Industrial cleaning baths play a vital role in maintaining surface cleanliness and product integrity across sectors such as electronics, automotive, and pharmaceuticals. However, real-time assessment of bath efficiency and contamination remains a challenge. This study presents a comprehensive strategy for characterizing volatile organic compounds (VOCs) emitted from both industrial cleaning agents and common surface contaminants such as greases and oils on metal. By employing advanced analytical platforms, such as comprehensive two-dimensional Gas Chromatography coupled with Time – of – Flight mass spectrometry (GC×GC – ToF – MS) and Hyperfast – GC – ToF – MS, we aim to establish detailed profiles that can act as predictive markers of cleaning bath performance and surface cleanliness level. By correlating VOCs with parameter such as bath age and contaminant type, a predictive model may be developed, enabling process optimisation, accurate scheduling of bath replacement and low-level contamination detection. Terpenes, such as β-pinene, limonene and linalool, are successfully correlated with degreasing bath exhaustion, while butylated hydroxytoluene, as well as octanal and decanal, may indicate a residual surface contamination for the lubricants tested in this work.

Industrial cleaning baths play a vital role in maintaining surface cleanliness and product integrity across sectors such as electronics, automotive, and pharmaceuticals. However, real-time assessment of bath efficiency and contamination remains a challenge. This study presents a comprehensive strategy for characterizing volatile organic compounds (VOCs) emitted from both industrial cleaning agents and common surface contaminants such as greases and oils on metal. By employing advanced analytical platforms, such as comprehensive two-dimensional Gas Chromatography coupled with Time – of – Flight mass spectrometry (GC×GC – ToF – MS) and Hyperfast – GC – ToF – MS, we aim to establish detailed profiles that can act as predictive markers of cleaning bath performance and surface cleanliness level. By correlating VOCs with parameter such as bath age and contaminant type, a predictive model may be developed, enabling process optimisation, accurate scheduling of bath replacement and low-level contamination detection. Terpenes, such as β-pinene, limonene and linalool, are successfully correlated with degreasing bath exhaustion, while butylated hydroxytoluene, as well as octanal and decanal, may indicate a residual surface contamination for the lubricants tested in this work.

Comprehensive Characterization of Volatile Organic Compounds released in Industrial Component Cleaning Processes by Advanced Mass Spectrometric Techniques

ZATTA, DANIELE
2024/2025

Abstract

Industrial cleaning baths play a vital role in maintaining surface cleanliness and product integrity across sectors such as electronics, automotive, and pharmaceuticals. However, real-time assessment of bath efficiency and contamination remains a challenge. This study presents a comprehensive strategy for characterizing volatile organic compounds (VOCs) emitted from both industrial cleaning agents and common surface contaminants such as greases and oils on metal. By employing advanced analytical platforms, such as comprehensive two-dimensional Gas Chromatography coupled with Time – of – Flight mass spectrometry (GC×GC – ToF – MS) and Hyperfast – GC – ToF – MS, we aim to establish detailed profiles that can act as predictive markers of cleaning bath performance and surface cleanliness level. By correlating VOCs with parameter such as bath age and contaminant type, a predictive model may be developed, enabling process optimisation, accurate scheduling of bath replacement and low-level contamination detection. Terpenes, such as β-pinene, limonene and linalool, are successfully correlated with degreasing bath exhaustion, while butylated hydroxytoluene, as well as octanal and decanal, may indicate a residual surface contamination for the lubricants tested in this work.
2024
Comprehensive Characterization of Volatile Organic Compounds released in Industrial Component Cleaning Processes by Advanced Mass Spectrometric Techniques
Industrial cleaning baths play a vital role in maintaining surface cleanliness and product integrity across sectors such as electronics, automotive, and pharmaceuticals. However, real-time assessment of bath efficiency and contamination remains a challenge. This study presents a comprehensive strategy for characterizing volatile organic compounds (VOCs) emitted from both industrial cleaning agents and common surface contaminants such as greases and oils on metal. By employing advanced analytical platforms, such as comprehensive two-dimensional Gas Chromatography coupled with Time – of – Flight mass spectrometry (GC×GC – ToF – MS) and Hyperfast – GC – ToF – MS, we aim to establish detailed profiles that can act as predictive markers of cleaning bath performance and surface cleanliness level. By correlating VOCs with parameter such as bath age and contaminant type, a predictive model may be developed, enabling process optimisation, accurate scheduling of bath replacement and low-level contamination detection. Terpenes, such as β-pinene, limonene and linalool, are successfully correlated with degreasing bath exhaustion, while butylated hydroxytoluene, as well as octanal and decanal, may indicate a residual surface contamination for the lubricants tested in this work.
VOCs
GCxGC
FFTG-GC
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/92842