Advancing of the lead halide perovskite solar cells towards photovoltaic market demands large-scale devices of high-power conversion efficiency, high reproducibility and stability via low-cost fabrication technology, and in particular resistance to humid environment for long-time operation. Here we achieve uniform perovskite film based on a novel polymer-scaffold architecture via a mild-temperature process. These solar cells exhibit efficiency of up to ∼16% with small variation. The unencapsulated devices retain high output for up to 300 h in highly humid environment (70% relative humidity). Moreover, they show strong humidity resistant and self-healing behaviour, recovering rapidly after removing from water vapour. Not only the film can self-heal in this case, but the corresponding devices can present power conversion efficiency recovery after the water vapour is removed. Our work demonstrates the value of cheap, long chain and hygroscopic polymer scaffold in perovskite solar cells towards commercialization.

The power conversion efficiency (PCE) of CH3NH3PbX3 (X = I, Br, Cl) perovskite solar cells has been developed rapidly from 6.5 to 18% within 3 years. However, the anomalous hysteresis found in I-V measurements can cause an inaccurate estimation of the efficiency. We attribute the phenomena to the ferroelectric effect and build a model based on the ferroelectric diode to explain it. The ferroelectric effect of CH3NH3PbI3-xClx is strongly suggested by characterization methods and the E-P (electrical field-polarization) loop. The hysteresis in I-V curves is found to greatly depend on the scan range as well as the velocity, which is well explained by the ferroelectric diode model. We also find that the current signals show exponential decay in ∼10 s under prolonged stepwise measurements, and the anomalous hysteresis disappears using these stabilized current values. The experimental results accord well with the model based on ferroelectric properties and prove that prolonged stepwise measurement is an effective way to evaluate the real efficiency of perovskite solar cells. Most importantly, this work provides a meaningful perspective that the ferroelectric effect (if it really exists) should be paid special attention in the optimization of perovskite solar cells.

Traditional methods of discovering new materials, such as the empirical trial and error method and the density functional theory (DFT)‐based method, are unable to keep pace with the development of materials science today due to their long development cycles, low efficiency, and high costs. Accordingly, due to its low computational cost and short development cycle, machine learning is coupled with powerful data processing and high prediction performance and is being widely used in material detection, material analysis, and material design. In this article, we discuss the basic operational procedures in analyzing material properties via machine learning, summarize recent applications of machine learning algorithms to several mature fields in materials science, and discuss the improvements that are required for wide‐ranging application.

Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query. Existing solutions formulate NLVL either as a ranking task and apply multimodal matching architecture, or as a regression task to directly regress the target video span. In this work, we address NLVL task with a span-based QA approach by treating the input video as text passage. We propose a video span localizing network (VSLNet), on top of the standard span-based QA framework, to address NLVL. The proposed VSLNet tackles the differences between NLVL and span-based QA through a simple and yet effective query-guided highlighting (QGH) strategy. The QGH guides VSLNet to search for matching video span within a highlighted region. Through extensive experiments on three benchmark datasets, we show that the proposed VSLNet outperforms the state-of-the-art methods; and adopting span-based QA framework is a promising direction to solve NLVL. 1 * Corresponding author. 1 https://github.com/IsaacChanghau/VSLNet Language Query: Men are celebrating and an old man gives a trophy to a young boy.

Understanding interfacial loss and the ways to improving interfacial property is critical to fabricate highly efficient and reproducible perovskite solar cells (PSCs). In SnO2‐based PSCs, nonradiative recombination sites at the SnO2–perovskite interface lead to a large potential loss and performance variation in the resulting photovoltaic devices. Here, a novel SnO2‐in‐polymer matrix (i.e., polyethylene glycol) is devised as the electron transporting layer to improve the film quality of the SnO2 electron transporting layer. The SnO2‐in‐polymer matrix is fabricated through spin‐coating a polymer‐incorporated SnO2 colloidal ink. The polymer is uniformly dispersed in SnO2 colloidal ink and promotes the nanoparticle disaggregation in the ink. Owing to polymer incorporation, the compactness and wetting property of SnO2 layer is significantly ameliorated. Finally, photovoltaic devices based on Cs0.05FA0.81MA0.14PbI2.55Br0.45 perovskite sandwiched between SnO2 and Spiro‐OMeTAD layer are fabricated. Compared with the averaging power conversion efficiency of 16.2% with 1.2% deviation for control devices, the optimized devices exhibit an improved averaging efficiency of 19.5% with 0.25% deviation. The conception of polymer incorporation in the electron transporting layer paves a way to further increase the performance of planar perovskite solar cells.

Solar cells based on metal halide perovskites have reached a power conversion efficiency as high as 25%. Their booming efficiency, feasible processability, and good compatibility with large‐scale deposition techniques make perovskite solar cells (PSCs) desirable candidates for next‐generation photovoltaic devices. Despite these advantages, the lifespans of solar cells are far below the industry‐needed 25 years. In fact, numerous PSCs throughout the literature show severely hampered stability under illumination. Herein, several photoinduced degradation mechanisms are discussed. With light radiation, the organic–inorgainc perovskites are prone to phase segregation or chemical decomposition; the oxide electron transport layers (ETLs) tend to introduce new defects at the interface; the commonly used small molecules‐based hole transport layers (HTLs) typically suffer from poor photostability and dopant diffusion during device operation. It has been demonstrated the photoinduced degradation can take place in every functional layer, including the active layer, ETL, HTL, and their interfaces. An overview of these degradation categories is provided in this review, in the hope of encouraging further research and optimization of relevant devices.

Ion migration has been regarded as the major cause of photocurrent hysteresis. Here we use photoluminescence (PL) and optical images, combined with Galvanostatic measurement, to detect the ionic motion. We observe an irreversible PL and optical transmittance change after electric poling. By comparing a neat perovskite film with the sample coated by poly(methyl methacrylate) (PMMA), polyethylene glycol (PEG), and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM), we found that PCBM effectively inhibits ionic motion near the surface of the perovskite.We further evidenced the donor−acceptor complex formed between PCBM and perovskite, implying the mechanism of inhibited ion migration by PCBM. We close by demonstrating that PCBM can also be introduced on the top of perovskite fim in an n−i−p TiO 2 planar structure, to achieve an average 14% steady-state output over 2.3 × 10 5 s (∼64 h). This work highlights the importance of inhibiting ionic motion in perovskite solar cells.

This paper summarizes the ideas, operations and workflows of how machine learning has driven the discovery of new materials.