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Computational Materials Science Lab

Texas A&M University College of Engineering

Research

Materials Design and Discovery

Constraint Satisfaction Problem Approach to Materials Design and Discovery

In order to come closer to materials design and discovery without having to rely on exhaustive computational/experimental approaches, the constraint satisfaction problem (CSP) approach is used. This approach uses efficient searching algorithms to evaluateĀ a design space against user-defined constraints, such as phase stability. Currently, the CSP approach has been coupled with Thermo-Calc software to search high-entropy alloy systems as well as liquid-metal dealloying systems. The CSP algorithm is provided by the Design Systems Lab from Mechanical Engineering and the work on liquid-metal dealloying systems is a collaboration with the Demkowicz Group from Materials Science and Engineering.

ResultsĀ of a single-phase search with the CSP in a near-equiatomic ternary (green is HCP, blue is BCC)

Latest News

  • Co-Ni-Ga HTSMAs October 29, 2016
  • Computational Design of High Strength Steels October 29, 2016
  • Constraint Satisfaction Problem Approach to Materials Design and Discovery March 27, 2017
  • Control of Variability in the Performance of Selective Laser Melting (SLM) Parts through Microstructure Control and Design March 28, 2017
  • Design/Optimization Under Uncertainty using Bayesian inferences March 27, 2017

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