Machine learning–based prediction of paracetamol solubility and CO₂ density in supercritical systems using artificial rabbits optimization
- DOI
- 10.1038/s41598-026-55333-y
- Published
- 2026-06-10
- 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/s41598-026-55333-y,
title = {Machine learning–based prediction of paracetamol solubility and CO₂ density in supercritical systems using artificial rabbits optimization},
author = {Hadil Faris Alotaibi and Arwa Omar Al Khatib and Junainah Abd Hamid and Subbulakshmi Ganesan and Aman Shankhyan and Rajashree Panigrahi and Fadhil Faez Sead and Aashna Sinha},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-55333-y},
url = {https://doi.org/10.1038/s41598-026-55333-y}
}RIS
TY - JOUR TI - Machine learning–based prediction of paracetamol solubility and CO₂ density in supercritical systems using artificial rabbits optimization AU - Hadil Faris Alotaibi AU - Arwa Omar Al Khatib AU - Junainah Abd Hamid AU - Subbulakshmi Ganesan AU - Aman Shankhyan AU - Rajashree Panigrahi AU - Fadhil Faez Sead AU - Aashna Sinha PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-55333-y UR - https://doi.org/10.1038/s41598-026-55333-y ER -
APA
Alotaibi, H. F., Khatib, A. O. A., Hamid, J. A., Ganesan, S., Shankhyan, A., Panigrahi, R., Sead, F. F., & Sinha, A. (2026). Machine learning–based prediction of paracetamol solubility and CO₂ density in supercritical systems using artificial rabbits optimization. Scientific Reports. https://doi.org/10.1038/s41598-026-55333-y
Source records
- crossref · retrieved 2026-09-26T23:17:03.232Z