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disclosure mechanism, reproducing 56% of target figures in benchmarks and generating research-grade results on unpublished problems.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
14 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.
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.
Paimon is an agentic framework that automates atomistic simulations and improves reliability by suppressing silent errors in agent workflows, demonstrated on liquid electrolyte cases and literature reproduction.
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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FermiLink: A Unified Agent Framework for Multidomain Autonomous Scientific Simulations
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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Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows
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.
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El Agente Quntur: A research collaborator agent for quantum chemistry
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.
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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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TSAgent: An Agentic Workflow for Autonomous Transition State Search
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.
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Evaluating LLM-generated code for domain-specific languages: molecular dynamics with LAMMPS
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.
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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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El Agente Estructural: An Artificially Intelligent Molecular Editor
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.
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A Robust Agentic Framework for Expert-Level Automation of Atomistic Simulations
Paimon is an agentic framework that automates atomistic simulations and improves reliability by suppressing silent errors in agent workflows, demonstrated on liquid electrolyte cases and literature reproduction.
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LARA: Validation-Driven Agentic Supercomputer Workflows for Atomistic Modeling
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.
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RADIANT-LLM: an Agentic Retrieval Augmented Generation Framework for Reliable Decision Support in Safety-Critical Nuclear Engineering
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.
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Toward Exascale AI for Science: A Scalable AI Skill for Autonomous Microkinetics Discovery
Introduces a scalable AI skill framework for autonomous microkinetics discovery that automates workflows and evaluates surrogate reliability.
- ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation
- Grounded autonomous scrutiny at scale: emergent critique from reproduction of published computational physics papers