Jiabao Li | Engineering | Research Excellence Award

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Mr. Jiabao Li | Engineering | Research Excellence Award

Yangzhou University | China

Mr. Jiabao Li is a materials scientist and electrochemical energy researcher specializing in sodium-ion batteries and capacitive deionization, with particular focus on electrode and electrolyte design for extreme temperature environments. He earned his bachelor’s and master’s degrees in applied chemistry from Anhui Agricultural University, followed by a Ph.D. in materials and optoelectronics from East China Normal University, including a joint research period at the Georgia Institute of Technology. Since completing his doctoral work, he has served as a lecturer and researcher, leading multiple competitive research projects in materials innovation and energy-storage systems. His work integrates experimental synthesis with computational tools such as DFT modeling and molecular dynamics simulations to advance high-performance sodium-ion storage materials. He has published 98 scientific documents, accumulating 5,410 citations across 4,235 referencing documents, with an h-index of 40, reflecting significant global impact in the fields of battery chemistry and electrochemical engineering. His awards include national and institutional scholarships that recognize excellence in scientific research and academic achievement. Overall, his career demonstrates sustained contributions to next-generation energy-storage technologies and the advancement of robust sodium-ion systems for low-temperature and high-efficiency applications.

Profile : Scopus

Featured Publications

Unveiling the neglected role of oxygen doping in nitrogen-doped carbon for enhanced capacitive deionization performance. Nature Communications, 2025.

Rapidly evaluating electrochemical performance of transition metal disulfides for lithium-ion batteries using machine learning classifier. Chemical Engineering Journal, 2025.

Ionic conductor-armored Li₃V₂(PO₄)₃: a robust electrode for lithium capture via capacitive desalination. Chemical Communications, 2025.

Anion screening in ether-based electrolytes for boosted sodium storage at low temperature. Energy Storage Materials, 2025.

Coordination-tuned Na₃V₂(PO₄)₃ cathodes for low-temperature sodium-ion batteries. Chemical Communications, 2025.

 

Fan Xiao | Data Processing | Research Excellence Award

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Assoc. Prof. Dr. Fan Xiao | Data Processing | Research Excellence Award

Sun Yat-sen University | China

Xiao Fan is an Associate Professor and PhD advisor at the School of Earth Sciences and Engineering, Sun Yat-sen University, recognized for his contributions to mineral exploration, mathematical geoscience, and data-driven Earth system analysis. He received his bachelor’s and doctoral degrees in mineral resource exploration from China University of Geosciences (Wuhan), with joint doctoral training at the University of Ottawa. His research focuses on mineral system modeling, multi-physics numerical simulation, fractal and singularity analysis, machine-learning-based mineral prospectivity, and knowledge-driven geoscientific data integration. As a core member of major national innovation teams, he has led or participated in several national and provincial research projects and contributed to the creation of an advanced UAV-based geophysical–geochemical acquisition and processing platform. He has published 54 documents with 986 citations from 706 sources and holds an h-index of 19, along with multiple patents, software copyrights, and highly cited works in leading SCI journals. He serves on editorial boards and scientific committees, including roles as youth editor and guest editor, and has organized sessions for the International Geological Congress. His work advances quantitative mineral prediction and computational geoscience, contributing impactful models and methods that enhance understanding of mineralization processes and exploration efficiency.

Profiles : Scopus | Orcid

Featured Publications

(2025). “Three-Dimensional Prospectivity Modeling of Jinshan Ag-Au Deposit, Southern China by Weights-of-Evidence.” Journal of Earth Science.

(2025). “Lithologic mapping of intermediate-acid intrusive rocks in the eastern Tianshan Gobi Desert using machine learning and multi-source data fusion.” Earth Science Frontiers.

(2025). “A DFT study on mechanisms of indium adsorption on sphalerite (100), (110), and (111) surfaces: Implications for critical metal mineralization.” Ore Geology Reviews.

(2025). “Data-driven expeditious mapping and identifying granites in covered areas via deep machine learning: A case study on the implications for geodynamics and mineralization of Eastern Tianshan.” Lithos.

(2025). “Numerical Modeling and Exploration Data Coupled-driven Mineral Prospectivity Mapping: A Case Study of Fankou Pb-Zn Deposit.” Geotectonica et Metallogenia.