论文标题
估计梯度水平制剂液相色谱中的吸附 - 等热参数的统计方法
A Statistical Approach to Estimating Adsorption-Isotherm Parameters in Gradient-Elution Preparative Liquid Chromatography
论文作者
论文摘要
确定吸附等温度是制备色谱中重要性重要性的问题。一种用于估计吸附等温线的现代技术是解决一个反问题，以便模拟的批次分离与实际的实验结果一致。但是，由于适应性不良，非线性高和相应物理模型的不确定性量化，现有的确定性反演方法通常在现实世界应用中效率低下。为了克服这些困难并研究吸附 - 等热参数的不确定性，在这项工作中，基于贝叶斯采样框架，我们提出了一种统计方法，用于估计各种色谱系统中的吸附等温线。开发了两种修改的马尔可夫链蒙特卡洛算法，以实现我们的统计方法。进行了合成和实际数据的数值实验，并描述了提出的新方法的效率。
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 non-linearity, 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.
