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14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Authors: Imran, Alishba; Schwarting, Marcus; Jablonka, Kevin Maik; Ai, Qianxiang; Al-Feghali, Alexander; Badhwar, Shruti; Bocarsly, Joshua D.; +49 Authors

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Abstract

We report the findings of a hackathon focused on exploring the diverse applications of large language models in molecular and materials science.

Keywords

Chemical Physics (physics.chem-ph), FOS: Computer and information sciences, 3403 Macromolecular and Materials Chemistry, Condensed Matter - Materials Science, Computer Science - Machine Learning, 34 Chemical Sciences, FOS: Clinical medicine, Ensure access to affordable, reliable, sustainable and modern energy for all, Neurosciences, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Gene Expression, 004, Macromolecular and Materials Chemistry, Machine Learning (cs.LG), Imaging, Chemistry, Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation, Physics - Chemical Physics, Chemical Sciences, Synthetic Biology, Microfabrication & Bioengineering, Genetics & Genomics

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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    download downloads 160
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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
70
Top 1%
Top 10%
Top 1%
63
160
Green
gold