Search

The power conversion efficiencies (PCEs) of perovskite solar cells have recently developed rapidly compared to crystalline silicon solar cells. To have an effective way to control the crystallization of perovskite thin films is the key for achieving good device performance. However, a paradox in perovskite crystallization is from the mismatch between nucleation and Oswald ripening. Usually, the large numbers of nucleation sites tend to weak Oswald ripening. Here, we proposed a new mechanism to promote the formation of nucleation sites by reducing surface energy from 44.9 mN/m to 36.1 mN/m, to spontaneously accelerate the later Oswald ripening process by improving the grain solubility through the elastic modulus regulation. The ripening rate is increased from 2.37 Åm ⋅ s−1 to 4.61 Åm ⋅ s−1 during annealing. Finally, the solar cells derived from the optimized films showed significantly improved PCE from 23.14 % to 25.32 %. The long‐term stability tests show excellent thermal stability (the optimized device without encapsulation maintaining 82 % of its initial PCE after 800 h aging at 85 °C) and an improved light stability under illumination. This work provides a new method, the elastic modulus regulation, to enhance the ripening process. [ABSTRACT FROM AUTHOR]

Perovskite solar cells (PSCs) with excellent photoelectric properties have attracted much attention in recent years. However, the solution manufacturing of PSCs inevitably introduces a large number of defects (both bulk and surface defects), which seriously affect the performance of PSCs. Defect passivation from additive engineering is an effective and simple strategy. Among these additives, polymers are increasingly attracting attention due to their excellent properties, such as adjustable structures, multiple functional groups, excellent stability, and low cost, which can further promote the commercialization of PSC technology. However, the application of polymers in PSCs have encountered some obstacles due to a lack of systematic studies, such as unelucidated interactions between polymers and perovskites, the frequent trial‐and‐error process used in material selection, and the lack of effective guidelines. In this review, the application of polymers in various layers of PSCs devices is first summarized. Then, three main roles of polymers in PSCs are summarized, including crystallization regulation, the mechanical stability enhancement of flexible perovskite solar cells (FPSCs), and their use as undoped hole transport materials (HTMs). More importantly, machine learning (ML) is proposed to design and select polymers as passivators and HTMs for PSCs. Finally, promising guidelines and recommendations are provided for the commercialization of PSCs. [ABSTRACT FROM AUTHOR]

Understanding the key factor driving the efficiency and stability of semiconductor devices is vital. To date, the key factor influencing the long‐term stability of perovskite solar cells (PSCs) remains unknown because of the many influencing factors. In this work, through machine learning, the influences of five factors, including grain size, defect density, bandgap, fluorescence lifetime, and surface roughness, on the efficiency and stability of PSCs have been revealed. It is found that the bandgap has the greatest influence on the efficiency, and the surface roughness and grain size are most influential to the long‐term stability. A mathematical model is given to predict efficiency based on fluorescence lifetime and bandgap. Guided by the model, four groups of experiments are conducted to confirm the machine‐learning predictions and a PSC with 23.4% efficiency and excellent long‐term stability is obtained, as manifested by retention of 97.6% of the initial efficiency after 3288 h aging in the ambient environment, the best stability under these conditions. This work shows that machine learning is an effective means to enrich semiconductor physical models. [ABSTRACT FROM AUTHOR]