Digging Deeper into the Methods of Computational Chemistry by Joshua A. Kammeraad A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Chemistry and Scientific Computing) in the University of Michigan 2020 Doctoral Committee: Associate Professor Paul M Zimmerman, Chair Professor Charles L. Brooks III Professor Robert Krasny Professor Roseanne Sension Joshua A. Kammeraad [email protected] ORCID iD: 0000-0003-0386-7198 © Joshua A. Kammeraad 2020 Dedication To God be all the glory. ii Acknowledgements First, I would like to thank my graduate mentor Paul Zimmerman for his mentorship. Paul learned my quirkiness and how to individually mentor me. His focus and direction kept me on track and his patience in challenging seasons is appreciated. I would also like to thank the rest of my graduate committee for their advice and feedback throughout this PhD program. I would like to acknowledge the rest of the Zimmerman lab, particularly Ian Pendleton, Alan Chien, and Andrew Molina for welcoming me into the lab and engaging in deep conversations of an academic and personal nature. I would like to thank Cody Aldaz for letting me be a part of his cool projects. Thank you Ambuj Tewari and everyone involved in our machine learning collaborations: Jack, Mina, Eric, Exequiel, Ziping, Tarun, and Eunjae. Ryan Hayes and Allison Roessler, thank you for all the times together in prayer for each other and our labs. I am also grateful for all of the mentors and teachers who prepared me for graduate school, particularly professors DeJongh, Pennings, Polik, and Cinzori for their support throughout my undergraduate education. Thank you to my cross country teammates including my roommates Tim Lewis and David Dolfin as well as Hania Szymczak, Michelle Kerr, and Jess Gaines for all of our nerdy, serious, and silly running conversations that kept me sane and the long nights and weekends of studying together that prepared me so well for this program. Thank you Dave Brzezinski, Jack Geddes, David Taylor, and Paul Webb from Grace Bible Church for your mentorship throughout my graduate studies. I am deeply grateful to my spiritual brothers and sisters in Impact Graduate Christian Fellowship without whom I could not have survived this program, including my accountability partners for their encouragement and support of my continued growth: Sinsar Hsie, Mark Dong, Calvin Montana, Matt Cui, Alex Wang, and Joseph Tu. A special thanks to each of the brothers and sisters I've had the privilege of serving closely with: Nancy Wu, Josh Cheng, Sara Timberlake, and Anita Luong. Our partnerships have sculpted and sharpened my character and your patience and support in my weakness is appreciated. Thank you Jasmine Jones for being so relentlessly selfless including spontaneously helping prepare me for my oral defense while I recovered from illness. iii James Tan and Matt Hughes, I have a deep appreciation for your loyal brotherhood in Christ and fighting with me through some of the hardest times of the past 5 years. To my family, thank you for being so loving and supportive of all stages of my education. Finally, I am eternally grateful to Jesus Christ my Savior and Lord for this beautiful, elegant universe and the capacity to explore it. iv Table of Contents Dedication ...................................................................................................................................... ii Acknowledgements ...................................................................................................................... iii List of Figures .............................................................................................................................. vii List of Schemes .............................................................................................................................. x List of Tables ................................................................................................................................ xi Abstract ........................................................................................................................................ xii Chapter 1. Introduction ........................................................................................................... 1 Chapter Overviews...................................................................................................................... 1 Chapter 2 ................................................................................................................................. 1 Chapter 3 ................................................................................................................................. 2 Chapter 4 ................................................................................................................................. 2 Chapter 5 ................................................................................................................................. 3 Themes ........................................................................................................................................ 3 Chapter 2. Estimating the Derivative Coupling Vector using Gradients ........................... 6 Main Text .................................................................................................................................... 6 Methods..................................................................................................................................... 15 Chapter 3. What Does the Machine Learn? Knowledge Representations of Chemical Reactivity ............................................................... 18 Introduction ............................................................................................................................... 18 A First Challenge: Representing Chemical Data ...................................................................... 22 Relationships Between Representations ................................................................................... 24 v Deconstruction of Machine Model-Making.............................................................................. 29 Reestablishing Chemical Concepts ........................................................................................... 30 Evans-Polanyi Relationships .................................................................................................... 33 Discussion ................................................................................................................................. 36 Conclusions ............................................................................................................................... 40 Computational Details .............................................................................................................. 41 Reaction Representations ...................................................................................................... 41 Dataset................................................................................................................................... 43 Machine Learning Pipeline ................................................................................................... 45 Appendix to Chapter 3 .............................................................................................................. 47 Note About Neural Network Topologies .............................................................................. 47 Note About Representing Atoms .......................................................................................... 52 Note on Data Postprocessing ................................................................................................ 62 Reactions Appearing in Data Set 1 ....................................................................................... 63 Chapter 4. Human – Algorithm Interactive Approach to Conformer Generation ......... 66 Introduction ............................................................................................................................... 66 Materials and Methods .............................................................................................................. 70 Results and Discussion ............................................................................................................. 75 Future Directions ...................................................................................................................... 79 Chapter 5. Final Thoughts .................................................................................................... 82 Open Questions and Research Opportunities ........................................................................... 83 How to Approach Future Challenges ........................................................................................ 84 Developing Multidisciplinary Scientific Leaders ................................................................. 85 Building a Strong Research Community with a Multidisciplinary Mindset ......................... 85 Active Engagement with Other Scientists ............................................................................ 87 Conclusion ................................................................................................................................ 87 Bibliography ...............................................................................................................................