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20242026
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cond-mat.mtrl-sci2026

Synergistic Interface Stability and High Room-Temperature Ionic Conductivity for Wide-Temperature All-Solid-State Batteries Based on Li6+xSixSb1-xS5I Electrolytes

Liang Ming, Qizhiran Sun, Guanping Xu +7

Solid-state lithium-ion batteries (LIBs) are increasingly recognized for their exceptional energy density and safety. However, their widespread adoption is challenged by persistent…

cond-mat.mtrl-sci2025

Synergistic effects of rare-earth doping on the magnetic properties of orthochromates: A machine learning approach

Guanping Xu, Zirui Zhao, Muqing Su +1

Multiferroic materials, particularly rare-earth orthochromates (RECrO), have garnered significant interest due to their unique magnetic and electric-polar properties, making th…

cond-mat.mtrl-sci2025

Integrating Machine Learning with Triboelectric Nanogenerators: Optimizing Electrode Materials and Doping Strategies for Intelligent Energy Harves

Guanping Xu, Zirui Zhao, Zhong Lin Wang +1

The integration of machine learning techniques with triboelectric nanogenerators (TENGs) offers a transformative pathway for optimizing energy harvesting technologies. In this stud…

cond-mat.mtrl-sci2024

Ultrasonic-assisted liquid phase exfoliation for high-yield monolayer graphene with enhanced crystallinity

Kaitong Sun, Si Wu, Junchao Xia +3

Graphene stands as a promising material with vast potential across energy storage, electronics, etc. Here, we present a novel mechanical approach utilizing ultrasonic high-energy i…

cond-mat.mtrl-sci2024

Deep learning-driven evaluation and prediction of ion-doped NASICON materials for enhanced solid-state battery performance

Zirui Zhao, Xiaoke Wang, Si Wu +5

We developed a convolutional neural network (CNN) model capable of predicting the performance of various ion-doped NASICON compounds by leveraging extensive datasets from prior exp…