Compositionally Complex Ceramics for Hypersonics via Knowledge-Guided Ceramization

Abstract

This MURI program aims to understand, design, ceramize, and evaluate compositionally complex ceramics (CCCs) for hypersonic conditions based on a novel approach that seamlessly integrates experimentation, characterization, simulation, and machine learning. Polymer-derived CCCs are a unique class of high-temperature materials that can meet extreme hypersonic conditions. The research problem for realizing their full potential is a lack of understanding of the mechanistic details of the ceramization process and overall materials design strategy. Our team is uniquely positioned to address this problem, comprising expertise in precursor synthesis, ceramization, characterization, reactive force field (ReaxFF) simulation, hypersonic thermomechanical and thermochemical property assessment, and adaptive machine learning. The overarching hypothesis is that the drastic and complex polymer to CCC conversion can be quantitatively described and fundamentally understood through precise precursor synthesis, quantified ceramization, ex--in-situ characterization, reaction kinetics understanding, and hypersonic property testing, enhanced with an adaptive learning loop. This MURI program presents a ground-breaking new paradigm in CCC design, synthesis, characterization, and performance evaluation. We will provide fundamental, comprehensive, and quantitative composition-processing-structure-property understanding on CCCs as well as offer accurate guidance and prediction on their high-temperature performance. Our carefully integrated and synergetic team will not only significantly expand the application range of this family of CCC materials in harsh hypersonic applications but also enable CCCs in many other harsh environmental areas related to the Department of Defense (DoD). The strong workforce development plan will create a pipeline of students and researchers who interact with the DoD labs and consider employment opportunities in the defense sector.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2025
Source ID
FA95502410301

Entities

People

  • Kathy Lu

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Alabama at Birmingham

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Distributed Systems and Data Platform Development
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Hypersonics