About this Abstract |
| Meeting |
MS&T26: Materials Science & Technology
|
| Symposium
|
Progress in High Entropy Materials: Integrating Experiments, Computation, and Machine Learning
|
| Presentation Title |
A Computational Framework for BCC–B2 Precipitation Strengthening in High Entropy Alloys |
| Author(s) |
Mikayla Obrist, Bernard Gaksey, Arindam Debnath, Janith Wanni, Ben Neuman, Avanish Mishra, Nithin Mathew, Tim Germann, Saryu Fensin |
| On-Site Speaker (Planned) |
Mikayla Obrist |
| Abstract Scope |
High entropy alloys (HEAs) are often designed as solid solution systems, but this approach can limit achievable strength–ductility combinations. Precipitation strengthening offers a promising alternative. However, experimental studies typically focus on individual alloy systems within narrow compositional spaces, highlighting the need for broader thermodynamic and kinetic screening approaches. In this work, an automated computational framework is developed to identify HEAs capable of B2 precipitation strengthening and determine corresponding heat treatment conditions. Candidate compositions are first filtered using a prior manufacturability screening approach that identifies alloys with potential for forming B2 precipitates in a BCC matrix. These compositions are then evaluated using CALPHAD to identify solutionizing and aging temperature windows based on phase stability. Precipitation kinetics simulations are used to assess viability. A physically informed metric combining precipitate volume fraction, number density, and particle size defines a near-optimal aging window, from which a representative aging time is selected. |
