingly common in criminal and terrorist activity due to their easy synthesis and high explosive power. The rise in terrorist attacks involving PBEs has heightened the importance of detecting trace amounts of explosive residue or vapors. This paper aims to provide a review on the developments of techniques and instruments for detecting PBEs over the past ten years, specifically discussing advancements in ion mobility spectrometry, ambient mass spectrometry, fluorescence techniques, colorimetric methods, and electrochemical methods. We provide examples to illustrate their evolution and focus on new strategies for improving detection performance, specifically in terms of sensitivity, selectivity, high-throughput, and wide explosives coverage. Finally, we discuss future prospects for PBE detection. It is hoped this treatment will serve as a guide to the novitiate and as aid memoire to the researchers.

Easy to assemble dielectric barrier discharge plasma ionization source based on printed circuit boards

Here, we present a new and an easy to assemble dielectric barrier discharge plasma ionization source based on printed circuit boards with two parallel isolated electrodes for generating a plasma inside an inert fused silica capillary. For demonstration, this plasma source is coupled to an ion mobility spectrometer. With two different sample gas feeds the analytes can either pass through the plasma or bypass the plasma before entering the reaction region of the ion mobility spectrometer, allowing for different ionization pathways, e.g. electron impact ionization, ionization by excited species, e.g. helium metastables, or chemical ionization via reactant ions generated inside or downstream of the plasma. The plasma source, in particular, the electrode geometry and the capillary diameter were designed with the help of electric field simulations. A rectangular electrode with a height of at least twice the outer diameter of the capillary turned out to be ideal, in both the simulation and the experiment. Furthermore, a simple control electronics has been developed, which can be easily applied to other plasma sources. With the plasma source presented here, detection limits in the mid ppt_v range have been reached.

Deconvolution of overlapping peaks in ion mobility spectrometry based on a multiobjective dynamic teaching-learning-based optimization

RATIONALE

Because of its powerful analytical ability, ion mobility spectrometry (IMS) plays an important role in the field of mass spectrometry. However, one of the main defects of IMS is its low structural resolution, which leads to the phenomenon of peak overlap in the analysis of compounds with similar mass charge ratio.

METHODS

A multiobjective dynamic teaching-learning-based optimization (MDTLBO) method was proposed to separate IMS overlapping peaks. This method prevents local optimization and identifies peak model coefficients efficiently. In addition, the position information of particles largely reflects the half-peak width of IMS, which makes single peaks difficult to appear and coefficient identification easier.

RESULTS

The performance comparison of MDTLBO with other deconvolution methods (genetic algorithm, improved particle swarm optimization algorithm, and dynamic inertia weight particle swarm optimization algorithm) shows that the maximum deconvolution error of MDTLBO is only 0.7%, which is much lower than that for the other three methods. In addition, robustness is a performance index that reflects the advantages and disadvantages of the algorithm.

CONCLUSION

MBTLBO is more robust than other algorithms for separating overlapping peaks. The algorithm can separate the heavily overlapped mobility peaks, produce better analysis results, and improve the resolution of IMS.

Volatolomic urinary profile analysis for diagnosis of the early stage of lung cancer

Nowadays in clinical practice there is a pressing need for potential biomarkers that can identify lung cancer at early stage before becoming symptomatic or detectable by conventional means. Several researchers have independently pointed out that the volatile organic compounds (VOCs) profile can be considered as a lung cancer fingerprint useful for diagnosis. In particular, 16% of volatiles contributing to the human volatilome are found in urine, which is therefore an ideal sample medium. Its analysis through non-invasive, relatively low-cost and straightforward techniques could offer great potential for the early diagnosis of lung cancer. In this study, urinary VOCs were analysed with a gas chromatography-ion mobility spectrometer (GC-IMS) and an electronic nose (e-nose) made by a matrix of twelve quartz microbalances (QMBs) complemented by a photoionization detector (PID). This clinical prospective study involved 127 individuals, divided into two groups: 46 with lung cancer stage I-II-III confirmed by computerized tomography (CT) or positron emission tomography-(PET) imaging techniques and histology (biopsy), and 81 healthy controls. Both instruments provided a multivariate signal which, after being analysed by a machine learning algorithm, identified eight VOCs that could distinguish lung cancer patients from healthy ones. The eight VOCs are 2-pentanone, 2-hexenal, 2-hexen-1-ol, hept-4-en-2-ol, 2-heptanone, 3-octen-2-one, 4-methylpentanol, 4-methyl-octane. Results show that GC-IMS identifies lung cancer with respect to the control group with a diagnostic accuracy of 88%. Sensitivity resulted as being 85%, and specificity was 90% - Area Under the Receiver Operating Characteristics (AUROC): 0.91. The contribution made by the e-nose was also important, even though the results were slightly less sensitive with an accuracy of 71.6%. Moreover, of the eight VOCs identified as potential biomarkers, five VOCs had a high sensitivity (p≤ 0.06) for early stage (stage I) lung cancer.

