Work

Prediction of Hydrogen Solubility in Brine Using Machine Learning

Year: 2025

Type: conference-paper

Source: SPE Annual Caspian Technical Conference and Exhibition

DOI: 10.2118/230474-ms

Authors: Dilyara Sagandykova, Shams Kalam, Peyman Pourafshary, Masoud Riazi

Institution: Nazarbayev University

Language: English

Topic: Phase Equilibria and Thermodynamics

Subfield: Physical and Theoretical Chemistry

Field: Chemistry

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

OpenAlex ID: W4416590836

FWCI:

Cites: 31

Cited by:

Related to: 10