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Royal Society of Chemistry, Journal of Materials Chemistry A: materials for energy and sustainability, 28(9), p. 15684-15695, 2021

DOI: 10.1039/d1ta04742f

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A time and resource efficient machine learning assisted design of non-fullerene small molecule acceptors for P3HT-based organic solar cells and green solvent selection

Journal article published in 2021 by Asif Mahmood ORCID, Jin-Liang Wang ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

A time and money efficient machine learning assisted design of non-fullerene small molecule acceptors for P3HT based organic solar cells is reported. Green solvents are also selected using machine learning predicted Hansen solubility parameters.