Adventures In High Dimensions: Understanding Glass For The 21ST Century
Open Access
- Author:
- Wilkinson, Collin
- Graduate Program:
- Materials Science and Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- February 23, 2021
- Committee Members:
- John C Mauro, Dissertation Advisor/Co-Advisor
John C Mauro, Committee Chair/Co-Chair
Susan B Sinnott, Committee Member
Ismaila Dabo, Committee Member
Seong Han Kim, Outside Member
John C Mauro, Program Head/Chair - Keywords:
- Glass
glass relaxation
glass-ceramics
machine learning
crystallization - Abstract:
- Glass is infinitely variable. This complexity stands as a promising technology for the 21st century since the need for environmentally friendly materials has reached a critical point due to climate change. However, such a wide range of variability makes new glass compositions difficult to design. The difficulty is only exaggerated when considering that not only is there an infinite variability in the compositional space, but also an infinite variability thermal history of a glass and in the crystallinity of glass-cearmics. This means that even for a simple binary glass there are at least 3 dimensions that have to be optimized. To resolve this difficulty, it is shown that energy landscapes can capture all three sets of complexity (composition, thermal history, and crystallinity). The explicit energy landscape optimization, however, has a large computational cost. To circumvent the cost of the energy landscape mapping, we present new research that allows for physical predictions of key properties. These methods are divided into two categories: compositional models and thermal history models. Both models for composition and thermal history are derived from energy landscapes. Software for each method is presented. As a conclusion, applications of the newly created models are discussed.