Predictive Modeling of Polymer-Derived Ceramics: Discovering Methods for the Design and Fabrication of Complex Disordered Solids

This new project aims to develop a general, simulation-driven methodology for accurately recreating the atomic structure of substructure-containing amorphous solids and mapping resultant structures and properties back to fabrication conditions, ultimately enabling a computational design capability.

The project combines state of the art computational techniques (AIMD, HRMC), modern optimization algorithms (e.g. artificial neural networks (ANNs), particle swarm optimization (PSO)), specialized experimental characterization techniques, (solid-state nuclear magnetic resonance (NMR), 4-dimensional scanning transmission electron microscopy (4D-STEM)), and advanced thin-film fabrication technology (plasma enhanced chemical vapor deposition (PECVD)). We will use a collection of thin-film amorphous preceramic polymers (a-BC:H, a-SiBCN:H, and a-SiCO:H) as suitably complex and technologically relevant case studies.