Session: 03-08-01: Integrated Computational Materials Engineering

Paper Number: 158137

158137 - Revealing Nanoscale Mechanisms of Pyrolysis at Phenolic Resin/carbon Fiber Interface via Molecular Dynamics Simulations 

Carbon-carbon composites are materials commonly used as heat shields for hypersonic applications due to their excellent mechanical and thermal shielding properties. Phenolic resins have been used as carbon matrix precursors due to high char yields of 50 – 55%. In this work,  molecular dynamics models of a phenolic resin matrix were polymerized and pyrolyzed in the presence of a graphitic layers (mimicking the surface of carbon fiber) using experimentally validated protocols to quantify the nanostructural and chemical evolution of the resin matrix as a function of distances from the resin/fiber interface. After pyrolysis, the predicted char yield was calculated to be 64 ± 0.55%, indicating the presence of the CF (graphite) surface aids in mass retention. Ring alignment analyses of the evolving pyrolyzed structures showed signs of templating as rings aligned with the graphitic layers. Filtering out non-aligned rings revealed bands of charred resin matrix equidistant from one another with a similar spacing as that of graphene layers in graphite. The methodology presented helps reveal nano length scale mechanisms of pyrolysis at resin/fiber interfaces and quantifies microstructural changes difficult to observe in situ, which is important to understand to tailor processing parameters and optimize carbon composite manufacturing for high temperature C/C relevant applications

Presenting Author: Vikas Varshney Air Force Research Laboratory

Presenting Author Biography: Dr. Vikas Varshney is a Senior Research Scientist specializing in polymer matrix composites at the Air Force Research Laboratory's Materials and Manufacturing Directorate. He holds a Ph.D. in Polymer Science from The University of Akron and has an extensive publication record with over 85 peer-reviewed articles and 7600+ citations. Dr. Varshney's research focuses on the development of multi-scale modeling and machine learning frameworks for advanced aerospace materials. His expertise spans a broad spectrum, including in-situ sensing, high-temperature resin systems, materials discovery, self-healing composites, and processing-structure-performance relationships.