Applications & products
GBClaw: An agentic AI framework for atomistic grain boundary research and mechanistic discovery
An arXiv abstract presents GBClaw, a modular agentic framework that studied 14 asymmetric tilt grain boundaries in nickel.
Why it matters: For agent builders, GBClaw is an example of an architecture that combines iterative planning with domain tools and simulation interfaces for a mechanistic research workflow. For materials researchers, the reported follow-up connects a surprising shear-resistance result to metastable structures, while the evidence here is limited to the paper’s abstract.