A critical review of degradation pathways and stability engineering for high-efficiency non-fullerene acceptor-based organic solar cells via multiscale computational approaches

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.