Lab Home | Phone | Search
	Center for Nonlinear Studies
	Home  ▶ People   CNLS Staff Members   Executive Committee   Postdocs   Visitors   Students   Research   Publications  ▶ Conferences   Workshops   Sponsorship  ▶ Talks   Seminars   Postdoc Seminars Archive   Quantum Lunch   Quantum Lunch Archive   P/T Colloquia   Archive   Ulam Scholar   Anastasio Fellow   Fellow Program    ▶ Student Requests        Student Program  ▶ Visitor Requests   Description   Past Visitors  ▶ Services   General     History of CNLS     Maps, Directions   T-Division   LANL				Monday, August 07, 20233:00 PM - 4:00 PMCNLS Conference Room (TA-3, Bldg 1690) Colloquium Accelerated Alloy Discovery and Optimization through the Batch-wise Improvement in Reduced Design Space using a Holistic Optimization Technique (BIRDSHOT) Raymundo ArroyaveTexas A&M University The Refractory High Entropy Alloy (RHEA) space is vast, and it is impossible to explore using conventional approaches to materials discovery. In this talk, I will present the Batch-wise Improvement in Reduced Design Space using a Holistic Optimization Technique (BIRDSHOT) framework. BIRDSHOT incorporates the strengths of ICME and combinatorial methods while addressing all their drawbacks, as it: (i) employs novel machine learning (ML) and data-driven search algorithms to identify efficiently the feasible regions amenable to optimization; (ii) exploits correlations to fuse simulations and experiments to obtain efficient ML models for predicting PSPP relations; (iii) uses Bayesian Optimization (BO) to make globally optimal iterative decisions regarding which region in the RHEA space to explore/exploit, leveraging existing models and data; (iv) is capable of carrying out multiple optimal parallel queries to the design space. We show how we have been using BIRDSHOT to search for next-generation refractory alloys for turbine engine applications. Host: Jan Janssen, T-1