AI-driven predictive modeling of supercritical CO<sub>2</sub> solubility using cheetah-optimized machine learning.
- DOI
- 10.3389/fmed.2026.1973985
- Published
- 2026-10-14
- Container
- Front Med (Lausanne)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fmed.2026.1973985,
title = {AI-driven predictive modeling of supercritical CO\<sub\>2\</sub\> solubility using cheetah-optimized machine learning.},
author = {Alorfi AS and Abu-Hamdeh NH.},
year = {2026},
journal = {Front Med (Lausanne)},
doi = {10.3389/fmed.2026.1973985},
url = {https://doi.org/10.3389/fmed.2026.1973985}
}RIS
TY - JOUR TI - AI-driven predictive modeling of supercritical CO<sub>2</sub> solubility using cheetah-optimized machine learning. AU - Alorfi AS AU - Abu-Hamdeh NH. PY - 2026 JO - Front Med (Lausanne) DO - 10.3389/fmed.2026.1973985 UR - https://doi.org/10.3389/fmed.2026.1973985 ER -
APA
AS, A., & NH., A. (2026). AI-driven predictive modeling of supercritical CO<sub>2</sub> solubility using cheetah-optimized machine learning.. Front Med (Lausanne). https://doi.org/10.3389/fmed.2026.1973985
Source records
- europe-pmc · retrieved 2026-11-10T11:13:15.533Z
- doaj · retrieved 2026-11-10T11:13:15.529Z