A critical review of degradation pathways and stability engineering for high-efficiency non-fullerene acceptor-based organic solar cells via multiscale computational approaches.
4 affiliations
- 1Department of Chemistry, Government College University Lahore Lahore Pakistan [email protected].
- 2Department of Physics, Hafiz Hayat Campus, University of Gujrat Gujrat Pakistan.
- 3Department of Physics, Gachon University 1342 Seongnam-daero, Sujeong-gu Seongnam-si Gyeonggi-do South Korea [email protected].
- 4Dipartimento Di Architettura E Disegno Industriale Via San Lorenzo - Abazia di San Lorenzo 81031-Aversa CE Italy.
Abstract
The emergence of non-fullerene acceptors (NFAs) has significantly transformed the landscape of organic solar cells (OSCs) and paved the way for achieving unprecedented power conversion efficiencies (PCEs) and making them suitable for practical photovoltaic applications. Computational techniques, meanwhile, have become essential for the efficient discovery, screening, and optimization of new photovoltaic (PV) materials. This review gives a comprehensive summary of the recent developments in computational design and construction of NFAs with special attention to the use of computational tools in the understanding and enhancement of the structural, electronic and optoelectronic properties of NFAs. In addition, the challenges related to the stability and degradation of NFAs are briefly addressed, with prominence on how computational methods can contribute to understanding these issues. Furthermore, this review comprehensively evaluates the core computational strategies used to probe NFA degradation mechanisms specifically photostability, thermal stress, morphological evolution and oxidative pathways, and offers computational solutions to improve the long-term stability of OSC devices. As the efficiency of OSCs has approached the benchmark values, the attention towards their practical application has risen substantially. Therefore, the importance of computational techniques like density functional theory (DFT), time-dependent DFT (TD-DFT), machine learning (ML) and molecular dynamics (MD) simulations is discussed to highlight the key aspects of NFA performance including charge transport, light harvesting, device stability, and exciton dissociation. Moreover, the role of these computational tools in understanding and predicting the structure-property relationships is described, which helps in the design of new NFA materials with enhanced device performance. Finally, the breakthroughs and future perspectives in the design of NFAs using computational approaches are discussed.
Related
- Degradation Behavior of NBR Seals Exposed to Halogenated Olefins under Coupled Thermal and Mechanical Loads: A Multiscale Experimental and Computational Study
- ROLE OF HETEROCYCLIC SCAFFOLDS IN MODERN DRUG DESIGN: STRUCTURE–ACTIVITY RELATIONSHIPS, THERAPEUTIC APPLICATIONS AND EMERGING COMPUTATIONAL APPROACHES
- Integrated machine learning, pharmacophore screening, and structure-based computational approaches for the identification of novel JAK3 inhibitors
- Overlooked Roles of Oxygen in PFAS Degradation by UV/Sulfite: Mechanistic Insights and Engineering Implications
- In situ multiscale XCT degradation study of PEO-modified WE43 scaffolds: Correlating microstructure with hydrogen evolution
BibTeX
@article{quratulain2026critical,
title = {{A critical review of degradation pathways and stability engineering for high-efficiency non-fullerene acceptor-based organic solar cells via multiscale computational approaches.}},
author = {Qurat-Ul-Ain and Abdul Majid and Muhammad Tayyab Raza and Sheraz Ahmad},
journal = {RSC advances},
year = {2026},
month = oct,
doi = {10.1039/d6ra08413c},
url = {https://europepmc.org/article/MED/42953774},
note = {CC BY},
}
RIS
TY - JOUR
TI - A critical review of degradation pathways and stability engineering for high-efficiency non-fullerene acceptor-based organic solar cells via multiscale computational approaches.
AU - Qurat-Ul-Ain
AU - Abdul Majid
AU - Muhammad Tayyab Raza
AU - Sheraz Ahmad
PY - 2026
DA - 2026/10/28
JO - RSC advances
DO - 10.1039/d6ra08413c
UR - https://europepmc.org/article/MED/42953774
AB - The emergence of non-fullerene acceptors (NFAs) has significantly transformed the landscape of organic solar cells (OSCs) and paved the way for achieving unprecedented power conversion efficiencies (PCEs) and making them suitable for practical photovoltaic applications. Computational techniques, meanwhile, have become essential for the efficient discovery, screening, and optimization of new photovoltaic (PV) materials. This review gives a comprehensive summary of the recent developments in computational design and construction of NFAs with special attention to the use of computational tools in the understanding and enhancement of the structural, electronic and optoelectronic properties of NFAs. In addition, the challenges related to the stability and degradation of NFAs are briefly addressed, with prominence on how computational methods can contribute to understanding these issues. Furthermore, this review comprehensively evaluates the core computational strategies used to probe NFA degradation mechanisms specifically photostability, thermal stress, morphological evolution and oxidative pathways, and offers computational solutions to improve the long-term stability of OSC devices. As the efficiency of OSCs has approached the benchmark values, the attention towards their practical application has risen substantially. Therefore, the importance of computational techniques like density functional theory (DFT), time-dependent DFT (TD-DFT), machine learning (ML) and molecular dynamics (MD) simulations is discussed to highlight the key aspects of NFA performance including charge transport, light harvesting, device stability, and exciton dissociation. Moreover, the role of these computational tools in understanding and predicting the structure-property relationships is described, which helps in the design of new NFA materials with enhanced device performance. Finally, the breakthroughs and future perspectives in the design of NFAs using computational approaches are discussed.
SN - 2046-2069
ER -