| About this Abstract |
| Meeting |
MS&T22: Materials Science & Technology
|
| Symposium
|
Advances in Dielectric Materials and Electronic Devices
|
| Presentation Title |
Leveraging Coupled-Cluster Techniques to Predict Pre-Cursor Material Improvements |
| Author(s) |
Matthew Trippy, Maximillian Estrada, Sean Garnsey, Paul Flynn, Amar Bhalla, Ruyan Guo |
| On-Site Speaker (Planned) |
Matthew Trippy |
| Abstract Scope |
Advancements in material science invariably rely on a blending of well-designed and controlled experimentation, with a careful study of the key theoretical principles that define the most significant parameters that present challenges and opportunities for complex, multi-step material construction methods of modern materials and devices. Simulation of expected performance of a variety of pre-cursor materials is explored jointly with the principal investigators of an additive hybrid 3D (H3D) fabrication process for deposition of Zinc Oxide (ZnO) films, in order to accelerate the selection of candidate materials and processing conditions for experimentation. This serves both to identify optimal conditions for desired film properties, as well as to provide continuous improvement in the in-house numerical tools and methods for complex material investigations through prediction of key characteristics of the desired compounds. |