2026-09-21T19:10:02Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/115918 2023-07-11 col_2142_5131 col_2142_14789 com_2142_5130 com_2142_14788 com_2142_8903

application/pdf en text Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01 The student, Brennan Rose, accepted the attached license on 2022-07-11 at 19:41. The student, Brennan Rose, submitted this Dissertation for approval on 2022-07-11 at 21:56. This Dissertation was approved for publication on 2022-07-15 at 11:07. DSpace SAF Submission Ingestion Package generated from Vireo submission #18241 on 2022-11-16 at 10:55:51 Denmark, Scott E Denmark, Scott E Burke, Martin D Sarlah, David Fout, Alison R 2022-08 Synthesis of universal training sets and applications of chemoinformatics toward enantioselective reaction optimization Rose, Brennan T. 2022-07-15 Chemoinformatics Chiral Brønsted Acid Catalysis Iodination 1,2-Amino alcohols This thesis covers three independent projects with highlights of my experimental contributions to all three projects and a detailed discussion of my application of the chemoinformatics workflow. A brief introduction to 3D-QSSR comprises the first half of chapter 1, followed by the development of a general method for the synthesis of 1,2-amino alcohols. Chapter 2 centers on the development of a chemoinformatics workflow, its application to chiral phosphoric acids, the synthesis of chiral phosphoric acids, and the validation of this proposed workflow. Prediction of highly selective catalysts (>80% ee) with high levels of accuracy are discussed towards the end of chapter 2. Chapter 3 of this thesis will cover the generation of an in silico library and selection of a universal training set (UTS) of disulfonimide (DSI) catalysts. The nearest neighbors analysis that was performed to ensure data integrity for modeling purposes is discussed throughout chapter 3. Finally, some excerpts of the synthesis of this UTS are provided. Chapter 4 will focus on the application of this DSI UTS towards the atropselective iodination of 2-amino-6-aryl pyridines. The development of a large diverse data set and a discussion of different approaches to regression modeling of this data set are presented. Finally, development of a new catalyst recommendation system called catalyst selection by committee (CSC) that is based heavily on high-level data fusion strategies is discussed towards the end of chapter 4. Initial validation of this CSC workflow by the synthesis of three of the proposed catalysts lead to the discovery of a significantly more general catalyst, whose application towards the preparative scale iodination of 2-amino-6-aryl-pyridines will be discussed. Thesis eng https://hdl.handle.net/2142/115918 Copyright 2020 Brennan T. Rose Ph.D. Dissertation Chemistry University of Illinois at Urbana-Champaign Chemistry