Lorenzo-Parodi, Nerea; Kaziur-Cegla, Wiebke; Schmidt, Torsten Claus:
Automation and optimization of the sample preparation of aromatic amines for their analysis with GC–MS
In: Green Analytical Chemistry, Band 6 (2023), Artikel 100071
2023Artikel/Aufsatz in ZeitschriftOA Gold
ChemieFakultät für Chemie » Analytische ChemieForschungszentren » Center for Nanointegration Duisburg-Essen (CENIDE)
Damit verbunden: 1 Publikation(en)
Titel in Englisch:
Automation and optimization of the sample preparation of aromatic amines for their analysis with GC–MS
Autor*in:
Lorenzo-Parodi, NereaUDE
LSF ID
55264
ORCID
0000-0002-4761-5403ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Kaziur-Cegla, WiebkeUDE
LSF ID
60436
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Schmidt, Torsten ClausUDE
GND
1074278453
LSF ID
14592
ORCID
0000-0003-1107-4403ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
korrespondierende*r Autor*in
Erscheinungsjahr:
2023
Open Access?:
OA Gold
Scopus ID
Notiz:
CA Schmidt
Sprache des Textes:
Englisch
Schlagwort, Thema:
Aromatic amines ; Automation ; Derivatization ; GC–MS ; SPME ; Urine

Abstract in Englisch:

Aromatic amines (AAs) in urine typically require complex, labor-intensive and time-consuming sample preparation procedures before they can be analyzed. Usually it consists of hydrolysis, extraction and, especially when analyzed with GC, derivatization. Traditionally, these steps are done manually, significantly contributing to the total analysis time and providing opportunities for human errors. Automation presents several advantages, such as minimized human intervention and errors, and an overall greener analytical procedure. In this study, the automation of the AAs sample preparation procedure for urine samples was investigated. Problems encountered during the automation and adjustments made to the original protocol are discussed in detail. Some examples include volume limitations or needle penetration depth adjustments. Taking advantage of the automation, several steps of the sample preparation procedure could be further optimized, such as reaction/extraction times or some of the reagents which were not optimal for the automated set-up. The automated procedure presented here enables a user-friendly and green approach for the analysis of AA in urine, which could be used to gain a better understanding between smoking, AA concentrations in urine, and the risk of developing smoking related diseases.