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Optimization of IC Separation Based on Isocratic-to-Gradient Retention Modeling in Combination with Sequential Searching or Evolutionary Algorithm
Author(s) -
Šime Ukić,
Marko Rogošić,
Mirjaovak Stankov,
Ena Šimović,
Vesna Tišler,
Tomislav Bolanča
Publication year - 2013
Publication title -
journal of analytical methods in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.407
H-Index - 25
eISSN - 2090-8865
pISSN - 2090-8873
DOI - 10.1155/2013/549729
Subject(s) - cellobiose , raffinose , simplex algorithm , maxima and minima , chromatography , genetic algorithm , algorithm , separation (statistics) , gradient descent , chemistry , mathematics , computer science , mathematical optimization , artificial intelligence , statistics , linear programming , cellulose , biochemistry , mathematical analysis , artificial neural network , sucrose , cellulase
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.

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