Ion Mobility Spectra Research Articles

Detection of Chemically Hazardous Substances by Ion Mobility Spectrometry

A comparison of chemical detectors based on ion mobility spectrometry used by rapid response services for the rapid detection and identification of a wide range of chemically hazardous substances has been carried out. The physical foundations of the registration method, the method of mathematical processing of spectra and determination of the ionic mobility of substances are presented. A procedure for the preparation of test samples of vapors of volatile organic compounds in a wide range of concentrations has been developed. To identify the compounds, domestic devices were used – the Kerber-T ion drift detector and the Segment stationary automatic gas detector. Their comparison in sensitivity and detection range in the identification of compounds was carried out. The research was conducted on a set of substances standardized to ensure safety in terrorist attacks. As a result of the work, ion mobility spectra for bromocyanum, carbon disulfide, and chloroacetone were obtained. The values of ionic mobility were determined, the dependences of the spectra of these compounds on the concentration in the air were investigated, as well as the limits of detection of substances. Possible mechanisms for the formation of the observed ion mobility spectra are proposed in accordance with the ionization characteristics of bromocyanate, carbon disulfide, and chloroacetone. Schemes of possible formation of monomeric and dimeric ions of compounds are shown. The generalized results of experimental studies, the peculiarities of the identification of compounds, taking into account the type of spectra, concentrations of substances and measurement conditions, are obtained.

Combining Fourier Transform Ion Mobility with Charge Detection Mass Spectrometry for the Analysis of Multimeric Protein Complexes.

Charge detection mass spectrometry (CDMS) allows direct mass measurement of heterogeneous samples by simultaneously determining the charge state and the mass-to-charge ratio (m/z) of individual ions, unlike conventional MS methods that use large ensembles of ions. CDMS typically requires long acquisition times and the collection of thousands of spectra, each containing tens to hundreds of ions, to generate sufficient ion statistics, making it difficult to interface with the time scales of online separation techniques such as ion mobility. Here, we demonstrate the application of Fourier transform multiplexing and drift tube ion mobility joined with Orbitrap-based CDMS for the analysis of multimeric protein complexes. Stepped frequency modulation was utilized to enable unambiguous frequency assignment during mobility sweeps and allow spectral averaging, which improves the accuracy and signal-to-noise of ion mobility spectra and CDMS measurements. Fourier transformation of the signal reveals the arrival times and collision cross sections of ions while simultaneously collecting charge information for thousands of individual ions. Combining Fourier transform multiplexing ion mobility and CDMS provides insight into each ion's size and mass while showcasing a potential solution to the duty cycle mismatch of online separation techniques in the single ion regime.

The Ion Formation and Quantitative Response of Isoprene, Monoterpenes and Terpenoids in Ion Mobility Spectrometry with Atmospheric-Pressure Chemical Ionization as a Function of Temperature.

Ion mobility spectrometry is successfully used as a sensor technology for different applications. A feature of this method is that characteristic ion mobility spectra are obtained for each measurement rather than a sum signal. The spectra result from the different drift velocities of ions in a drift tube at atmospheric pressure. In this study, we investigated the ion formation processes and the quantitative response of isoprene, monoterpenes and monoterpenoids as a function of the temperature of the spectrometer using a tritium ionization source. These substances are important target analytes in atmospheric monitoring and in the analysis of essential oils in different matrices. A drift tube temperature above 120 °C permitted the most sensitive detection of isoprene and monoterpenes, while 80 °C was sufficient for the sensitive detection of most terpenoids. Dimer ions were formed for isoprene over the whole temperature range. The ionization processes of monoterpenes and terpenoids were strongly influenced by the temperature. At temperatures of 40 °C, adduct ions were formed in addition to MH+ ions for monoterpenes. Enhanced temperatures provided a single peak with the same drift time for all monoterpenes. Structural differences influenced the ion formation of terpenoids, and much more complex spectra were obtained. The nature of the product ions changed depending on the temperature.

