Work

Machine‐Learning‐Based Design of Organic Chromophores with Improved Photovoltaic Efficiency

Year: 2025

Type: article

Source: ChemistrySelect

DOI: 10.1002/slct.202503160

Authors: Hussein A.K. Kyhoiesh, Masar A. Awad, Karrar H. Salem, Azal S. Waheeb, Ahmed A. Al‐Kubaisi, Gaber A. M. Mersal, Islam H. El Azab, Mohamed H.H. Mahmoud, Zainab J. Hamoodah, Zainab A. Abass

Institutions: National University of Science and Technology, Al-Muthanna University, Al-Zahraa University for Women, Al-Ayen Iraqi University, University of Al Maarif, Taif University, Mazaya University College, Al-Mustaqbal University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

OpenAlex ID: W4414717463

FWCI: 0.359

Cites: 49

Cited by: 2

Related to: 10