Repository logo
Log In(current)
  1. Home
  2. Colleges & Schools
  3. Graduate School
  4. Doctoral Dissertations
  5. Small Molecule Activation by Transition Metal Complexes: Studies with Quantum Mechanical and Machine Learning Methodologies
Details

Small Molecule Activation by Transition Metal Complexes: Studies with Quantum Mechanical and Machine Learning Methodologies

Date Issued
May 1, 2021
Author(s)
Kirkland, Justin Kyle
Advisor(s)
Konstantinos D. Vogiatzis
Additional Advisor(s)
Sharani Roy
Ziling Xue
Vasileios Maroulas
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/27995
Abstract

One of the largest areas of study in the fields of chemistry and engineering is that of activation of small molecules such as nitrogen, oxygen and methane. Herein we study the activation of such molecules by transition metal compounds using quantum mechanical methods in order to understand the complex chemistry behind these processes. By understanding these processes, we can design and propose novel catalytic species, and through the use of data-driven machine learning methods, we are able to accelerate materials discovery.

Subjects

Chemistry

Machine Learning

Quantum Chemistry

Catalysis

Disciplines
Physical Chemistry
Degree
Doctor of Philosophy
Major
Chemistry
File(s)
Thumbnail Image
Name

JKKirkland_Dissertation_Revised_v3.pdf

Size

10.65 MB

Format

Adobe PDF

Checksum (MD5)

b09a4d5a0b902bcc4f6c85c035ae2fb1

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback
  • Contact
  • Libraries at University of Tennessee, Knoxville
Repository logo COAR Notify