Analysis of the ion mobility spectra of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol

Objectives. To determine the ion mobilities of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol; the structure of ions corresponding to characteristic signals; the detection limits of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol with the Kerber-T ion drift detector and the Segment automatic stationary gas detector.Methods. Ion mobility spectrometry was used in order to determine the ion mobilities and detect analytes. The enthalpies of reactions of ion formation were calculated using the ORCA 4.1.1 software by means of the B3LYP density functional method with the 6-31G(d,p) basis set.Results. The ion mobilities of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol were determined. A method for recording ion mobility spectra and their mathematical processing was developed. The dependencies of the change in ion mobility spectra on the analyte concentration were also studied. Possible mechanisms were proposed for the formation of the ion mobility spectra observed, in accordance with the ionization features of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol. The enthalpies of ion formation were calculated. The ionization schemes of the compounds were shown. The generalized results of experimental studies were presented, as were the features of compound identification taking into account the structure of the spectra, the concentrations of substances, and the detection conditions.Conclusions. Characteristic signals of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol were identified. All studied hazardous substances can be detected with an ion mobility spectrometer at concentrations at the ppm level. The following detection limits of the substances were determined with the Segment gas detector: chloroacetophenone, 245 mg/m3; tris(2-chloroethyl)amine, 0.01 mg/m3; and methanethiol, 0.8 mg/m3.

Thermal decomposition and atmospheric pressure chemical ionization of alanine using ion mobility spectrometry and computational study

Thermal decomposition and atmospheric pressure chemical ionization of alanine using ion mobility spectrometry and computational study

Time-Resolved Ion Mobility Mass Spectrometry to Solve Conformational Changes in a Cryptochrome.

Many biological mechanisms rely on the precise control of conformational changes in proteins. Understanding such dynamic processes requires methods for determining structures and their temporal evolution. In this study, we introduce a novel approach to time-resolved ion mobility mass spectrometry. We validated the method on a simple photoreceptor model and applied it to a more complex system, the animal-like cryptochrome from Chlamydomonas reinhardtii (CraCRY), to determine the role of specific amino acids affecting the conformational dynamics as reaction to blue light activation. In our setup, using a high-power LED mounted in the source region of an ion mobility mass spectrometer, we allow a time-resolved evaluation of mass and ion mobility spectra. Cryptochromes like CraCRY are a widespread type of blue light photoreceptors and mediate various light-triggered biological functions upon excitation of their inbuilt flavin chromophore. Another hallmark of cryptochromes is their flexible carboxy-terminal extension (CTE), whose structure and function as well as the details of its interaction with the photolyase homology region are not yet fully understood and differ among different cryptochromes types. Here, we addressed the highly conserved C-terminal domain of CraCRY, to study the effects of single mutations on the structural transition of the C-terminal helix α22 and the attached CTE upon lit-state formation. We show that D321, the putative proton acceptor of the terminal proton-coupled electron transfer event from Y373, is essential for triggering the large-scale conformational changes of helix α22 and the CTE in the lit state, while D323 influences the timing.

Impact of Source Conditions on Collision Cross Section Determination by Trapped Ion Mobility Spectrometry.

Collision cross section (CCS) values determined in ion mobility-mass spectrometry (IM-MS) are increasingly employed as additional descriptors in metabolomics studies. CCS values must therefore be reproducible and the causes of deviations must be carefully known and controlled. Here, we analyzed lipid standards by trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) to evaluate the effects of solvent and flow rate in flow injection analysis (FIA), as well as electrospray source parameters including nebulizer gas pressure, drying gas flow rate, and temperature, on the ion mobility and CCS values. The stability of ion mobility experiments was studied over 10 h, which established the need for a delay-time of 20 min to stabilize source parameters (mostly pressure and temperature). Modifications of electrospray source parameters induced shifts of ion mobility peaks and even the occurrence of an additional peak in the ion mobility spectra. This behavior could be essentially explained by ion-solvent cluster formation. Changes in source parameters were also found to impact CCS value measurements, resulting in deviations up to 0.8%. However, internal calibration with the Tune Mix calibrant reduced the CCS deviations to 0.1%. Thus, optimization of source parameters is essential to achieve a good desolvation of lipid ions and avoid misinterpretation of peaks in ion mobility spectra due to solvent effects. This work highlights the importance of internal calibration to ensure interoperable CCS values, usable in metabolomics annotation.

Elucidating Structures of Protein Complexes by Collision-Induced Dissociation at Elevated Gas Pressures.

