Data Cleansing and Sub-Unit-Based Molecular Description Enable Accurate Prediction of The Energy Levels of Non-Fullerene Acceptors Used in Organic Solar Cells

Ting Zhang, Joshua Yuk Lin Lai, Mingzhe Shi, Qing Li, Chen Zhang, He Yan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Non-fullerene acceptors (NFAs) have recently emerged as pivotal materials for enhancing the efficiency of organic solar cells (OSCs). To further advance OSC efficiency, precise control over the energy levels of NFAs is imperative, necessitating the development of a robust computational method for accurate energy level predictions. Unfortunately, conventional computational techniques often yield relatively large errors, typically ranging from 0.2 to 0.5 electronvolts (eV), when predicting energy levels. In this study, the authors present a novel method that not only expedites energy level predictions but also significantly improves accuracy, reducing the error margin to 0.06 eV. The method comprises two essential components. The first component involves data cleansing, which systematically eliminates problematic experimental data and thereby minimizes input data errors. The second component introduces a molecular description method based on the electronic properties of the sub-units comprising NFAs. The approach simplifies the intricacies of molecular computation and demonstrates markedly enhanced prediction performance compared to the conventional density functional theory (DFT) method. Our methodology will expedite research in the field of NFAs, serving as a catalyst for the development of similar computational approaches to address challenges in other areas of material science and molecular research.

Original languageEnglish
Article number2308652
Pages (from-to)1-10
JournalAdvanced Science
Volume11
Issue number17
DOIs
Publication statusPublished - 8 May 2024

Keywords

  • data cleansing
  • non-fullerene acceptors
  • organic solar cells
  • prediction of energy levels

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • General Chemical Engineering
  • General Materials Science
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • General Engineering
  • General Physics and Astronomy

Fingerprint

Dive into the research topics of 'Data Cleansing and Sub-Unit-Based Molecular Description Enable Accurate Prediction of The Energy Levels of Non-Fullerene Acceptors Used in Organic Solar Cells'. Together they form a unique fingerprint.

Cite this