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Machine Learning Drives a Path to Defect Engineering for Suppressing Nonradiative Recombination Losses in Cu2ZnSn(S,Se)4 Solar Cells

Year: 2025

Type: article

Source: ACS Applied Materials & Interfaces

DOI: 10.1021/acsami.5c01764

Authors: Vijay C. Karade, Kuldeep Singh Gour, Mingrui He, Junsung Jang, Temujin Enkhbat, Minwoo Lee, Junho Kim, Junho Kim, Santosh S. Sutar, Tukaram D. Dongale, Randy J. Ellingson, Jae Sung Yun, Jin Hyeok Kim, Jin Hyeok Kim, Jongsung Park

Institutions: Chonnam National University, University of Toledo, Advanced Materials Corporation (United States), National Metallurgical Laboratory, Council of Scientific and Industrial Research, Academy of Scientific and Innovative Research, UNSW Sydney, Incheon National University, Shivaji University, Saveetha University, University of Surrey, Gyeongsang National University

Language: English

Topic: Chalcogenide Semiconductor Thin Films

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

Funders: Gyeongsang National University, National Research Foundation of Korea

Awards: G2635238814, G361782601, G423529737

OpenAlex ID: W4411102345

FWCI: 1.577

Cites: 50

Cited by: 7

Related to: 10