Ion activation methods carried out at gas pressures compatible with ion mobility separations are not yet widely established. This limits the analytical utility of emerging tandem-ion mobility spectrometers that conduct multiple ion mobility separations in series. The present work investigates the applicability of collision-induced dissociation (CID) at 1 to 3 mbar in a tandem-trapped ion mobility spectrometer (tandem-TIMS) to study the architecture of protein complexes. We show that CID of the homotetrameric protein complexes streptavidin (53 kDa), neutravidin (60 kDa), and concanavalin A (110 kDa) provides access to all subunits of the investigated protein complexes, including structurally informative dimers. We report on an "atypical" dissociation pathway, which for concanavalin A proceeds via symmetric partitioning of the precursor charges and produces dimers with the same charge states that were previously reported from surface induced dissociation. Our data suggest a correlation between the formation of subunits by CID in tandem-TIMS/MS, their binding strengths in the native tetramer structures, and the applied activation voltage. Ion mobility spectra of in situ-generated subunits reveal a marked structural heterogeneity inconsistent with annealing into their most stable gas phase structures. Structural transitions are observed for in situ-generated subunits that resemble the transitions reported from collision-induced unfolding of natively folded proteins. These observations indicate that some aspects of the native precursor structure is preserved in the subunits generated from disassembly of the precursor complex. We rationalize our observations by an approximately 100-fold shorter activation time scale in comparison to traditional CID in a collision cell. Finally, the approach discussed here to conduct CID at elevated pressures appears generally applicable also for other types of tandem-ion mobility spectrometers.

Overlapping peak separation algorithm for ion mobility spectra based on multistrategy JAYA.

In the field of separation science, ion mobility spectrometry (IMS) plays an important role as an analytical tool. However, the lack of sufficient structural resolution is a common problem in qualitative and quantitative analysis using IMS. A method is needed to solve the problem of overlapping peaks caused by insufficient resolution. The method uses multiple strategies to more effectively use population information to balance exploration and exploitation capabilities, prevent local optimization, accurately resolve overlapping peaks, quickly obtain optimal spectral peak model coefficients, and accurately identify compounds. Multistrategy JAYA algorithm's (MSJAYA) performance is compared with improved particle swarm optimization (IPSO), dynamic inertia weight particle swarm optimization (DIWPSO), and multiobjective dynamic teaching-learning-based optimization (MDTLBO). The analysis shows that MSJAYA's maximum separation error is within 0.6%, a level of accuracy not guaranteed by the other algorithms. In addition, the separation error fluctuates within a much smaller range, demonstrating MSJAYA's superior robustness. Compared with other overlapping peak separation algorithms, MSJAYA is more applicable because no special parameters are used. The method allows fast deconvolution analysis of strong overlapping peaks with multiple components, which greatly improves the resolution of IMS.

Complementary methods for structural assignment of isomeric candidate structures in non-target liquid chromatography ion mobility high-resolution mass spectrometric analysis

Non-target screening with LC/IMS/HRMS is increasingly employed for detecting and identifying the structure of potentially hazardous chemicals in the environment and food. Structural assignment relies on a combination of multidimensional instrumental methods and computational methods. The candidate structures are often isomeric, and unfortunately, assigning the correct structure among a number of isomeric candidate structures still is a key challenge both instrumentally and computationally. While practicing non-target screening, it is usually impossible to evaluate separately the limitations arising from (1) the inability of LC/IMS/HRMS to resolve the isomeric candidate structures and (2) the uncertainty of in silico methods in predicting the analytical information of isomeric candidate structures due to the lack of analytical standards for all candidate structures. Here we evaluate the feasibility of structural assignment of isomeric candidate structures based on in silico–predicted retention time and database collision cross-section (CCS) values as well as based on matching the empirical analytical properties of the detected feature with those of the analytical standards. For this, we investigated 14 candidate structures corresponding to five features detected with LC/HRMS in a spiked surface water sample. Considering the predicted retention times and database CCS values with the accompanying uncertainty, only one of the isomeric candidate structures could be deemed as unlikely; therefore, the annotation of the LC/IMS/HRMS features remained ambiguous. To further investigate if unequivocal annotation is possible via analytical standards, the reversed-phase LC retention times and low- and high-resolution ion mobility spectrometry separation, as well as high-resolution MS2 spectra of analytical standards were studied. Reversed-phase LC separated the highest number of candidate structures while low-resolution ion mobility and high-resolution MS2 spectra provided little means for pinpointing the correct structure among the isomeric candidate structures even if analytical standards were available for comparison. Furthermore, the question arises which prediction accuracy is required from the in silico methods to par the analytical separation. Based on the experimental data of the isomeric candidate structures studied here and previously published in the literature (516 retention time and 569 CCS values), we estimate that to reduce the candidate list by 95% of the structures, the confidence interval of the predicted retention times would need to decrease to below 0.05 min for a 15-min gradient while that of CCS values would need to decrease to 0.15%. Hereby, we set a clear goal to the in silico methods for retention time and CCS prediction.Graphical abstract

Simultaneous Ion Swarm Profiling and Ion Mobility Measurement using Ion Cameras.

