Siyuan Zhao

With the global shift toward green energy, solar photovoltaic (PV) power has expanded rapidly. However, the unpredictable nature of PV generation, caused by changing weather conditions like irradiance and temperature, challenges grid stability and power scheduling. Therefore, developing smart forecasting models for high-precision PV power prediction is essential for modern grid management. This paper introduces an optimized forecasting framework using Long Short-Term Memory (LSTM) networks. By integrating historical power generation data with localized meteorological factors, a multivariate predictive model was developed and validated using empirical data from a 100 MW PV plant. Based on Pearson correlation analysis, four key features—temperature, direct normal irradiance (DNI), relative humidity, and cloud cover—were chosen as the main drivers of PV output. A multivariate LSTM model was then trained and carefully tested using time series cross-validation. Results show the multi-feature architecture consistently outperforms and surpasses single-feature benchmarks. Specifically, the model achieved a peak R² of 0.9864 and minimum MAE of 1.4057 kW. Across four validation sets, R² remained stable (0.9755–0.9836), with most errors tightly bounded within ±5 kW. These findings confirm the model’s excellent accuracy and its value for improving power system dispatch and resource planning.

Flexible Al–air batteries have attracted widespread attention in the field of wearable power due to the high theoretical energy density of Al metal. However, the efficiency degradation and anodizing retardation caused by Al parasitic corrosion severely limit the performance breakthrough of the batteries. Herein, a Prussian‐blue bifunctional interface membrane is proposed to improving the discharge performance of hydrogel‐based Al–air battery. When a rational 12 mg·cm⁻² membrane is loaded, the effect of anticorrosion and activation is optimal thanks to the formation of a stable and breathable interface. The results demonstrate that a flexible Al–air battery using the membrane can output a high power density of 65.76 mW·cm⁻². Besides, the battery can achieve a high capacity of 2377.43 mAh·g⁻¹, anode efficiency of 79.78%, and energy density of 3176.39 Wh·kg⁻¹ at 10 mA·cm⁻². Density functional theory calculations uncover the anticorrosion‐activation mechanism that Fe³⁺ with a large number of empty orbitals can accelerate electrons transfer, and nucleophilic reactant [Fe^II(CN)₆]⁴⁻ promotes the Al³⁺ diffusion. These findings are beneficial to the inhibition of interfacial parasitic corrosion and weakening of discharge hysteresis for flexible Al–air batteries.

The sluggish kinetics of the oxygen reduction reaction (ORR) with complex multielectron transfer steps significantly limits the large‐scale application of electrochemical energy devices, including metal–air batteries and fuel cells. Recent years witnessed the development of metal oxide‐supported metal catalysts (MOSMCs), covering single atoms, clusters, and nanoparticles. As alternatives to conventional carbon‐dispersed metal catalysts, MOSMCs are gaining increasing interest due to their unique electronic configuration and potentially high corrosion resistance. By engineering the metal oxide substrate, supported metal, and their interactions, MOSMCs can be facilely modulated. Significant progress has been made in advancing MOSMCs for ORR, and their further development warrants advanced characterization methods to better understand MOSMCs and precise modulation strategies to boost their functionalities. In this regard, a comprehensive review of MOSMCs for ORR is still lacking despite this fast‐developing field. To eliminate this gap, advanced characterization methods are introduced for clarifying MOSMCs experimentally and theoretically, discuss critical methods of boosting their intrinsic activities and number of active sites, and systematically overview the status of MOSMCs based on different metal oxide substrates for ORR. By conveying methods, research status, critical challenges, and perspectives, this review will rationally promote the design of MOSMCs for electrochemical energy devices.

Lithium–air (Li–air) batteries stand out among the post‐Li‐ion batteries due to their high energy density, which has rapidly progressed in the past years. Regarding the fundamental mechanism of Li–air batteries that discharge products produced and decomposed during charging and recharging progress, the reversibility of products closely affects the battery performance. Along with the upsurge of the mainstream discharge products lithium peroxide, with devoted efforts to screening electrolytes, constructing high‐efficiency cathodes, and optimizing anodes, much progress is made in the fundamental understanding and performance. However, the limited advancement is insufficient. In this case, the investigations of other discharge products, including lithium hydroxide, lithium superoxide, lithium oxide, and lithium carbonate, emerge and bring breakthroughs for the Li–air battery technologies. To deepen the understanding of the electrochemical reactions and conversions of discharge products in the battery, recent advances in the various discharge products, mainly focusing on the growth and decomposition mechanisms and the determining factors are systematically reviewed. The perspectives for Li–air batteries on the fundamental development of discharge products and future applications are also provided.