13 citations · 15 across the 5 of their papers we have counts for
5 papers
A BRAVE Alloy Design Campaign (Bayesian Risk-aware Alloy discoVery and Exploration)
Mrinalini Mulukutla, Danial Khatamsaz, Trevor Hastings +23
In constrained alloy optimization, the compositions with the highest performance potential often reside at the boundary of phase stability -- where the risk of experimental failure…
Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes
Sk Md Ahnaf Akif Alvi, Mrinalini Mulukutla, Nicolas Flores +6
Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys(HEAs), especially when integrating computational predi…
Supply Risk-Aware Alloy Discovery and Design
Mrinalini Mulukutla, Robert Robinson, Danial Khatamsaz +3
Materials design is a critical driver of innovation, yet overlooking the technological, economic, and environmental risks inherent in materials and their supply chains can lead to…
Illustrating an Effective Workflow for Accelerated Materials Discovery
Mrinalini Mulukutla, A. Nicole Person, Sven Voigt +26
Algorithmic materials discovery is a multi-disciplinary domain that integrates insights from specialists in alloy design, synthesis, characterization, experimental methodologies, c…
Accelerated Multi-Objective Alloy Discovery through Efficient Bayesian Methods: Application to the FCC Alloy Space
Trevor Hastings, Mrinalini Mulukutla, Danial Khatamsaz +14
This study introduces BIRDSHOT, an integrated Bayesian materials discovery framework designed to efficiently explore complex compositional spaces while optimizing multiple material…