A STATISTICAL APPROACH TO ESTIMATING ADSORPTION-ISOTHERM PARAMETERS IN GRADIENT-ELUTION PREPARATIVE LIQUID CHROMATOGRAPHY
成果类型：
Article
署名作者：
Su, Jiaji; Yao, Zhigang; Li, Cheng; Zhang, Ye
署名单位：
National University of Singapore; Shenzhen MSU-BIT University
刊物名称：
ANNALS OF APPLIED STATISTICS
ISSN/ISSBN：
1932-6157
DOI：
10.1214/23-AOAS1772
发表日期：
2023
页码：
3476-3499
关键词：
摘要：
Determining the adsorption isotherms is an issue of significant importance in preparative chromatography. A modern technique for estimating adsorption isotherms is to solve an inverse problem so that the simulated batch separation coincides with actual experimental results. However, due to the ill-posedness, the high nonlinearity, and the uncertainty quantification of the corresponding physical model, the existing deterministic inversion methods are usually inefficient in real-world applications. To overcome these difficulties and study the uncertainties of the adsorption-isotherm parameters, in this work, based on the Bayesian sampling framework, we propose a statistical approach for estimating the adsorption isotherms in various chromatography systems. Two modified Markov chain Monte Carlo algorithms are developed for a numerical realization of our statistical approach. Numerical experiments with both synthetic and real data are conducted and described to show the efficiency of the proposed new method.
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