Published October 28, 2024
| Version v1
Journal article
Open
Connecting metal-organic framework synthesis to applications with multimodal machine learning
Description
This repository contains relevant data for the paper " Connecting metal-organic framework synthesis to applications with a self-supervised multimodal model", and contains the powder x-ray diffraction (PXRD) pattern data, precursor data, corresponding labels and (example) weights used for this work.
Associated article (preprint): https://doi.org/10.26434/chemrxiv-2024-mq9b4
Files
figures.zip
Files
(10.6 GB)
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md5:8320796dc59a554f1768a97025318698
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10.4 MB | Preview Download |
md5:d08ad9820e157ff4b02f65f7f504dfbe
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733.0 kB | Preview Download |
md5:78e3b7b7a576d4083d908ea4d4aa3284
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45.2 MB | Preview Download |
md5:b52903823cad441047daba0a33b53bd8
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9.7 GB | Preview Download |
md5:e4b50f5ad2e9d05a8f92c9846e73f57a
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3.4 kB | Preview Download |
md5:e6d76da936c5e74b379627a637fdf45a
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1.2 MB | Preview Download |
md5:490f859d001ab545e94263876f0e09dd
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883.1 MB | Preview Download |
Additional details
Identifiers
Funding
- Natural Sciences and Engineering Research Council
- Canada First Research Excellence Fund
- CFREF-2022-00042
- National Research Council Canada
Software
- Repository URL
- https://github.com/AI4ChemS/XRayPro
- Programming language
- Python