Due to the relatively high capacity and lower cost, transition metal sulfides (TMS) as anode show promising potential in sodium‐ion batteries (SIBs). Herein, a binary metal sulfide hybrid consisting of carbon encapsulated CoS/Cu2S nanocages (CoS/Cu2S@C‐NC) is constructed. The interlocked hetero‐architecture filled with conductive carbon accelerates the Na+/e− transfer, thus leading to improved electrochemical kinetics. Also the protective carbon layer can provide better volume accommondation upon charging/discharging. As a result, the battery with CoS/Cu2S@C‐NC as anode displays a high capacity of 435.3 mAh g−1 after 1000 cycles at 2.0 A g−1 (≈3.4 C). Under a higher rate of 10.0 A g−1 (≈17 C), a capacity of as high as 347.2 mAh g−1 is still remained after long 2300 cycles. The capacity decay per cycle is only 0.017%. The battery also exhibits a better temperature tolerance at 50 and −5 °C. A low internal impedance analyzed by X‐ray diffraction patterns and galvanostatic intermittent titration technique, narrow band gap, and high density of states obtained by first‐principle calculations of the binary sulfides, ensure the rapid Na+/e− transport. The long‐cycling‐life SIB using binary metal sulfide hybrid nanocages as anode shows promising applications in versatile electronic devices.

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The development of modern civil industry, energy and information technology is inseparable from the rapid explorations of new materials. However, only a small fraction of materials being experimentally/computationally studied in a vast chemical space. Artificial intelligence (AI) is promising to address this gap, but faces many challenges, such as data scarcity and inaccurate material descriptors. Here, we develop an AI platform, AlphaMat, that can complete data preprocessing and downstream AI models. With high efficiency and accuracy, AlphaMat exhibits strong powers to model typical 12 material attributes (formation energy, band gap, ionic conductivity, magnetism, bulk modulus, etc.). AlphaMat’s capabilities are further demonstrated to discover thousands of new materials for use in specific domains. AlphaMat does not require users to have strong programming experience, and its effective use will facilitate the development of materials informatics, which is of great significance for the implementation of AI for Science (AI4S).

Anhui Provincial Engineering Laboratory for Engineering appropriate cathode materials is significant for the development of high-performance aluminum-ion (Al-ion) batteries. Here, a pyramidal metal-organic frameworks (MOFs)-derived FeP@CoP composite was developed as cathode, which exhibits good stability and high capacity. FeP@CoP cathode maintains a high capacity of 168 mAh g À 1 after 200 cycles, and displays a stable rate-performance at both room and low temperatures of À 10 °C. After three rounds of rate-performance cycling, the FeP@CoP composite recovers 178.2 mAh g À 1 at 0.3 A g À 1 . Moreover, density functional theory (DFT) calculations verify improved electrontransfer kinetics with narrowed band gap and enhanced density of states. These findings inspire a broad set of studies on MOFs-derived composites for high-performance secondary batteries.