Perovskite solar cells (PSCs) have attracted considerable attention as next-generation photovoltaic technologies owing to their solution processability, low weight, and mechanical flexibility. Despite rapid progress, defect-induced nonradiative recombination remains a major obstacle, hindering further improvements in the device efficiency and operational stability. In this study, we introduce 1H-indole-3-carbohydrazide (1H-CBH) as a multifunctional molecular additive that effectively mitigates these issues through synergistic defect passivation. Specifically, 1H-CBH simultaneously coordinates with uncoordinated Pb²⁺ ions and forms hydrogen bonds with uncoordinated I⁻ ions and formamidinium cations. This dual interaction strategy promotes the growth of larger grains, reduces the density of grain boundary defects, and enhances the interfacial compatibility with the electron-transport layer, thereby enabling improved charge transport. Consequently, the incorporation of 1H-CBH into mixed-cation PSCs yields a remarkable enhancement in the power conversion efficiency from 21.18% to 23.59%. Moreover, the 1H-CBH-modified devices demonstrated exceptional environmental stability, retaining their initial morphology after 8 months under ambient conditions (25°C, 50%‒80% relative humidity), whereas their unpassivated counterparts underwent complete degradation. Under inert N₂ atmosphere, PSCs incorporating 1H-CBH maintained >80% of their initial power conversion efficiency after 600 h continuous storage. These results highlight the critical role of multifunctional additive engineering in achieving highly efficient and durable perovskite solar cells, paving the way toward scalable and reliable photovoltaic technologies.

Due to their excellent advantages such as low toxicity, superior optoelectronic properties, low-temperature fabrication, and cost-effectiveness, Sn-based perovskites have become the most promising alternatives for high performance lead-free perovskite solar cells. However, the character of Sn²⁺ is easily oxidized to Sn⁴⁺, causing unnecessary p-type self-doping and high leakage current. More seriously, trap-induced non-radiative recombination from rapid crystallization causes into large energy loss with a low open circuit voltage. Therefore, the Sn-based solar cells have efficiency far behind the Pb-based solar cells. Herein, the polymer poly(ethylene glycol) diacrylate (PEGDA) is used to control crystal growth and passivate the defects in FA_0.85PEA_0.15SnI₃ thin film. This Sn-perovskite layer shows compact crystal with large grain size and reduced defects. Optimized perovskite thin film is further processed to fabricate the inverted solar cell with device structure of ITO (indium tin oxide)/PEDOT:PSS (Poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate))/FA_0.85PEA_0.15SnI₃/ICBA (indene-C60 bisadduct)/BCP (bathocuproine)/Ag, which shows the power conversion efficiency (PCE) of 11.45% with voltage of 0.82 V. Moreover, corresponding perovskite solar cells exhibit an enhanced stability due to PEGDA induced compressive strain in perovskite. This work could shed light on one of successful attempts to improve Sn-based solar cell efficiency for sustainable energy conversion.

It remains challenging to effectively estimate the remaining capacity of the secondary lithium-ion batteries that have been widely adopted for consumer electronics, energy storage, and electric vehicles. Herein, by integrating regular real-time current short pulse tests with data-driven Gaussian process regression algorithm, an efficient battery estimation has been successfully developed and validated for batteries with capacity ranging from 100% of the state of health (SOH) to below 50%, reaching an average accuracy as high as 95%. Interestingly, the proposed pulse test strategy for battery capacity measurement could reduce test time by more than 80% compared with regular long charge/discharge tests. The short-term features of the current pulse test were selected for an optimal training process. Data at different voltage stages and state of charge (SOC) are collected and explored to find the most suitable estimation model. In particular, we explore the validity of five different machine-learning methods for estimating capacity driven by pulse features, whereas Gaussian process regression with Matern kernel performs the best, providing guidance for future exploration. The new strategy of combining short pulse tests with machine-learning algorithms could further open window for efficiently forecasting lithium-ion battery remaining capacity.

A high-quality hybrid Cs_0.15FA_0.85PbI₃ thin film is deposited through doping of carbon nanodots (CNDs) into perovskite precursor solution. The corresponding inverted planar perovskite solar cells (PSCs) of ITO/PTAA/Cs_0.15FA_0.85PbI₃/PC₆₁BM/BCP/Ag exhibit an improvement in efficiency from 17.36% to 20.06%, which could be attributed to the passivation of the defects at the crystallized perovskite thin film and enhanced perovskite phase uniformity. The results of electron trap density indicate that the addition of CNDs significantly reduces the defects density at the perovskite thin film and the recombination of charge carriers in transport process is minimized. These results demonstrate that low-cost CNDs are effective additives for passivating defects, further reducing charge carrier recombination and improving device efficiency.