A5100452452- Electrocatalysts for Energy Conversion
- Fuel Cells and Related Materials
- Advanced battery technologies research
- Advancements in Solid Oxide Fuel Cells
- Supercapacitor Materials and Fabrication
- Advancements in Battery Materials
- Advanced Photocatalysis Techniques
- Membrane-based Ion Separation Techniques
- CO2 Reduction Techniques and Catalysts
- Extraction and Separation Processes
- Advanced Battery Technologies Research
- Ionic liquids properties and applications
- Hybrid Renewable Energy Systems
- Advanced Radiotherapy Techniques
- Microstructure and Mechanical Properties of Steels
- Carbon Dioxide Capture Technologies
- CO2 Sequestration and Geologic Interactions
- Recycling and Waste Management Techniques
- Solar Thermal and Photovoltaic Systems
- TiO2 Photocatalysis and Solar Cells
- Gas Sensing Nanomaterials and Sensors
- Metallurgy and Material Forming
- Medical Image Segmentation Techniques
- Machine Learning in Materials Science
- Methane Hydrates and Related Phenomena
University of Surrey
2022-2025
Stanford University
2002-2025
Ocean University of China
2024
China Animal Disease Control Center
2024
Qingdao National Laboratory for Marine Science and Technology
2024
Xi'an Jiaotong University
2024
Union Hospital
2023
Jilin University
2023
Inner Mongolia University of Science and Technology
2020-2023
Dalian University of Technology
2009-2023
The development of oxygen reduction reaction (ORR) electrocatalysts based on earth-abundant nonprecious materials is critically important for sustainable large-scale applications fuel cells and metal-air batteries. Herein, a hetero-single-atom (h-SA) ORR electrocatalyst presented, which has atomically dispersed Fe Ni coanchored to microsized nitrogen-doped graphitic carbon support with unique trimodal-porous structure configured by highly ordered macropores interconnected through mesopores....
The development of artificial intelligence (AI) greatly boosts scientific and engineering innovation. As one the promising candidates for transiting carbon intensive economy to zero emission future, proton exchange membrane (PEM) fuel cells has aroused extensive attentions. gas diffusion layer (GDL) strongly affects water heat management during PEM operation, therefore multi-variable optimization, including thickness, porosity, conductivity, channel/rib widths compression ratio, is essential...
Solar-driven vaporization is a sustainable solution to water and energy scarcity. However, most of the present evaporators are still suffering from inefficient utilization converted thermal energy. Herein, universal sandwich membrane strategy demonstrated by confining hierarchical porous carbon cells in two barriers obtain high-efficiency evaporator with rapid evaporation rate 1.87 kg m-2 h-1 under 1 sun illumination, which among highest performance for carbon-based wood-based evaporators....
A sandwich hydrogel evaporator is obtained by confining plasmonic Cu/carbon cell solar absorbers in the evaporation surface of a PVA to achieve high-efficiency water purification.
Dust accumulation on the surface of solar photovoltaic panels diminishes their power generation efficiency, leading to reduced energy generation. Regular monitoring and cleaning is essential. Thus, developing optimal procedures for upkeep crucial improving component reducing maintenance costs, conserving resources. This study introduces an improved Adam optimization algorithm designed specifically detecting dust panels. Although traditional preferred choice optimizing neural network models,...
Using routine preradiation treatment CT simulation scans and tumor segmentation data, a deep learning model was developed to detect segment lung tumors, good performance achieved on diverse datasets.