Multimodal graph-based deep learning for predicting heat of combustion as a key hazard indicator under GHS/CLP standards
- DOI
- 10.1038/s41598-026-60540-8
- Published
- 2026-07-19
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-60540-8,
title = {Multimodal graph-based deep learning for predicting heat of combustion as a key hazard indicator under GHS/CLP standards},
author = {Osita Sunday Nnyigide and Haewon Byeon and Uchenna Esther Okpete},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-60540-8},
url = {https://doi.org/10.1038/s41598-026-60540-8}
}RIS
TY - JOUR TI - Multimodal graph-based deep learning for predicting heat of combustion as a key hazard indicator under GHS/CLP standards AU - Osita Sunday Nnyigide AU - Haewon Byeon AU - Uchenna Esther Okpete PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-60540-8 UR - https://doi.org/10.1038/s41598-026-60540-8 ER -
APA
Nnyigide, O. S., Byeon, H., & Okpete, U. E. (2026). Multimodal graph-based deep learning for predicting heat of combustion as a key hazard indicator under GHS/CLP standards. Scientific Reports. https://doi.org/10.1038/s41598-026-60540-8
Source records
- crossref · retrieved 2026-09-26T04:45:29.924Z