High voltage pulser for ion shutters in ion mobility spectrometry based on an optocoupler

A novel high voltage pulser for an ion shutter used in drift-tube ion-mobility spectrometers is described. The simple design suitable for the in-house construction of these spectrometers relies on a special optocoupler to isolate the triggering circuitry from the high voltage at the ion shutter. The device was tested with an electrospray-ionization ion-mobility device with a 10 cm drift tube operated at 4 kV into which a standard test mixture of four tetraalkylamines was injected with a negative going gating pulse of about 50 V on top of 4 kV. A fall time of 15.7 µs and a rise time of 2.0 µs were determined for the pulse, which was adequate for the required injection pulse width of 450 µs. Resolving powers between 61 and 81 were determined for the four quaternary amines, which were found to be comparable to the performance obtained with a previously reported pulser circuitry of a different design used as a reference.

Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis

Ion mobility analysis is a well-known analytical technique for identifying gas-phase compounds in fast-response gas-monitoring systems. However, the conventional plasma discharge system is bulky, operates at a high temperature, and inappropriate for volatile organic compounds (VOCs) concentration detection. Therefore, we report a machine learning (ML)-enhanced ion mobility analyzer with a triboelectric-based ionizer, which offers good ion mobility selectivity and VOC recognition ability with a small-sized device and non-strict operating environment. Based on the charge accumulation mechanism, a multi-switched manipulation triboelectric nanogenerator (SM-TENG) can provide a direct current (DC) bias at the order of a few hundred, which can be further leveraged as the power source to obtain a unique and repeatable discharge characteristic of different VOCs, and their mixtures, with a special tip-plate electrode configuration. Aiming to tackle the grand challenge in the detection of multiple VOCs, the ML-enhanced ion mobility analysis method was successfully demonstrated by extracting specific features automatically from ion mobility spectrometry data with ML algorithms, which significantly enhance the detection ability of the SM-TENG based VOC analyzer, showing a portable real-time VOC monitoring solution with rapid response and low power consumption for future internet of things based environmental monitoring applications.

Rapid and highly sensitive measurement of trimethylamine in seawater using dynamic purge-release and dopant-assisted atmospheric pressure photoionization mass spectrometry

Trimethylamine (TMA) is ubiquitous in the marine systems and may affect atmospheric chemistry as a precursor and strong stabilizer of atmospheric secondary aerosol, influencing cloud formation. Rapid and accurate measurement of the concentration of TMA in seawater is challenging due to their polarity, aqueous solubility, volatility and existence at low concentrations in marine environments. In this study, a dopant-assisted atmospheric pressure photoionization time-of-flight mass spectrometry (DA-APPI-TOFMS) coupled with a dynamic purge-release method was developed for rapid and sensitive analysis of TMA in seawater. A novel three-zones ionization source has been developed for improving the ionization efficiency of analyte molecules and minimizing the influence of high-humidity of the sample gas, which allowed direct analysis of high-humidity (RH> 90%) gas samples from microbubble purging process by the mass spectrometer. At atmospheric pressure, the three-zones ionization source allows the use of high-speed purge gas to quickly purge all organic amines dissolved in the water into the gas phase, ensuring quantitative accuracy. The limit of quantification (LOQ) for TMA down to 0.1 μg L^-1 was obtained in less than 2 min by consuming only 2 mL seawater sample. This method was applied for the determination of the concentrations of TMA in the coastal seawater to validate its practicability and reliability for analysis of trace amines in marine environments.

Accurate and rapid discrimination of cigarette and household decoration material ash residues by negative chemical ionization TOFMS via acid-enhanced evaporation

The detection and identification of cigarette ash in fire debris can be meaningful in fire investigations caused by burning cigarettes. In this work, a novel analytical method based on negative chemical ionization time-of-flight mass spectrometry (NCI/TOFMS) combined with a phosphoric-acid-enhanced evaporation strategy has been developed for the discrimination of cigarette ash samples (CAs) and common household decoration material ash samples (CHDMAs). A series of characteristic ions representing the acidified products HNCO and formic acid in the CAs were achieved, whose signal responses were enhanced with the help of mechanical agitation operation. To account for both the signal responses of the characteristic ions and acid corrosion of the ion source, the dynamic-purge gas was chosen to be 200 mL/min. The whole time for analysis was only 5 min, which is suitable for high-throughput measurements of large quantities of fire debris. As a result, a preliminary discrimination was achieved between the CAs and CHDMAs by virtue of the chemometric tool of principal components analysis (PCA) based on intensity differences of the characteristic ions. The results are encouraging and highlight the potential of NCI/TOFMS without complicated sample preparation steps for the accurate and high-throughput identification of cigarette ash on substrates in fire debris.