Low-cost heat assisted ambient ionization source for mass spectrometry in food and pharmaceutical screening

Ambient Ionization Mass Spectrometry (AI-MS) techniques have revolutionized analytical chemistry by enabling rapid analysis of samples under atmospheric conditions with minimal to no preparation. In this study, the optimization of a cold atmospheric plasma for the analysis of food and pharmaceutical...

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Published inAnalyst (London) Vol. 149; no. 17; pp. 4487 - 4495
Main Authors Gazeli, Odhisea, Elia, Efstathios A, Argirusis, Nikolaos, Lazarou, Constantinos, Anastassiou, Charalambos, Franzke, Joachim, Garcia-Reyes, Juan F, Georghiou, George E, Agapiou, Agapios
Format Journal Article
LanguageEnglish
Published England Royal Society of Chemistry 19.08.2024
Subjects
Analytical chemistry
Cost analysis
Dielectric barrier discharge
Food
Food Analysis - methods
Gas transport
Heating
Hot Temperature
Hydrodynamics
Inlet temperature
Ionization
Mass spectrometry
Mass Spectrometry - methods
Pharmaceutical Preparations - analysis
Pharmaceutical Preparations - chemistry
Pharmaceuticals
Plasma Gases - chemistry
Scientific imaging
Sensitivity analysis
Technology assessment
Transport properties
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Summary:Ambient Ionization Mass Spectrometry (AI-MS) techniques have revolutionized analytical chemistry by enabling rapid analysis of samples under atmospheric conditions with minimal to no preparation. In this study, the optimization of a cold atmospheric plasma for the analysis of food and pharmaceutical samples, liquid and solid, using a Heat-Assisted Dielectric Barrier Discharge Ionization (HA-DBDI) source is described. A significant enhancement in analyte signals was observed when a heating element was introduced into the design, potentially allowing for greater sensitivity. Furthermore, the synergy between the inlet temperature of the mass spectrometer and the heating element allows for precise control over the analytical process, leading to improved detection sensitivity and selectivity. Incorporating computational fluid dynamic (CFD) simulations into the study elucidated how heating modifications can influence gas transport properties, thereby facilitating enhanced analyte detection and increased signal intensity. These findings advance the understanding of HA-DBDI technology and provide valuable insights for optimizing AI-MS methodologies for a wide range of applications in food and pharmaceutical analysis.
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ISSN:0003-2654
1364-5528
1364-5528
DOI:10.1039/d4an00901k