mlsanityData to 14 Oct 2026

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon

arXiv 2306.06283 ↗First posted 9 Jun 2023cond-mat.mtrl-sci cs.LG physics.chem-phcited by 86

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Abstract (arXiv)

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.

Key facts. Cited by 86 papers in the map (data through 14 Oct 2026). Builds on 42 of its 158 references that are in the map. First posted on arXiv 9 Jun 2023.

Builds on

42 of 158 references.

References · 42

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30 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 9; 2024: 28; 2025: 33; 2026: 16.

86 papers.

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  1. 2025Towards Scientific Intelligence: A Survey of LLM-based Scientific Agentscited by 98
  2. 2024Evolutionary Computation in the Era of Large Language Model: Survey and Roadmapcited by 90
  3. 2024Instruction Backdoor Attacks Against Customized LLMscited by 62
  4. 2024HoneyComb: A Flexible LLM-Based Agent System for Materials Sciencecited by 57
  5. 2024A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?cited by 48
  6. 2024SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretationcited by 48
  7. 2024Are LLMs Ready for Real-World Materials Discovery?cited by 40
  8. 2024AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligencecited by 36
  9. 2024Are large language models superhuman chemists?cited by 34
  10. 2024Probing the limitations of multimodal language models for chemistry and materials researchcited by 32
  11. 2024Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planningcited by 29
  12. 2024Materials science in the era of large language models: a perspectivecited by 24
38 more
  1. 2025MDCrow: Automating Molecular Dynamics Workflows with Large Language Modelscited by 22
  2. 2024ChatGPT as Research Scientist: Probing GPT's Capabilities as a Research Librarian, Research Ethicist, Data Generator and Data Predictorcited by 21
  3. 2024When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challengescited by 20
  4. 2023ChatMOF: An Autonomous AI System for Predicting and Generating Metal-Organic Frameworkscited by 17
  5. 2024Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Surveycited by 17
  6. 2024Large Language Models as Software Components: A Taxonomy for LLM-Integrated Applicationscited by 17
  7. 2024ChIRAAG: ChatGPT Informed Rapid and Automated Assertion Generationcited by 16
  8. 2023An Interdisciplinary Outlook on Large Language Models for Scientific Researchcited by 15
  9. 2024Assessing Large Language Models in Mechanical Engineering Education: A Study on Mechanics-Focused Conceptual Understandingcited by 15
  10. 2025MatSciBench: Benchmarking the Reasoning Ability of Large Language Models in Materials Sciencecited by 15
  11. 2024PRESTO: Progressive Pretraining Enhances Synthetic Chemistry Outcomescited by 14
  12. 2023Transformers and Large Language Models for Chemistry and Drug Discoverycited by 13
  13. 2025Large language models as uncertainty-calibrated optimizers for experimental discoverycited by 13
  14. 2025Zephyrus: An Agentic Framework for Weather Sciencecited by 10
  15. 2024Generative AI and Process Systems Engineering: The Next Frontiercited by 9
  16. 2024Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictionscited by 9
  17. 202534 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discoverycited by 9
  18. 2025ChemPile: A 250GB Diverse and Curated Dataset for Chemical Foundation Modelscited by 9
  19. 2023HW-V2W-Map: Hardware Vulnerability to Weakness Mapping Framework for Root Cause Analysis with GPT-assisted Mitigation Suggestioncited by 8
  20. 2025MatLLMSearch: Crystal Structure Discovery with Evolution-Guided Large Language Modelscited by 7
  21. 2026MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamicscited by 7
  22. 2023Image and Data Mining in Reticular Chemistry Using GPT-4Vcited by 6
  23. 2024Learning Electromagnetic Metamaterial Physics With ChatGPTcited by 6
  24. 2025Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applicationscited by 6
  25. 2024LLeMpower: Understanding Disparities in the Control and Access of Large Language Modelscited by 5
  26. 2025Bridging Molecular Graphs and Large Language Modelscited by 5
  27. 2025Scaling Laws in Scientific Discovery with AI and Robot Scientistscited by 5
  28. 2025A Multi-Task Evaluation of LLMs' Processing of Academic Text Inputcited by 5
  29. 2023Future-proofing geotechnics workflows: accelerating problem-solving with large language modelscited by 4
  30. 2024Minstrel: Structural Prompt Generation with Multi-Agents Coordination for Non-AI Expertscited by 4
  31. 2024ProtoMed-LLM: An Automatic Evaluation Framework for Large Language Models in Medical Protocol Formulationcited by 4
  32. 2025GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocolscited by 4
  33. 2024KBAlign: Efficient Self Adaptation on Specific Knowledge Basescited by 3
  34. 2025Towards an automated workflow in materials science for combining multi-modal simulative and experimental information using data mining and large language modelscited by 3
  35. 2025Survey on Recent Progress of AI for Chemistry: Methods, Applications, and Opportunitiescited by 3
  36. 2025ChemOrch: Empowering LLMs with Chemical Intelligence via Synthetic Instructionscited by 3
  37. 2025SynthStrategy: Extracting and Formalizing Latent Strategic Insights from LLMs in Organic Chemistrycited by 3
  38. 2026MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentialscited by 3

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