General-purpose LLMs recover 96% of low-energy Elpasolites via iterative in-context learning, surpassing task-specific models on an established benchmark.
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Pith papers citing it
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cond-mat.mtrl-sci 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
QUASAR is a new autonomous LLM-based system that orchestrates multi-scale atomistic simulations and benchmarks as a general reasoning tool rather than a narrow automation script.
OptiMat Alloys is a conversational AI system that maintains a living FAIR database of multi-principal element alloy calculations and enables natural-language, on-demand computations with built-in uncertainty checks.
citing papers explorer
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General-purpose LLMs as Constrained Crystal Composition Generators
General-purpose LLMs recover 96% of low-energy Elpasolites via iterative in-context learning, surpassing task-specific models on an established benchmark.
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QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities
QUASAR is a new autonomous LLM-based system that orchestrates multi-scale atomistic simulations and benchmarks as a general reasoning tool rather than a narrow automation script.
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OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent
OptiMat Alloys is a conversational AI system that maintains a living FAIR database of multi-principal element alloy calculations and enables natural-language, on-demand computations with built-in uncertainty checks.