When operated as a standalone analytical device, traditional drift tube ion mobility spectrometry (IMS) experiments require high-speed, high-gain transimpedance amplifiers to record ion separations with sufficient resolution. Recent developments in the fabrication of charge-sensitive cameras (e.g., IonCCD) have provided key insights for ion beam profiling in mass spectrometry and even served as detectors for miniature magnetic sector instruments. Unfortunately, these platforms have comparatively slow integration times (multiple ms), which largely precludes their use for recording ion mobility spectra, where sampling rates into the 10s of kHz are generally required. As a result, experiments that simultaneously probe the longitudinal and transverse mobility of an injected species using an array detector have not been reported. To address this duty-cycle mismatch, a frequency encoding strategy is used to evaluate ion swarm characteristics, while directly capturing ion mobility information using the Fourier transform. This apparatus described allows the ion beam to be profiled over the full course of the experiment and establishes the foundation to examine axial and longitudinal drift velocities simultaneously.

Validation of Field-Dependent Ion-Solvent Cluster Modeling via Direct Measurement of Cluster Size Distributions.

Ion mobility spectrometry is widely used in analytical chemistry, either as a stand-alone technique or coupled to mass spectrometry. Ions in the gas phase tend to form loosely bound clusters with surrounding solvent vapors, artificially increasing the collisional cross section and the mass of the ion. This, in turn, affects ion mobility and influences separation. Further, ion-solvent clusters play an important role in most ionization mechanisms occurring in the gas phase. Consequently, a deeper understanding of ion-solvent cluster association and dissociation processes is desirable to guide experimental design and interpretation. A few computational models exist, which aim to describe the amount of clustering as a function of the reduced electric field strength, bath gas pressure and temperature, and the chemical species probed. It is especially challenging to model ion mobility under high reduced electrical field strengths due to the nonthermal conditions created by the field. In this work, we aim to validate a recently proposed first-principles model by comparing its predictions with direct measurements of cluster size distributions over a range of 20-120 Td as observed using a High Kinetic Energy Ion Mobility Spectrometer coupled to a mass spectrometer (HiKE-IMS-MS). By studying H+(H2O)n, [MeOH + H + n(H2O)]+, [ACE + H + n(H2O)]+, and [PhNH2 + H + n(H2O)]+ as test systems, we find very good agreement between model and experiment, supporting the validity of the computational workflow. Further, the detailed information gained from the modeling yields important insights into the cluster dynamics within the HiKE-IMS, allowing for better interpretation of the measured ion mobility spectra.

Exploratory data fusion of untargeted multimodal LC-HRMS with annotation by LCMS-TOF-ion mobility: White wine case study.

Applied sciences have increased focus on omics studies which merge data science with analytical tools. These studies often result in large amounts of data produced and the objective is to generate meaningful interpretations from them. This can sometimes mean combining and integrating different datasets through data fusion techniques. The most strategic course of action when dealing with products of unknown profile is to use exploratory approaches. For omics, this means using untargeted analytical methods and exploratory data analysis techniques. The current study aimed to perform data fusion on untargeted multimodal (negative and positive mode) liquid chromatography-high-resolution mass spectrometry data using multiple factor analysis. The data fusion results were interpreted using agglomerative hierarchical clustering on biplot projections. The study reduced the thousands of spectral signals processed to less than a hundred features (a primary parameter combination of retention time and mass-to-charge ratios, RT_m/z). The correlations between cluster members (samples and features from) were calculated and the top 10% highly correlated features were identified for each cluster. These features were then tentatively identified using secondary parameters (drift time, ion mobility constant and collision cross-section values) from the ion mobility spectra. These ion mobility (secondary) parameters can be used for future studies in wine chemical analysis and added to the growing list of annotated chemical signals in applied sciences.

Non-Contact, Continuous Sampling of Porous Surfaces for the Detection of Particulate and Adsorbed Organic Contaminations by Low-Temperature Plasma Coupled to Ion Mobility Spectrometer.

