Computer Assisted Method Development in Liquid Chromatography
Tomislav Bolanča
; Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10000 Zagreb, Croatia
Šime Ukić
; Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10000 Zagreb, Croatia
Mirjana Novak
; Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10000 Zagreb, Croatia
Marko Rogošić
; Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10000 Zagreb, Croatia
APA 6th Edition Bolanča, T., Ukić, Š., Novak, M. i Rogošić, M. (2014). Computer Assisted Method Development in Liquid Chromatography. Croatica Chemica Acta, 87 (2), 111-122. https://doi.org/10.5562/cca2241
MLA 8th Edition Bolanča, Tomislav, et al. "Computer Assisted Method Development in Liquid Chromatography." Croatica Chemica Acta, vol. 87, br. 2, 2014, str. 111-122. https://doi.org/10.5562/cca2241. Citirano 05.03.2021.
Chicago 17th Edition Bolanča, Tomislav, Šime Ukić, Mirjana Novak i Marko Rogošić. "Computer Assisted Method Development in Liquid Chromatography." Croatica Chemica Acta 87, br. 2 (2014): 111-122. https://doi.org/10.5562/cca2241
Harvard Bolanča, T., et al. (2014). 'Computer Assisted Method Development in Liquid Chromatography', Croatica Chemica Acta, 87(2), str. 111-122. https://doi.org/10.5562/cca2241
Vancouver Bolanča T, Ukić Š, Novak M, Rogošić M. Computer Assisted Method Development in Liquid Chromatography. Croatica Chemica Acta [Internet]. 2014 [pristupljeno 05.03.2021.];87(2):111-122. https://doi.org/10.5562/cca2241
IEEE T. Bolanča, Š. Ukić, M. Novak i M. Rogošić, "Computer Assisted Method Development in Liquid Chromatography", Croatica Chemica Acta, vol.87, br. 2, str. 111-122, 2014. [Online]. https://doi.org/10.5562/cca2241
Sažetak This paper describes potential applications of computer-assisted chemometrics in method devel-opment in liquid chromatography. These include modeling of retention (isocratic, gradient, molecular modeling, artificial neural networks), assessment of separation (peak capacity), single and multiple objective optimization approach, advanced optimization algorithms (genetic algorithms, simulated annealing) and method transfer issues (transfer of methods between instruments and / or laboratories). Selected topics provide an accessible source of information needed for successful increase of chromatographic efficiency and economic feasibility (higher sample throughput) in liquid chromatography.