Accuracy of retention model parameters obtained from retention data in liquid chromatography-Reference-Cited by-同舟云学术

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Accuracy of retention model parameters obtained from retention data in liquid chromatography

Published:2022-04-04 Issue:17 Volume:45 Page:3241-3255
ISSN:1615-9306
Container-title:Journal of Separation Science
language:en
Short-container-title:J of Separation Science

Author:

Brau Tyler¹,Pirok Bob¹²,Rutan Sarah³,Stoll Dwight¹

Affiliation:

1. Department of Chemistry Gustavus Adolphus College 800 West College Avenue Saint Peter MN 56082 USA

2. Van’t Hoff Institute for Molecular Sciences University of Amsterdam Amsterdam 1090 GD The Netherlands

3. Department of Chemistry Virginia Commonwealth University 1001 West Main St. Richmond VA 23284‐2006 USA

Publisher

Wiley

Subject

Filtration and Separation,Analytical Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jssc.202100911

Reference26 articles.

1. Chromatographic Characterization of Silica C18 Packing Materials. Correlation between a Preparation Method and Retention Behavior of Stationary Phase

2. Chromatographic classification of commercially available reverse-phase HPLC columns

3. A New Look at the Selectivity of RPC Columns

4. Column Characterization and Selection Systems in Reversed-Phase High-Performance Liquid Chromatography

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1. A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatography;Journal of Chromatography A;2024-01

2. The Gradient Delay Volume, Part I: Theory;LCGC International;2024-01-01

3. Experimental design and re-parameterization of the Neue-Kuss model for accurate and precise prediction of isocratic retention factors from gradient measurements in reversed phase liquid chromatography;Journal of Chromatography A;2023-11

4. Quality Evaluation of Sanguisorbae Radix via Python Aided Optimization Fingerprint Chromatography Combined with Quantitative Analysis of Multi-components by Single Marker;Chromatographia;2023-10-26

5. Computer-driven optimization of complex gradients in comprehensive two-dimensional liquid chromatography;Journal of Chromatography A;2023-09

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