Results 121 to 130 of about 50,739 (222)
Time-weighted average solid-phase microextraction (TWA-SPME) is a solvent-free passive sampling technique increasingly applied to volatile organic compounds (VOCs) monitoring in air. This review critically examines the theoretical foundations of TWA-SPME
Shokouh Haddadi +2 more
doaj +1 more source
Phytotherapy Research, Volume 40, Issue 2, Page 488-492, February 2026.
Luigi A. Morrone +11 more
wiley +1 more source
The goal of this research is the development of a solid phase microextraction based on monolithic molecularly imprinted polymer fiber (SPME-MMIPF) method to determine 229 pesticides in edible oil samples using gas chromatography-mass spectrometry (GC-MS)
Fatemeh Kardani +7 more
doaj +1 more source
Method for covering a spme fibre with carbon nanotubes and resulting spme fibre
[EN] The invention relates to a method for covering solid phase microextraction (SPME) fibres with carbon nanotubes (CNT), comprising the following operations: (i) depositing a layer of a metal material on the SPME fibre; (ii) applying a heat treatment in order to form catalytic metal nanoparticles in a reducing atmosphere; and (iii) applying
Bertrán, Enric +3 more
openaire +1 more source
Nuevos desarrollos metodológicos en SPME [PDF]
La Microextracción en fase sólida (SPME) ha experimentado un rápido desarrollo desde su introducción hace más de 20 años teniendo un gran impacto sobre las prácticas de muestreo y preparación de muestra en áreas como análisis químico, bioanálisis, los alimentos y las ciencias ambientales.
openaire +1 more source
Headspace SPME GC-MS Analysis of Urinary Volatile Organic Compounds (VOCs) for Classification Under Sample-Limited Conditions. [PDF]
Woyciechowski L +11 more
europepmc +1 more source
In situ electro-polymerized polyaniline thin film on highly porous carbon fiber felt for extraction and chromatographic detection of non-steroidal anti-inflammatory drugs. [PDF]
Sheikhi T, Razmi H, Mohammadiazar S.
europepmc +1 more source
Honey Botanical Origin Authentication Using HS-SPME-GC-MS Volatile Profiling and Advanced Machine Learning Models (Random Forest, XGBoost, and Neural Network). [PDF]
Pourmoradian A +3 more
europepmc +1 more source

