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Titel: Novel approaches for quantitative analysis of small biomolecules in MALDI-MS and SALDI-MS
VerfasserIn: Zhen, Liu
Sprache: Englisch
Erscheinungsjahr: 2020
DDC-Sachgruppe: 540 Chemie
Dokumenttyp: Dissertation
Abstract: The aim of this work is to develop novel approaches to improve signal reproducibility and sensitivity in matrix-assisted laser desorption/ionization (MALDI) and surface-assisted laser desorption/ionization (SALDI) mass spectrometry (MS), for quantitative analysis of small biomolecules including endogenous metabolites and small lipids. Firstly, regular channels were designed in the target plate to inhibit the inhomogeneous deposition of the samples during solvent evaporation, to improve the signal reproducibility in MALDI-MS. Secondly, a series of ultra-thin and homogeneous AuNP substrates ([AuNP]n) were prepared at the air/water interface by using a Langmuir-Blodgett inspired approach. The optimized [AuNP]n substrates exhibited not only high SALDI-MS signal intensity but also excellent signal reproducibility, both of which benefits the quantitative analyses in SALDI-MS. Thirdly, influences of gold core size and surface ligands on the MS signal were systematically studied to further improve the function of AuNP substrates in SALDI-MS. The results indicated that the AuNPs with bigger core size and hydrophobic surface ligands showed higher signal intensity. Moreover, removing the organic ligand of the as-deposited AuNP substrates could further increase the signal intensity.
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-324341
hdl:20.500.11880/29869
http://dx.doi.org/10.22028/D291-32434
Erstgutachter: Volmer, Dietrich A.
Tag der mündlichen Prüfung: 24-Sep-2020
Datum des Eintrags: 16-Okt-2020
Drittmittel / Förderung: Chinese Council scholarship
Fördernummer: 201608080213
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Chemie
Professur: NT - Keiner Professur zugeordnet
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

Dateien zu diesem Datensatz:
Datei Beschreibung GrößeFormat 
PhD thesis-Zhen Liu - 05.10.2020.pdfPhD dissertation29,36 MBAdobe PDFÖffnen/Anzeigen


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