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Meeting MS&T23: Materials Science & Technology
Symposium Computational Discovery, Understanding, and Design of Multi-principal Element Materials
Presentation Title Yield Strength-Plasticity Trade-off and Uncertainty Quantification in ML-based Design of Refractory High-entropy Alloys
Author(s) Stephen Giles, Debasis Sengupta, Hugh Shortt, Peter Liaw
On-Site Speaker (Planned) Stephen Giles
Abstract Scope Development of process-structure-property relationships in materials science is an important and challenging frontier which promises improved materials and reduced time and cost in production. Refractory high entropy alloys (RHEAs) are a class of materials that are capable of excellent high-temperature properties. However, due to their multi-component nature, RHEAs have a vast composition space which presents challenges for traditional experimental exploration. Here, quantitative models of compressive yield strength and room-temperature plasticity are developed through a deep learning approach. Uncertainty quantification is performed through a variety of statistical validation techniques. Model predictions are experimentally validated through collection of recent literature and the synthesis and experimental characterization of two new, unreported RHEAs: AlMoTaTiZr and Al0.239Mo0.123Ta0.095Ti0.342Zr0.201. Finally, through the application of model interpretability, features having the greatest impact on both the mechanical property and uncertainty of the deep learning models are revealed, and shown to agree well with current physics and materials science theory.


A New Modified Embedded Atom Method Potential to Understand Plasticity in VNbTaTiZr High Entropy Alloy
Ab-Initio Investigation of Jahn-Teller Distortions within High Entropy Oxide Systems Using Recently Developed Meta-GGA Functionals
Charge-Density based Convolutional Neural Networks for Property Prediction in High Entropy Alloys
Computational Microstructural Design for Multi-phase Multi-principal Element Alloys
Computational Studies of Deformation Twinning in BCC Complex Concentrated Alloys
Critical Shear Stress Distribution and Average Dislocation Mobility in FeNiCrCoCu High Entropy Alloys Computed via Atomistic Simulations
Effect of Elasticity in Microstructural Evolution of Multi-component, Multi-phase System
Effects of Chemical Short-range Order in Medium Entropy Alloy CoCrNi
First-principles Study for Discovery of High-entropy MXenes
Hybrid Machine Learning Approach for Designing Refractory High Entropy Alloys
Microstructural Engineering via Heat Treatments in Multi-principal Element Alloy Systems with Miscibility Gaps
Modelling and Simulation on Mechanical Behavior of High-entropy Alloys
Phase Field Simulation of AgCuNi Ternary Alloy: Exploring Ag-CuNi Precipitation and Immiscibility
Predicting Ideal Shear Strength of Dilute Multicomponent Ni-based Alloys by an Integrated First-principles, CALPAHD, and Correlation Analysis
The Elastic Properties and Stacking Fault Energy of FeNiMoW
Yield Strength-Plasticity Trade-off and Uncertainty Quantification in ML-based Design of Refractory High-entropy Alloys

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