Chemical analysis of hazardous surface contaminations, such as hazardous substances, explosives or illicit drugs, is an essential task in security, environmental and safety applications. This task is mostly based on the collection of particles with swabs, followed by thermal desorption into a vapor analyzer, usually a detector based on ion mobility spectrometry (IMS). While this methodology is well established for several civil applications, such as border control, it is still not efficient enough for various conditions, as in sampling rough and porous surfaces. Additionally, the process of thermal desorption is energetically inefficient, requires bulky hardware and introduces device contamination memory effects. Low-temperature plasma (LTP) has been demonstrated as an ionization and desorption source for sample preparation-free analysis, mostly at the inlet of a mass spectrometer analyzer, and in rare cases in conjunction with an ion mobility spectrometer. Herein, we demonstrate, for the first time, the operation of a simple, low cost, home-built LTP apparatus for desorbing non-volatile analytes from various porous surfaces into the inlet of a handheld IMS vapor analyzer. We show ion mobility spectra that originate from operating the LTP jet on porous surfaces such as asphalt and shoes, contaminated with model amine-containing organic compounds. The spectra are in good correlation with spectra measured for thermally desorbed species. We verify through LC-MS analysis of the collected vapors that the sampled species are not fragmented, and can thus be identified by commercial IMS detectors.

Mechanism of formation and ion mobility separation of protomers and deprotomers of diaminobenzoic acids and aminophthalic acids.

Aminobenzoic acids are well-established candidates for understanding the formation of isomeric ions in positive mode electrospray ionization as they yield both N- and O-protomers (prototropic isomers) at the amine and carbonyl sites, respectively. In the present work, a combination of ion mobility-mass spectrometry and density functional theory calculations to determine the protonation and deprotonation behaviour of four diamino benzoic acid and four aminophthalic acid isomers is presented. The additional COOH group on the ring of aminophthalic acids provides experimental evidence regarding the mechanism of intramolecular NH3+ → O proton transfer, which has been the subject of debate in recent years. To determine the proton acceptor O atom, ion mobility spectra of the fragments of protomers were used as a new method for the confidential assignment of the O-protomer structure, confirming only short-distance intramolecular NH3+ → O proton transfer. Additionally, the substitution pattern both influences the basicity of the protonation sites and enables these molecules to form internal hydrogen bonds with the protonated or deprotonated sites. The formation of the hydrogen bonds in the deprotonated aminophthalic acids changed the charge distribution and subsequently their ion mobility-derived collision cross sections in nitrogen (CCSN2) leading to separation of the four isomers studied. Finally, an interesting effect of the substitution pattern was observed as a synergistic electron-donating effect of the amine groups of 3,5-diaminobenzoic acid on enhancing the basicity of the carbon atom C2 of the ring and previously unreported formation of a C-protomer within aminobenzoic acid systems.

A Cleavable Self-Inclusion Conjugate with Enhanced Biocompatibility and Antitumor Bioactivity

A Cleavable Self-Inclusion Conjugate with Enhanced Biocompatibility and Antitumor Bioactivity

Two-step particle swarm optimization algorithm for effective deconvolution and resolution enhancement of various overlapping peaks.

The existing particle swarm optimization (PSO) algorithms are only effective in deconvoluting the overlapping peaks in ion mobility spectra with fewer than four component peaks, which limits the applicability of these algorithms. A high-performance two-step particle swarm optimization (TSPSO) algorithm was developed. Compared to the existing PSO algorithms, TSPSO can narrow the search ranges of all coefficients for the overlapping peaks through Gaussian model calculation, and thus can deconvolute various overlapping peaks with high accuracy, even for 30-component overlapping peaks. In addition, the TSPSO could be further applied to enhance the resolution of the spectra by narrowing the peak widths after the peak deconvolution. Simulated overlapping peaks were first used to evaluate the performance of TSPSO as compared to the dynamic inertia weight particle swarm optimization (DIWPSO) algorithm. The results showed that the profiles of the peaks deconvoluted by using TSPSO were more consistent with the original ones. The fitness values and the standard deviations of the fitness values from TSPSO were also at least an order of magnitude less than those from DIWPSO. By applying TSPSO, the overlapping peaks from both mass spectrometry (MS) and field asymmetric waveform ion mobility spectrometry (FAIMS) spectra can also be well deconvoluted. In addition, the resolutions of the MS and FAIMS spectra can be effectively enhanced after peak deconvolution. The enhanced spectra matched excellently with the experimental ones acquired at high-resolution modes. The experiment results convincingly demonstrate that the TSPSO algorithm is capable of both deconvoluting complex overlapping peaks and enhancing the spectrum resolution with high accuracy.

