• PyICLab: An integrated Python-...

Treffer: PyICLab: An integrated Python-based toolkit for in-silico simulations of ion chromatography.

Title:
PyICLab: An integrated Python-based toolkit for in-silico simulations of ion chromatography.
Authors:
Zhang K; Ningbo Key Laboratory of Agricultural Germplasm Resources Mining and Environmental Regulation, College of Science and Technology, Ningbo University, Ningbo, 315300, China. Electronic address: zhangkai1@nbu.edu.cn., Qian Y; College of Biological and Environmental Engineering, Zhejiang Shuren University, Hangzhou, 310015, China., Lou C; College of Quality and Standardization, China Jiliang University, Hangzhou, 310018, China. Electronic address: superiorlcy@126.com., Ye M; College of Biological and Environmental Engineering, Zhejiang Shuren University, Hangzhou, 310015, China., Zhu Y; Department of Chemistry, Zhejiang University, Hangzhou, 310028, China.
Source:
Talanta [Talanta] 2025 Jan 01; Vol. 282, pp. 127054. Date of Electronic Publication: 2024 Oct 15.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: Netherlands NLM ID: 2984816R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-3573 (Electronic) Linking ISSN: 00399140 NLM ISO Abbreviation: Talanta Subsets: PubMed not MEDLINE; MEDLINE
Imprint Name(s):
Publication: Amsterdam : Elsevier
Original Publication: Oxford : Pergamon Press
Contributed Indexing:
Keywords: Ion chromatography; Modeling; Open-source software; Python; Simulation; Two-dimensional ion chromatography
Entry Date(s):
Date Created: 20241018 Latest Revision: 20241119
Update Code:
20250114
DOI:
10.1016/j.talanta.2024.127054
PMID:
39423637
Database:
MEDLINE

Weitere Informationen

PyICLab is an open-source Python-based package featuring an object-oriented programming (OOP) interface, providing tools for realistic and customized numerical simulations of ion chromatography (IC). In this paper, we showcase PyICLab's use in simulating diverse separation scenarios, including isocratic carbonate elution, gradient hydroxide elution, high-concentration and large-volume injections. The accuracy of the embedded models was validated by demonstrating strong correlations between predicted and experimental results. Additionally, PyICLab's capability to handle complex IC configurations was demonstrated through a simulation of a column-switching system for seawater analysis. PyICLab offers valuable resources for chromatographic optimization, method development, and educational purposes. It is available on PyPI at pypi.org/project/pyIClab. Interested readers can install PyICLab using the pip command in a Python 3.11 or higher environment.
(Copyright © 2024 Elsevier B.V. All rights reserved.)

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.