{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/14-examples-of-how-llms-can-transform","title":"14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon","arxiv_id":"2306.06283","date":"2023-06-09","proceeding":null,"authors":["Kevin Maik Jablonka","Qianxiang Ai","Alexander Al-Feghali","Shruti Badhwar","Joshua D. Bocarsly","Andres M Bran","Stefan Bringuier","L. Catherine Brinson","Kamal Choudhary","Defne Circi","Sam Cox","Wibe A. de Jong","Matthew L. Evans","Nicolas Gastellu","Jerome Genzling","María Victoria Gil","Ankur K. Gupta","Zhi Hong","Alishba Imran","Sabine Kruschwitz","Anne Labarre","Jakub Lála","Tao Liu","Steven Ma","Sauradeep Majumdar","Garrett W. Merz","Nicolas Moitessier","Elias Moubarak","Beatriz Mouriño","Brenden Pelkie","Michael Pieler","Mayk Caldas Ramos","Bojana Ranković","Samuel G. Rodriques","Jacob N. Sanders","Philippe Schwaller","Marcus Schwarting","Jiale Shi","Berend Smit","Ben E. Smith","Joren Van Herck","Christoph Völker","Logan Ward","Sean Warren","Benjamin Weiser","Sylvester Zhang","Xiaoqi Zhang","Ghezal Ahmad Zia","Aristana Scourtas","KJ Schmidt","Ian Foster","Andrew D. White","Ben Blaiszik"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2306.06283v4","url_pdf":"https://arxiv.org/pdf/2306.06283v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"14-examples-of-how-llms-can-transform","repo_url":"https://github.com/qai222/llm_organic_synthesis","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"14-examples-of-how-llms-can-transform","repo_url":"https://github.com/doncamilom/bollama","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"large-language-model","task_name":"Large Language Model"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"gpt-4","method_name":"GPT-4"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2306.06283","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.06283"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/doncamilom/bollama","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/qai222/llm_organic_synthesis","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":8},"by_repo_kind":{"official":{"samples":8,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"d61b864ce3c844ab","entry":"calculate_tokens","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"workplace_cot/cot_gpt.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/workplace_cot/cot_gpt.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d61b864ce3c844ab"}},{"code_sha256_prefix":"e75452a76d4fed91","entry":"convert_entries","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"hackathon/models_openai/convert_data_to_openai_format.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/hackathon/models_openai/convert_data_to_openai_format.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e75452a76d4fed91"}},{"code_sha256_prefix":"7fe51e1fe114abe7","entry":"flatten","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"ord/utils.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/ord/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"7fe51e1fe114abe7"}},{"code_sha256_prefix":"c75d1f1ed97dc9dd","entry":"get_completion","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"hackathon/models_openai/inference.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/hackathon/models_openai/inference.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c75d1f1ed97dc9dd"}},{"code_sha256_prefix":"9505b9029260a857","entry":"get_cot_prompt","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"workplace_cot/cot_gpt.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/workplace_cot/cot_gpt.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9505b9029260a857"}},{"code_sha256_prefix":"dea6a20d32fd9e3a","entry":"get_dict_depth","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"ord/utils.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/ord/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"dea6a20d32fd9e3a"}},{"code_sha256_prefix":"e0a842f2f35e6139","entry":"json_load","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"workplace_cde/cde.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/workplace_cde/cde.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e0a842f2f35e6139"}},{"code_sha256_prefix":"66dc4c7f1fb25b5e","entry":"simple_open","repo":"qai222/llm_organic_synthesis","repo_kind":"official","path":"demo_apps/dash_app/synthesis_parser.py","file_url":"https://github.com/qai222/llm_organic_synthesis/blob/HEAD/demo_apps/dash_app/synthesis_parser.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"66dc4c7f1fb25b5e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}