AIMC Topic: Ion Mobility Spectrometry

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Application and integration of deep learning in FAIMS for identifying acetone concentration.

Analytical biochemistry
In practical applications, analytical instruments are used for both qualitative and quantitative analysis. However, for high-field asymmetric-waveform ion mobility spectrometry (FAIMS), most studies to date have been focused on the qualitative analys...

Identification of Nonvolatile Migrates from Food Contact Materials Using Ion Mobility-High-Resolution Mass Spectrometry and in Silico Prediction Tools.

Journal of agricultural and food chemistry
The identification of migrates from food contact materials (FCMs) is challenging due to the complex matrices and limited availability of commercial standards. The use of machine-learning-based prediction tools can help in the identification of such c...

High-Throughput Measurement and Machine Learning-Based Prediction of Collision Cross Sections for Drugs and Drug Metabolites.

Journal of the American Society for Mass Spectrometry
Drug metabolite identification is a bottleneck of drug metabolism studies due to the need for time-consuming chromatographic separation and structural confirmation. Ion mobility-mass spectrometry (IM-MS), on the other hand, separates analytes on a ra...

Collision Cross Section Calculations to Aid Metabolite Annotation.

Journal of the American Society for Mass Spectrometry
The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low o...

Prediction of Collision Cross Section Values: Application to Non-Intentionally Added Substance Identification in Food Contact Materials.

Journal of agricultural and food chemistry
The synthetic chemicals in food contact materials can migrate into food and endanger human health. In this study, the traveling wave collision cross section in nitrogen values of more than 400 chemicals in food contact materials were experimentally d...

Identification of Specific Substances in the FAIMS Spectra of Complex Mixtures Using Deep Learning.

Sensors (Basel, Switzerland)
High-field asymmetric ion mobility spectrometry (FAIMS) spectra of single chemicals are easy to interpret but identifying specific chemicals within complex mixtures is difficult. This paper demonstrates that the FAIMS system can detect specific chemi...

QSSR Modeling of Bacillus Subtilis Lipase A Peptide Collision Cross-Sections in Ion Mobility Spectrometry: Local Descriptor Versus Global Descriptor.

The protein journal
To investigate the structure-dependent peptide mobility behavior in ion mobility spectrometry (IMS), quantitative structure-spectrum relationship (QSSR) is systematically modeled and predicted for the collision cross section Ω values of totally 162 s...

Gas-phase volatilomic approaches for quality control of brewing hops based on simultaneous GC-MS-IMS and machine learning.

Analytical and bioanalytical chemistry
For the first time, a prototype HS-GC-MS-IMS dual-detection system is presented for the analysis of volatile organic compounds (VOCs) in fields of quality control of brewing hop. With a soft ionization and drift time-based ion separation in IMS and a...

Breaking Down Structural Diversity for Comprehensive Prediction of Ion-Neutral Collision Cross Sections.

Analytical chemistry
Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or drug metabolite identification. Ion mobility-mass spectrometry (IM-MS) provides rapid two-dimensional separation of ions based on their mobility throu...

Predicting Breast Cancer by Paper Spray Ion Mobility Spectrometry Mass Spectrometry and Machine Learning.

Analytical chemistry
Paper spray ionization has been used as a fast sampling/ionization method for the direct mass spectrometric analysis of biological samples at ambient conditions. Here, we demonstrated that by utilizing paper spray ionization-mass spectrometry (PSI-MS...