About this Abstract |
Meeting |
6th World Congress on Integrated Computational Materials Engineering (ICME 2022)
|
Symposium
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6th World Congress on Integrated Computational Materials Engineering (ICME 2022)
|
Presentation Title |
Accelerated HEA Development and Evaluation via Combined Approach of Additive Manufacturing, Machine Learning, and Thermodynamic Modeling |
Author(s) |
Phalgun Nelaturu, Jason Hattrick-Simpers, Thien Duong, Michael Moorehead, Santanu Chauduri, Adrien Couet, Dan J Thoma |
On-Site Speaker (Planned) |
Phalgun Nelaturu |
Abstract Scope |
Additive manufacturing via directed energy deposition was employed as a high-throughput technique to synthesize alloys in the Cr-Fe-Mn-Ni quaternary system. 120 alloy compositions were synthesized in a week, exploring a vast portion of the composition space. Tight compositional control within ±5 at% and <0.2% unmelted powder fraction were achieved. The rapid synthesis combined with rapid heat treatment, characterization, and nano- and micro-hardness measurements enabled high-throughput evaluation of these materials. The large dataset of experimentally measured properties were used to develop a predictive hardening model using active machine learning algorithm coupled with thermodynamic modeling. The overall high-throughput framework being developed for material discovery will be presented along with important insights into advantages of coupling blind machine learning with physics-based modeling. |
Proceedings Inclusion? |
Definite: Other |