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.<br><br>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.<br>