Work

Modeling of H2S solubility in ionic liquids using deep learning: A chemical structure-based approach

Year: 2021

Type: article

Source: Journal of Molecular Liquids

DOI: 10.1016/j.molliq.2021.118418

Authors: Seyed Pezhman Mousavi, Saeid Atashrouz, Reza Nakhaei-Kohani, Fahimeh Hadavimoghaddam, Ali Shawabkeh, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

Institutions: Shahid Bahonar University of Kerman, Amirkabir University of Technology, Shiraz University, Ufa State Petroleum Technological University, Northeast Petroleum University, American University of the Middle East, Jilin University

Language: English

Topic: Ionic liquids properties and applications

Subfield: Physical and Theoretical Chemistry

Field: Chemistry

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

Funder: Ministry of Education and Science of the Russian Federation

Award: G2488182671

OpenAlex ID: W4200337261

FWCI: 2.254

Cites: 80

Cited by: 38

Related to: 10