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09:19
Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction
Published on: June 1, 2022
A novel differential mobility analyzer as a VOC detector and multivariate techniques for identification and
V Pomareda1, S Lopez-Vidal, D Calvo
1Intelligent Signal Processing Group, Department of Electronics, University of Barcelona, Martí i Franques 1, 08028 Barcelona, Spain. vpomareda@el.ub.es
The Analyst
|May 14, 2013
Summary
This study introduces a novel parallel plate Differential Mobility Analyser (DMA) with enhanced sheath flow and detection for improved ion mobility spectrometry. It demonstrates the first use of multivariate data processing for quantitative analysis of volatile organic compounds (VOCs) and environmental samples using a stand-alone DMA.
Area of Science:
- Analytical Chemistry
- Physical Chemistry
- Environmental Science
Background:
- Ion Mobility Spectrometry (IMS) separates ions based on their drift time.
- Differential Mobility Analysers (DMA) separate ions spatially based on electrical mobility.
- Traditional IMS/DMA data analysis often relies on univariate techniques for qualitative detection.
Purpose of the Study:
- To present results from a novel parallel plate DMA instrument.
- To highlight improvements in resolving power and sensitivity due to unique design features.
- To demonstrate the application of multivariate data processing for quantitative analysis with a stand-alone DMA.
Main Methods:
- Utilized a parallel plate DMA instrument with modified sheath flow and detection systems.
- Acquired datasets from the stand-alone DMA instrument.
- Applied multivariate data processing techniques to the acquired datasets.
Main Results:
- The novel DMA design demonstrated improved resolving power and sensitivity.
- Successful quantitative measurements were achieved using multivariate data processing.
- The study presents the first application of multivariate analysis for VOCs and environmental samples with a stand-alone DMA.
Conclusions:
- The developed parallel plate DMA offers enhanced performance for ion mobility analysis.
- Multivariate data processing significantly improves quantitative capabilities for DMA measurements.
- This approach provides a powerful tool for analyzing volatile organic compounds and environmental samples.
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