Machine Learning Helps Data Mining to Build Descriptor Databases for Lithium‐Ion Batteries

ABSTRACT The rapid development of computer science has made machine learning (ML)‐driven design a research hotspot in high‐performance lithium‐ion batteries. Descriptors play a critical role in ML processes, as accurate descriptors significantly improve prediction accuracy (achieving over 92% validation accuracy in density functional theory [DFT]‐calibrated models). Although open‐source databases offer rich material data, their operational complexity hinders effective utilization. This review highlights ML algorithms that streamline data extraction from these repositories, slashing experimental iterations by 75%–80%. Further analyze future challenges in descriptor acquisition for lithium‐ion batteries. This review is to provide insights into dataset construction and ML‐compatible descriptor generation, accelerating electrode material discovery from conventional 5–7 years to < 18 months in recent cases

Flexible Wearable Electronics: Present State and Future Development

Wearable electronics are expected to be light, durable, flexible, and comfortable. Many fibrous, planar and tridimensional structures have been designed to realize flexible devices that can sustain geometrical deformations, such as bending, twisting, folding, and stretching normally at ambient conditions. As a flexible electrode for batteries or other devices, it possess favorable mechanical strength and large specific capacity and preserve efficient ionic and electronic conductivity with a certain shape, structure and function. To fulfill flexible energy-storage devices, much effort has been devoted to design of structures and materials with mechanical characteristics. This review attempts to critically review the state‐of‐arts with respect to materials, and structural design of devices as well as applications of the wearable electronic products. Finally, discussion present regarding to limitations of current materials, fabrication techniques, devices concerning manufacturability and performance as well as scientific understanding that must be improved prior to their wide adoption.</jats:p

Local electronic structure constructing of layer‐structured oxide cathode material for high‐voltage sodium‐ion batteries

Abstract As the cyclable sodium ions' primary suppliers, O3‐type layer‐structured manganese‐based oxides are recognized as one of the most competitive cathode candidates for sodium‐ion batteries. Suffering from complex structural transformations and transition metal migration during the sodium intercalation/deintercalation process, particularly at high voltage, the energy density and lifespan cannot satisfy the increasing demand. The orbital and electronic structure of the octahedral center metal element plays an important role in maintaining the octahedral structural integrity and improving the Na+ diffusivity by the introduced heterogeneous [Me–O] (Me: transition metals) chemical bonding. Herein, inspired by the 4f and 5d orbital bonding possibility from the abundant configuration of extranuclear electrons and large ion radius, O3‐type Na[La0.01Ni0.3Mn0.54Cu0.1Ti0.05]O2 was synthesized with a nearly single crystal structure. Based on the experimental and computational results, the introduced heterogeneous [La–O] chemical bond with larger bond strength can not only ensure the stability of the lattice oxygen framework and the reversibility of oxygen redox but also optimize the oxygen local electronic structure resulting from La 5d and O 2p orbital mixing due to O 2p → La 5d charge transfer. It delivers an optimal electrochemical performance with a high energy density and cycling lifespan