ReviewJournal of separation science2021
Recent applications of retention modelling in liquid chromatography.
Review in Journal of separation science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Graphical Visualization Approach for Two-Dimensional Liquid Chromatography with Parallel Column Arrays.ACS measurement science au · 2026Article
- Review
- Characterization of Dye-Loaded Poly(lactic-Analytical chemistry · 2023Article
- Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data.Journal of cheminformatics · 2023Article
- Advances on Hormones in Cosmetics: Illegal Addition Status, Sample Preparation, and Detection Technology.Molecules (Basel, Switzerland) · 2023Review
- Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT).Frontiers in chemistry · 2023Article
- Expediting the chromatographic analysis of COVID-19 antibody therapeutics with ultra-short columns, retention modeling and automated method development.Journal of pharmaceutical and biomedical analysis · 2022Article
- User-Driven Strategy for In Silico Screening of Reversed-Phase Liquid Chromatography Conditions for Known Pharmaceutical-Related Small Molecules.Molecules (Basel, Switzerland) · 2022Article
- Numerical Approximation of the Nonequilibrium Model of Gradient Elution Chromatography Considering Linear and Nonlinear Solvent Strength Models.ACS omega · 2022Article
- A simple mathematical treatment for predicting linear solvent strength behavior in gradient elution: Application to biomolecules.Journal of separation science · 2022Article
- From Centroided to Profile Mode: Machine Learning for Prediction of Peak Width in HRMS Data.Analytical chemistry · 2021Article
- Recent applications of retention modelling in liquid chromatography.Journal of separation science · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Recent applications of retention modelling in liquid chromatography (2015-2020) are comprehensively reviewed. The fundamentals of the field, which date back much longer, are summarized. Retention modeling is used in retention-mechanism studies, for determining physical parameters, such as lipophilicity, and for various more-practical purposes, including method development and optimization, method transfer, and stationary-phase characterization and comparison. The review focusses on the effects of mobile-phase composition on retention, but other variables and novel models to describe their effects are also considered. The five most-common models are addressed in detail, i.e. the log-linear (linear-solvent-strength) model, the quadratic model, the log-log (adsorption) model, the mixed-mode model, and the Neue-Kuss model. Isocratic and gradient-elution methods are considered for determining model parameters and the evaluation and validation of fitted models is discussed. Strategies in which retention models are applied for developing and optimizing one- and two-dimensional liquid chromatographic separations are discussed. The review culminates in some overall conclusions and several concrete recommendations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.