Use of Modern Computational Methods and Neural Networks to Optimize Methods for LC/MS/MS Analysis of Military-Relevant Organophosphorus Compounds

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG45__%2F25%3A00563070" target="_blank" >RIV/60162694:G45__/25:00563070 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.chemicke-listy.cz/ojs3/index.php/chemicke-listy/article/view/4512" target="_blank" >http://www.chemicke-listy.cz/ojs3/index.php/chemicke-listy/article/view/4512</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.54779/chl20240103" target="_blank" >10.54779/chl20240103</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Use of Modern Computational Methods and Neural Networks to Optimize Methods for LC/MS/MS Analysis of Military-Relevant Organophosphorus Compounds

Popis výsledku v původním jazyce

The search for the optimal instrumental settings of conditions in chemical analysis is typically a lengthy process. This article proposes the use of neural networks for this purpose, particularly in relation to determining the optimal conditions for the analysis of substances under study using LC/MS/MS and ESI technologies, based on the knowledge of their fundamental properties, referred to as universal descriptors. The work focuses on finding such analysis conditions that maximize the precursor ion signal. The paper specifically addresses the question of whether the results obtained from one type of analyte can be used for neural -interpolated prediction of optimal conditions for similar analytes.

Název v anglickém jazyce

Use of Modern Computational Methods and Neural Networks to Optimize Methods for LC/MS/MS Analysis of Military-Relevant Organophosphorus Compounds

Popis výsledku anglicky

The search for the optimal instrumental settings of conditions in chemical analysis is typically a lengthy process. This article proposes the use of neural networks for this purpose, particularly in relation to determining the optimal conditions for the analysis of substances under study using LC/MS/MS and ESI technologies, based on the knowledge of their fundamental properties, referred to as universal descriptors. The work focuses on finding such analysis conditions that maximize the precursor ion signal. The paper specifically addresses the question of whether the results obtained from one type of analyte can be used for neural -interpolated prediction of optimal conditions for similar analytes.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10400 - Chemical sciences

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

CHEMICKE LISTY

ISSN

0009-2770

e-ISSN

1213-7103

Svazek periodika

118

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

103-110

Kód UT WoS článku

001163279300006

EID výsledku v databázi Scopus

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