OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent

TL;DR

OptiMat Alloys is a conversational, FAIR-compliant database and tool that enables on-demand exploration and screening of multi-principal element alloys using a large language model and machine learning potentials.

Contribution

It introduces a living, accessible database with integrated uncertainty quantification and natural-language interaction for alloy discovery, extending FAIR principles to on-demand knowledge generation.

Findings

Supports targeted alloy exploration with zero programming required.

Provides uncertainty estimates through cross-validation techniques.

Enables materials scientists to perform computational screening on demand.

Abstract

The FAIR principles have transformed how computational data and workflows are shared in materials research, yet existing repositories can only serve pre-computed entries -- broad coverage is perpetually incomplete and cannot adapt to new questions on demand. To address these challenges, we present OptiMat Alloys, a large language model-powered conversational agent for multi-principal element alloy exploration built on three pillars: a living database that stores every calculation with provenance, low-barrier accessibility through a web interface requiring zero programming expertise, and built-in uncertainty quantification via cross-potential and cross-configuration validation. Coupling foundational machine learning interatomic potentials covering near-all periodic table of elements with natural-language interaction, OptiMat Alloys enables targeted, on-demand computation guided by the user's domain knowledge-extending FAIR from pre-computed repositories to on-demand knowledge generation and making computational alloy screening accessible to any materials scientist.