Multimodal graph-based deep learning for predicting heat of combustion as a key hazard indicator under GHS/CLP standards

Osita Sunday Nnyigide, Haewon Byeon, Uchenna Esther Okpete

Open source

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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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

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