Innovative computational framework for Sr<sub>3</sub>SbCl<sub>3</sub> absorber optimization: DFT, SCAPS-1D, and machine learning perspectives
Recent progress in solar technology has drawn attention to novel inorganic cubic perovskites like Sr 3 SbCl 3 , due to their excellent physical properties and solar cell potential, as supported by machine learning (ML) insights.
Authors
- Q. Mohsen
- Hafizur Rahman (ORCID: https://orcid.org/0000-0003-1108-9816)
- Mohd Taukeer Khan (ORCID: https://orcid.org/0000-0002-6715-4501)
- Samah Saidi (ORCID: https://orcid.org/0000-0002-6030-2380)
- Noureddine Ali Elboughdiri (ORCID: https://orcid.org/0000-0003-2923-3062)
- Abdel Majid A. Adam (ORCID: https://orcid.org/0000-0001-8938-4407)
- Md. Sharif Uddin (ORCID: https://orcid.org/0000-0001-8314-9473)
- Md. Azizur Rahman (ORCID: https://orcid.org/0009-0002-3937-4977)
- Bhupoti Bhushan Sarkar
- Jothiramalingam Rajabathar
- Abdulaziz A. Alshihri
Institutions
- Prince Sattam Bin Abdulaziz University (SA)
- Begum Rokeya University (BD)
- Taif University (SA)
- University of Ha'il (SA)
- Islamic University of Madinah (SA)
- King Khalid University (SA)
- Saveetha University (IN)
Publication Details
- Journal
- New Journal of Chemistry
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5nj01823d
- Citations
- 14
- Primary Topic
- Optical properties and cooling technologies in crystalline materials
- Type
- article
- Field-Weighted Citation Impact
- 17.45