Protomer Formation Can Aid the Structural Identification of Caffeine Metabolites.

The structural annotation of isomeric metabolites remains a key challenge in untargeted electrospray ionization/high-resolution mass spectrometry (ESI/HRMS) metabolomic analysis. Many metabolites are polyfunctional compounds that may form protomers in electrospray ionization sources and therefore yield multiple peaks in ion mobility spectra. Protomer formation is strongly structure-specific. Here, we explore the possibility of using protomer formation for structural elucidation in metabolomics on the example of caffeine, its eight metabolites, and structurally related compounds. It is observed that two-thirds of the studied compounds formed high- and low-mobility species in high-resolution ion mobility. Structures in which proton hopping was hindered by a methyl group at the purine ring nitrogen (position 3) yielded structure-indicative fragments with collision-induced dissociation (CID) for high- and low-mobility ions. For compounds where such a methyl group was not present, a gas-phase equilibrium could be observed for tautomeric species with two-dimensional ion mobility. We show that the protomer formation and the gas-phase properties of the protomers can be related to the structure of caffeine metabolites and facilitate the identification of the structural isomers.

Machine learning approaches over ion mobility spectra for the discrimination of ignitable liquids residues from interfering substrates

• Fire debris including petroleum-derived substrates was analyzed by HS-GC-IMS. • The HCA analysis revealed a classification trend according to the type of ILs and substrate used. • SVM and RF models detect the presence of ILs in fire debris with 100% accuracy. • The RF model achieved the best accuracy in discriminating the type of ILRs. In arson fires, ignitable liquids (ILs) are frequently used to start combustion. For this reason, detecting IL residues (ILRs) at the fire scene is a key factor in fire investigation to determine whether a crime has been committed as well as to establish the modus operandi of the perpetrator. In the present study, the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) for the detection of ILRs in fire debris from complex matrices in combination with machine learning (ML) tools is proposed as an alternative to the traditional method, based on gas chromatography–mass spectrometry (GC-MS), described by the ASTM E1618 standard method. For this purpose, petroleum-derived substrates (vinyl, nylon, and polyester) and natural substrates (cotton, cork and linoleum) burned alone and with different ILs (gasoline, diesel, ethanol and charcoal starter with kerosene) were used. In addition, samples were taken at different times (0, 1, 6, 12, 24 and 48 h) after the fire was finished. The ion mobility sum spectrum (IMSS) of each sample was obtained and different ML algorithms were applied. The first derivative was performed at the IMSS, as well as a Savitzky-Golay filter. Hierarchical cluster analysis (HCA) revealed a clustering trend as a function of substrate and ILs used, where the studied sampling times did not affect the resulting clusters. The classification models for the detection of the presence of ILRs have high performance with an accuracy of 100% for support vector machines (SVM) and random forest model (RF), followed by linear discriminant analysis (LDA) with an accuracy of 86.67%. When discriminating the type of ILs used, the RF model obtained an accuracy of 100%, followed by the LDA with 97.22% and finally the SVM model with an accuracy of 93.06%. In addition, a simple web application has been developed where the trained models can be used, so any researcher can apply the method to detect ILRs in fire debris.

Fourier Deconvolution Ion Mobility Spectrometry.

Multiplexing the ion packet injection with advanced signal processing is an effective method to improve both the ion throughput and signal-to-noise ratio for ion mobility spectrometry. Generally used multiplexing methods include Hadamard transform ion mobility spectrometry (HT-IMS), Fourier transform ion mobility spectrometry (FT-IMS), and correlation ion mobility spectrometry (C-IMS). However, HT-IMS sometimes suffer from false peaks and further processing is needed, FT-IMS generally requires longer spectra acquisition time than the traditional signal averaging method, and C-IMS also demonstrated drawbacks such as spectra baseline distortions when using traditional on-off binary gating switches. To improve the performance of multiplexing ion mobility spectrometry, this study investigates the Fourier deconvolution to increase the resolving power and signal-to-noise ratio at the same time. This approach modulates the ion gate with a linear square wave chirp sequence and synchronizes the data acquisition and ion gate modulation and then reconstructs the ion mobility spectra based on convolution theorems. The equivalent ion injection period is decreased to microseconds scale with the signal-to-noise ratio improved by up to 13 times on average, and the resolving power is improved by up to 50% compared with traditional signal averaging methods without hardware modifications.