FermiLink is a unified AI agent framework that automates multidomain scientific simulations via separated package knowledge bases and a four-layer progressive disclosure mechanism, reproducing 56% of target figures in benchmarks and generating research-grade results on unpublished problems.
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Dreams: Density functional theory based research engine for agentic materials simulation
13 Pith papers cite this work. Polarity classification is still indexing.
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Lang2MLIP is an LLM multi-agent framework that automates end-to-end development of machine learning interatomic potentials from natural language input for heterogeneous materials systems.
El Agente Quntur is a new multi-agent system that uses reasoning over literature and software documentation to autonomously handle the full workflow of quantum chemistry experiments in ORCA.
AutoDFT presents a closed-loop multi-agent LLM framework achieving 94.1% success on a 34-task DFT benchmark and reliable property predictions on materials databases.
TSAgent automates transition state searches at DFT accuracy via an agentic loop, reaching 83% success on 100 OC20NEB examples and 70% on 10 held-out cases versus 73% for human experts.
An LLM-orchestrated framework automates the full XANES workflow from natural language to normalized spectra and curated data.
An LLM agent autonomously runs read-plan-compute-compare loops on 111 computational physics papers, raising substantive concerns in 42% of them (97.7% only after execution), and generates a full publishable Comment revising the headline conclusion of a Nature Communications paper on 2D-material MOFs
LLM syntax accuracy for LAMMPS scripts improved to 91% parser pass rate, yet only 1/80 scripts were scientifically correct on the hardest prompt; an agentic verification skill raised success to 5/6.
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.
El Agente Estructural is a new multimodal agent that performs natural-language-driven 3D molecular geometry editing and generation using integrated domain tools and vision-language models.
LARA-HPC introduces a validation-first agentic system with dry-run verification and multi-phase refinement that improves robustness of AI-generated DFT workflows on HPC systems.
RADIANT-LLM is a local-first multi-modal RAG system with provenance tracking that delivers lower hallucination rates than general LLMs on nuclear engineering benchmarks.
Introduces a scalable AI skill framework for autonomous microkinetics discovery that automates workflows and evaluates surrogate reliability.
citing papers explorer
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AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations
AutoDFT presents a closed-loop multi-agent LLM framework achieving 94.1% success on a 34-task DFT benchmark and reliable property predictions on materials databases.
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ChemGraph-XANES: An Agentic Framework for XANES Simulation and Analysis
An LLM-orchestrated framework automates the full XANES workflow from natural language to normalized spectra and curated data.
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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.