Assoc. Prof. Dr. Xiaoping Yi | Best Researcher Award

Assoc. Prof. Dr. Xiaoping Yi | Best Researcher Award

University of Science and Technology Beijing | China

Dr. Xiaoping Yi is a materials scientist specializing in first-principles calculations and molecular dynamics of lithium batteries and solid electrolytes, with strong experience in both simulation and experimental design. She earned her PhD in Chemistry from the University of Science and Technology Beijing (2018–2023) and also conducted research at the University of Birmingham, UK, focusing on novel inorganic solid electrolytes, polymer electrolyte design, and silicon-based anodes. After completing her doctorate, she joined the Institute of Physics at the Chinese Academy of Sciences as a postdoctoral researcher (2023–2025), and in 2025 she became Associate Professor at the University of Science and Technology Beijing. Her research interests include nanomaterials design, solid-state lithium/sodium ion batteries, interface electrochemistry, catalytic mechanisms, synchrotron spectroscopy, electron microscopy, and computational materials science. She has published over 25 peer-reviewed SCI articles in high-impact journals (e.g. Advanced Energy Materials, Energy Storage Materials), and her work is recognized for integrating theory and experiment to address performance and safety trade-offs in all-solid-state batteries. Her representative recent work is “Achieving Balanced Performance and Safety for Manufacturing All‐Solid‐State Lithium Metal Batteries by Polymer Base Adjustment” (Adv. Energy Mater., 2025). Her current h-index is approximately 13 with ~1,164 citations (estimated) according to public metrics. She has received recognition for her contributions in battery materials and solid-state electrolytes. Looking ahead, she aims to drive breakthroughs in safe, high-energy density solid-state battery systems via multiscale modeling and experimental validation.

Profile : Orcid

Featured Publications

Yi, X., Li, H.*, Yang, Y., Xiao, K., Zhang, S., Wang, B., Wu, N., Cao, B., Zhou, K., Zhao, X., Leong, K. W., et al. (2025). Achieving balanced performance and safety for manufacturing all-solid-state lithium metal batteries by polymer base adjustment. Advanced Energy Materials, 15(3), 2404973.

Yi, X., Li, H.*, et al. (2025). Strategically tailored polyethylene separator parameters enable cost-effective, facile, and scalable development of ultra-stable liquid and all-solid-state lithium batteries. Energy Storage Materials, 77, 104191.

Chen, N., Yi, X., Liang, Y., et al. (2025). Terminal steric shielding resolves solvent co-intercalation degradation: Molecularly tailored weak-solvation electrolytes for structurally durable K-ion batteries. Chemical Engineering Journal. (Accepted).

Qi, G., Yi, X.*, et al. (2025). Electrochemical-mechanical coupled phase-field modeling for lithium dendrite growth in all-solid-state lithium metal batteries. Journal of Energy Chemistry, 110, 80–87.

Chen, N., Yi, X., Liang, Y., et al. (2024). Dual-steric hindrance modulation of interface electrochemistry for potassium-ion batteries. ACS Nano, 18(32), 32205–32214.

Mr. Ulrich Ngnassi Nguelcheu | Best Researcher Award

Mr. Ulrich Ngnassi Nguelcheu | Best Researcher Award

Researcher at University of Ngaoundéré | Cameroon

Dr. Ulrich Ngnassi Nguelcheu is a researcher at the University of Ngaoundéré, Cameroon, specializing in artificial intelligence applications in renewable energy systems. With 11 publications, 1,302 reads, and 5 citations (h-index: 2), he has made valuable contributions to intelligent control and data-driven optimization for sustainable energy technologies. He holds a doctorate in Artificial Intelligence applied to Renewable Energies, focusing on enhancing the performance and reliability of electromechanical systems through AI-based modeling and simulation. His research experience covers wind energy systems, maintenance optimization, reliability analysis, and composite material development. Among his notable works are studies on the use of artificial neural networks for improved wind turbine control and the optimization of preventive maintenance using genetic algorithms, published in leading journals such as Engineering Applications of Artificial Intelligence. