5 papers
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…
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…
Insights into dendritic growth mechanisms in batteries: A combined machine learning and computational study
Zirui Zhao, Junchao Xia, Si Wu +5
In recent years, researchers have increasingly sought batteries as an efficient and cost-effective solution for energy storage and supply, owing to their high energy density, low c…
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…
High-performance magnesium/sodium hybrid ion battery based on sodium vanadate oxide for reversible storage of Na+ and Mg2+
Xiaoke Wang, Titi Li, Xixi Zhang +5
Magnesium ion batteries (MIBs) are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation. Magnesi…