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Inverse Design of Singlet-Fission Materials with Uncertainty-Controlled Genetic Optimization.

Luca Schaufelberger¹, J Terence Blaskovits¹, Ruben Laplaza^1,2

¹École polytechnique fédérale de Lausanne (EPFL), Institute of Chemical Sciences and Engineering, Lausanne, Switzerland, CH-, 1015.

Angewandte Chemie (International Ed. in English)

|September 25, 2024

Summary

Researchers developed a new algorithm to discover materials for singlet fission solar cells. This method optimizes molecular properties, accelerating the search for efficient and synthesizable singlet fission materials.

Keywords:

Genetic Algorithm Inverse Design Machine Learning Singlet Fission Uncertainty Quantification

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Area of Science:

Materials Science
Computational Chemistry
Renewable Energy

Background:

Singlet fission (SF) is a promising mechanism for enhancing solar cell efficiency.
The development of SF materials is limited by the scarcity of suitable molecular candidates.
Efficient SF materials are crucial for next-generation photovoltaic technologies.

Purpose of the Study:

To introduce an uncertainty-controlled genetic algorithm (ucGA) for accelerated discovery of SF materials.
To optimize excited state energies, synthesizability, and exciton size concurrently.
To explore vast chemical spaces for novel SF material candidates.

Main Methods:

Utilized an ensemble machine learning approach with diverse molecular representations.
Employed an uncertainty-controlled genetic algorithm (ucGA) for efficient chemical space exploration.
Leveraged the reFORMED fragment database (45,000 cores, 5,000 substituents).

Main Results:

The ucGA successfully identified novel SF material candidates in both exploitative and explorative modes.
Discovered a class of heteroatom-rich mesoionic compounds as potential SF acceptors.
These compounds exhibit favorable properties like triplet state localization and diradicaloid character.

Conclusions:

The ucGA is an effective tool for discovering high-performance SF materials.
Mesoionic compounds show promise as acceptors in charge-transfer SF systems.
Optimized SF materials can improve exciton injection into semiconductor solar cells.