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master's thesis
Optimiranje razdvajanja pesticida u HPLC analizi
Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology, 2017. urn:nbn:hr:149:758713
Nikolaš, Ljubica
University of Zagreb
Faculty of Chemical Engineering and Technology

Institutional repository: Repository of Faculty of Chemical Engineering and Technology University of Zagreb

Cite this document

Nikolaš, Lj. (2017). Optimiranje razdvajanja pesticida u HPLC analizi (Master's thesis). Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology. Retrieved from https://urn.nsk.hr/urn:nbn:hr:149:758713

Nikolaš, Ljubica. "Optimiranje razdvajanja pesticida u HPLC analizi." Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2017. https://urn.nsk.hr/urn:nbn:hr:149:758713

Nikolaš, Ljubica. "Optimiranje razdvajanja pesticida u HPLC analizi." Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2017. https://urn.nsk.hr/urn:nbn:hr:149:758713

Nikolaš, Lj. (2017). 'Optimiranje razdvajanja pesticida u HPLC analizi', Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:149:758713

Nikolaš Lj. Optimiranje razdvajanja pesticida u HPLC analizi [Master's thesis]. Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology; 2017 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:149:758713

Lj. Nikolaš, "Optimiranje razdvajanja pesticida u HPLC analizi", Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:149:758713

Metadata
TitleOptimiranje razdvajanja pesticida u HPLC analizi
Title (english)Optimization of pesticide separation in HPLC analysis
AuthorLjubica Nikolaš
MentorŠime Ukić (mentor)
Committee memberŠime Ukić (predsjednik povjerenstva)
Committee memberTomislav Bolanča (član povjerenstva)
Committee memberEma Horak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Chemical Engineering and Technology
Zagreb
Defense date and country2017-09-27, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Chemistry
Analytic Chemistry
Abstract
Razvitak novih metoda za određivanje pojedinih analita vrlo je često dugotrajan proces. Pronalazak optimalnih uvjeta analize zahtijeva puno vremena, te je često s ekonomske strane vrlo nepovoljan proces. Razvijanje novih postupaka analize uglavnom se temelji na metodi pokušaja i pogreške pri čemu se troši puno kemijskih reagensa. U svrhu smanjenja troškova i vremena potrebnog za razvitak nove metode koriste se različiti modeli vremena zadržavanja. Ovaj rad fokusiran je na optimiranje separacije skupine pesticida analiziranih tekućinskom kromatografijom visoke djelotvornosti (HPLC) matematičkim putem. HPLC analizama dobivena su vremena zadržavanja ispitivanih pesticida pri izokratnim uvijetima elucije, te potom transferirana u gradijentno okruženje koristeći tzv. iso-to-grad pristup. Iako gradijentni model nije pružio očekivanu kvalitetu predviđanja, detektirani su potencijalni uzroci njegovog nedostatka. Za očekivati je kako će se njihovom eliminacijom dobiti modeli znatno boljih prediktivnh karakteristika.
Abstract (english)
Developing new methods for determining certain analytes is often a time-consumming process. Discovering the optimal conditions for analysis requires time and it is often non-economical. The development of new analytical procedures is often a result of the trial and error approach, where many chemical reagents are wasted. Retention time modelling is commonly used to reduce both: the costs and time spent for developing of a new method. The aim of this work is mathematical optimization of separation for group of pesticides analyzed by High Performance Liquid Chromatography (HPLC). A set of isocratic elutions was performed and the results were transferred into gradient environment by applying so called iso-to-grad approach. The tested gradient model did not show great predictive capacity. Yet, such model approved itself in case with one-component eluent and therefore higher predictive abilities were expected. The major potential causes of this inadequate prediction were detected and discussed. It is expected that elimination of these causes will lead to significant increase of the model’s predictive abilities.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:149:758713
Study programmeTitle: Applied Chemistry - Graduate study; specializations in: Environmental chemistry and green technologies, Advanced materials and technologies, Applied organic chemistry
Course: Environmental chemistry and green technologies
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra primijenjene kemije (magistar/magistra primijenjene kemije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-04-28 10:19:59