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Application note
Enhancing the sensitivity of headspace analysis using large volume preconcentration (LVP) – Trace-level GC–MS analysis of VOCs in foods and beverages
Application Note 264
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Application note
Enhancing sensitivity for headspace and headspace-SPME analysis: The benefits of a trap-based approach
Application Note 267
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Application note
Enhancing the performance of SPME and sorptive extraction for GC–MS using trap-based preconcentration
Application Note 268
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Application note
Trace-level analysis of VOCs in a tomato product using headspace extraction with large volume preconcentration (LVP) and multi-step enrichment (MSE)
Application Note 270
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Application note
Quantifying trace volatile aromatics (BTEX-styrene) in foodstuffs caused by migration from packaging using extraction and enrichment techniques to enhance GC–MS analysis
Application Note 271
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Application note
Improving extraction efficiency of SPME on soil samples by using SPME–trap and SPME–trap with multi-step enrichment
Application Note 263
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Application note
Quantifying trace odorants in water by GC–MS with trap-based preconcentration: An assessment of high-capacity sorptive extraction
Application Note 255
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Application note
Breath sampling for clinical research and occupational health monitoring
Application Note 147
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Application note
A scalable TD–GC–MS approach for the discovery of breath biomarkers of malaria
Application Note 148
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