5 papers
Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap
Rafael Ferreira da Silva, Milad Abolhasani, Peter Beaucage +25
The paper updates a community roadmap for autonomous scientific laboratories, emphasizing trust, verification, reproducibility, safety, security, and governance as central challeng…
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…
AIMD-L: An automated laboratory for high-throughput characterization of structural materials for extreme environments
Todd C. Hufnagel, Pranav Addepalli, Anuruddha Bhattacharjee +14
Rapid developments in artificial intelligence and machine learning as applied to materials science are creating an urgent need for experimental data, which can be provided by high-…
Automated laboratory x-ray diffractometer and fluorescence spectrometer for high-throughput materials characterization
Hyun Sang Park, Timothy Long, Michael Wall +8
The increasing importance of artificial intelligence and machine learning in materials research has created demand for automated, high-throughput characterization techniques capabl…
Datatractor: Metadata, automation, and registries for extractor interoperability in the chemical and materials sciences
Matthew L. Evans, Gian-Marco Rignanese, David Elbert +1
Two key issues hindering the transition towards FAIR data science are the poor discoverability and inconsistent instructions for the use of data extractor tools, i.e., how we go fr…