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Optimization of IC Separation Based on Isocratic-to-Gradient Retention Modeling in Combination with Sequential Searching or Evolutionary Algorithm

机译:基于等度梯度保留模型与顺序搜索或进化算法相结合的IC分离优化

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Gradient ion chromatography was used for the separation of eight sugars: arabitol, cellobiose, fructose, fucose, lactulose, melibiose, N-acetyl-D-glucosamine, and raffinose. The separation method was optimized using a combination of simplex or genetic algorithm with the isocratic-to-gradient retention modeling. Both the simplex and genetic algorithms provided well separated chromatograms in a similar analysis time. However, the simplex methodology showed severe drawbacks when dealing with local minima. Thus the genetic algorithm methodology proved as a method of choice for gradient optimization in this case. All the calculated/predicted chromatograms were compared with the real sample data, showing more than a satisfactory agreement.
机译:梯度离子色谱法用于分离八种糖:阿糖醇,纤维二糖,果糖,岩藻糖,乳果糖,蜜二糖,N-乙酰基-D-葡萄糖胺和棉子糖。使用单纯形或遗传算法与等度至梯度保留模型的组合优化了分离方法。单纯形法和遗传算法在相似的分析时间内都提供了分离良好的色谱图。但是,单纯形法在处理局部极小值时显示出严重的缺点。因此,在这种情况下,遗传算法方法被证明是梯度优化的一种选择方法。将所有计算/预测的色谱图与真实样品数据进行比较,显示出令人满意的一致性。

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