Chemometric Optimization Studies in Catalysis Employing High-Throughput Experimentation
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The main topic of this thesis is the investigation of the synergies between High-Throughput Experimentation (HTE) and Chemometric Optimization methodologies in Catalysis research and of the use of such methodologies to maximize the advantages of using HTE methods. Several case studies were analysed including: 1) the exploration of a terpene addition reaction parameter space, in this case a hydration reaction, using a multi-step Design of Experiments approach. From this investigation insights on the main reactivity trends were obtained. 2) The optimization of the reaction conditions for the hydrogenation of cyanohydrin esters to N-acylated-ß-amino alcohols, using again a multi-step Design of Experiments approach. 3) The planning and modelling of catalytic benchmark response surfaces using Design of Experiments is performed. A library of 189 mixed-oxide catalysts was prepared and their activity tested and modelled for the CO oxidation reaction in both the absence (COOX) and presence (SELOX) of hydrogen. The COOX and SELOX benchmarks were used to access the optimization performance of selected Global optimization algorithms. 4) The optimization procedure of employing the Global Optimization Genetic algorithm and the influence of the algorithm settings on its optimization efficiency is studied. Both the COOX and SELOX benchmarks obtained were used to validate the Genetic algorithm performance. A Design of Experiments approach was used to select the configurations to be tested and study the effects of the chosen parameter settings. 5) The optimization performance of several algorithms was tested on the SELOX benchmark. The studied algorithms include Evolutionary Algorithms, Genetic Algorithms, Simulated Annealing, Taboo Search, and Hybrid Genetic Algorithms. Altogether, it was shown that the use of HTE, as a powerful method for catalysis research, is further improved by the application of appropriate experimental planning techniques. Strategies involving Chemometric methods like Design of Experiments and Global Optimization techniques can help in avoiding exhaustive experimental investigations and enhance the power of exploring large parameter spaces and locate the optimum catalytic system conditions.