activity
20232026
most citedActive and transfer learning with partially Bayesian neural networks for materials and chemicals

9 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2026

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

Andrew Ritchhart, Sarah I. Allec, Pravalika Butreddy +5

We present a multi-agentic workflow for critical materials recovery that deploys a series of AI agents and automated instruments to recover critical materials from produced water a…

cs.AI2025★ 5 cited

Operationalizing Serendipity: Multi-Agent AI Workflows for Enhanced Materials Characterization with Theory-in-the-Loop

Lance Yao, Suman Samantray, Ayana Ghosh +4

The history of science is punctuated by serendipitous discoveries, where unexpected observations, rather than targeted hypotheses, opened new fields of inquiry. While modern autono…

cond-mat.dis-nn2025★ 9 cited

Active and transfer learning with partially Bayesian neural networks for materials and chemicals

Sarah I. Allec, Maxim Ziatdinov

Active learning, an iterative process of selecting the most informative data points for exploration, is crucial for efficient characterization of materials and chemicals property s…

cond-mat.mtrl-sci2024

Towards Informatics-Driven Design of Nuclear Waste Forms

Vinay I. Hegde, Miroslava Peterson, Sarah I. Allec +11

Informatics-driven approaches, such as machine learning and sequential experimental design, have shown the potential to drastically impact next-generation materials discovery and d…

cond-mat.mtrl-sci2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Sarah I. Allec, Xiaonan Lu, Daniel R. Cassar +8

Glasses form the basis of many modern applications and also hold great potential for future medical and environmental applications. However, their structural complexity and large c…

cond-mat.mtrl-sci2023★ 1 cited

A case study of multi-modal, multi-institutional data management for the combinatorial materials science community

Sarah I. Allec, Eric S. Muckley, Nathan S. Johnson +9

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functio…