16 citations · 53 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
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…
Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials
Zirui Zhao, Hai-Feng Li
Understanding and predicting interface diffusion phenomena in materials is crucial for various industrial applications, including semiconductor manufacturing, battery technology, a…
Predicting doping strategies for ternary nickel-cobalt-manganese cathode materials to enhance battery performance using graph neural networks
Zirui Zhao, Dong Luo, Shuxing Wu +3
The exceptional electrochemical performance of lithium-ion batteries has spurred considerable interest in advanced battery technologies, particularly those utilizing ternary nickel…