AUTOSEP-Automated Separation by Eluotropic Space Optimisation

This project is named “AUTOSEP-Automated separation by eluotropic space optimisation” using High Performance Liquid Chromatography, (HPLC). The term eluotropic space is defined as the design space, which includes all the chemical and instrumental changes that can be performed in a chromatographic system e.g. changes in types of columns, gradients, solvents, pH. This project includes procedures of method development, optimisation, and validation. Its aim is to design a system which would optimize the separation of mixtures of compounds by defining eluotropic space around column separation, organic modifiers, and buffers. The use of Design of Experiment will help at the optimisation of lab experiments to obtain data to predict the best selection of columns, solvents, mobile phases for the new analyte/matrix combinations. Due to Covid-19 situation and restriction in getting back to the lab, at my request experimental data was generated by the Nouryon Expert Capability Group, Measurement and Analytical Sciences in the Netherlands and Waters Corporation, London. These data covered the experimental design addressing different injection volumes, flow rates, mobile phase ratios to measure retention time, peak area, peak asymmetry. Waters used different columns and solvents and measured retention time, peak area and resolution. My experimental work was to do the method development, optimisation and validation of the separation of drugs, as well as, agrochemicals, by choosing the best mobile phase ratio for succeeding the optimum peak separation by measuring resolution values. The experimental work was optimised by DOE by using a wide range of design and response variables to access the separation of compounds. Concerning the main results, there was successful separation of the of drugs but the complicated matrix of 11 agrochemicals only 2 of them could not be separated and for later work DOE together with LC/MS could be performed to identify all the compounds.

Name dc:type.qualificationname

Master's Thesis

Level dc:type.qualificationlevel

Student thesis

Year dc:date.issued

2024

Author dc:creator

• Ioannidou, Aikaterini

Advisors dc:contributor.advisor

• Davies, Antony
• Guwy, Alan

Language dc:language

eng

Identifier

oai:pure.atira.dk:studenttheses/37e368db-7162-4282-a713-e86c78932997

OAI identifier oai:identifier

oai:pure.atira.dk:studenttheses/37e368db-7162-4282-a713-e86c78932997