Litcius/Paper detail

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

Asif Mahmood, Jin‐Liang Wang

2021Journal of Materials Chemistry A207 citationsDOI

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.

Topics & Concepts

FullereneOrganic solar cellSolubilityOrganic moleculesResource (disambiguation)SolventMoleculeSelection (genetic algorithm)Computer scienceMaterials scienceNanotechnologyBiochemical engineeringArtificial intelligenceChemistryOrganic chemistryPolymerEngineeringComputer networkOrganic Electronics and PhotovoltaicsMachine Learning in Materials ScienceConducting polymers and applications
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 | Litcius