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Computational Materials Science Lab

Texas A&M University College of Engineering

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

  • MSGalaxy Platform Workflow Design August 16, 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
  • Constraint Satisfaction Problem Approach to Materials Design and Discovery March 27, 2017
  • Computational Design of High Strength Steels October 29, 2016

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