Cover Image

Supply Risk-Aware Alloy Discovery and Design

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mulukutla, Mrinalini, Robinson, Robert, Khatamsaz, Danial, Vela, Brent, Vu, Nhu, Arróyave, Raymundo
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Materials Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes
by: Alvi, Sk Md Ahnaf Akif, et al.
Published: (2025)

Physics-Informed Gaussian Process Classification for Constraint-Aware Alloy Design
by: Hardcastle, Christofer, et al.
Published: (2025)

Microstructure-Aware Bayesian Materials Design
by: Khatamsaz, Danial, et al.
Published: (2025)

Towards Autonomous Experimentation: Bayesian Optimization over Problem Formulation Space for Accelerated Alloy Development
by: Khatamsaz, Danial, et al.
Published: (2025)

Accelerated Multi-Objective Alloy Discovery through Efficient Bayesian Methods: Application to the FCC Alloy Space
by: Hastings, Trevor, et al.
Published: (2024)

Deep Gaussian Process-based Cost-Aware Batch Bayesian Optimization for Complex Materials Design Campaigns
by: Alvi, Sk Md Ahnaf Akif, et al.
Published: (2025)

Hierarchical Gaussian Process-Based Bayesian Optimization for Materials Discovery in High Entropy Alloy Spaces
by: Alvi, Sk Md Ahnaf Akif, et al.
Published: (2024)

Visualizing High Entropy Alloy Spaces: Methods and Best Practices
by: Vela, Brent, et al.
Published: (2024)

Accelerating CALPHAD-based Phase Diagram Predictions in Complex Alloys Using Universal Machine Learning Potentials: Opportunities and Challenges
by: Zhu, Siya, et al.
Published: (2024)

Good Enough is Better: Feasibility vs. Pareto-Optimality in Alloy Design
by: Maguire, Cayden, et al.
Published: (2025)

DataScribe: An AI-Native, Policy-Aligned Web Platform for Multi-Objective Materials Design and Discovery
by: Singh, Divyanshu, et al.
Published: (2026)

Performance-driven Computational Design of Multi-terminal Compositionally Graded Alloy Structures using Graphs
by: Allen, Marshall D., et al.
Published: (2024)

Simulated Annealing-based Candidate Optimization for Batch Acquisition Functions
by: Alvi, Sk Md Ahnaf Akif, et al.
Published: (2026)

Mapping of Microstructure Transitions during Rapid Alloy Solidification Using Bayesian-Guided Phase-Field Simulations
by: Mancias, José, et al.
Published: (2025)

Influence of Coherent Elastic Strain on Phase Separation in BCC Nb-V Alloys
by: Zhu, Siya, et al.
Published: (2026)

Illustrating an Effective Workflow for Accelerated Materials Discovery
by: Mulukutla, Mrinalini, et al.
Published: (2024)

Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys
by: Zadeh, Sina Hossein, et al.
Published: (2024)

Data Driven Insights into Composition Property Relationships in FCC High Entropy Alloys
by: Flores, Nicolas, et al.
Published: (2025)

Ground-State Structure Search of Defective High-Entropy Alloys Using Machine-Learning Potentials and Monte Carlo Sampling
by: Zhu, Siya, et al.
Published: (2026)

Machine Learning-Driven Creep Law Discovery Across Alloy Compositional Space
by: Chen, Hongshun, et al.
Published: (2026)

Kolmogorov-Arnold Neural Networks for High-Entropy Alloys Design
by: Bandyopadhyay, Yagnik, et al.
Published: (2024)

Machine Learning Potentials for Alloys: A Detailed Workflow to Predict Phase Diagrams and Benchmark Accuracy
by: Zhu, Siya, et al.
Published: (2025)

Generative Inversion for Property-Targeted Materials Design: Application to Shape Memory Alloys
by: Li, Cheng, et al.
Published: (2025)

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
by: Yan, Keqiang, et al.
Published: (2025)

Synthesizability Prediction of Crystalline Structures with a Hierarchical Transformer and Uncertainty Quantification
by: Ebrahimzadeh, Danial, et al.
Published: (2025)

Enhancing Materials Discovery with Valence Constrained Design in Generative Modeling
by: Cheng, Mouyang, et al.
Published: (2025)

Uncertainty-Aware Machine-Learning Framework for Predicting Dislocation Plasticity and Stress-Strain Response in FCC Alloys
by: Luo, Jing, et al.
Published: (2025)

AlloyBERT: Alloy Property Prediction with Large Language Models
by: Chaudhari, Akshat, et al.
Published: (2024)

Learning ORDER-Aware Multimodal Representations for Composite Materials Design
by: Li, Xinyao, et al.
Published: (2026)

Autonomous Multi-objective Alloy Design through Simulation-guided Optimization
by: Yang, Penghui, et al.
Published: (2025)

Decoding Non-Linearity and Complexity: Deep Tabular Learning Approaches for Materials Science
by: Attari, Vahid, et al.
Published: (2024)

Mixed-Variable Global Sensitivity Analysis For Knowledge Discovery And Efficient Combinatorial Materials Design
by: Comlek, Yigitcan, et al.
Published: (2023)

Do Graph Neural Networks Work for High Entropy Alloys?
by: Zhang, Hengrui, et al.
Published: (2024)

PGNAA Spectral Classification of Aluminium and Copper Alloys with Machine Learning
by: Folz, Henrik, et al.
Published: (2024)

MolMiner: Towards Controllable, 3D-Aware, Fragment-Based Molecular Design
by: Ortega-Ochoa, Raul, et al.
Published: (2024)

Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates
by: Okabe, Ryotaro, et al.
Published: (2024)

Machine learning model for predicting surface wettability in laser-textured metal alloys
by: Sanandaji, Mohammad Mohammadzadeh, et al.
Published: (2026)

Physically Consistent Machine Learning for Melting Temperature Prediction of Refractory High-Entropy Alloys
by: Hasnain, Mohd
Published: (2026)

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures
by: Yan, Keqiang, et al.
Published: (2025)

Multimodal Foundation Models for Material Property Prediction and Discovery
by: Moro, Viggo, et al.
Published: (2023)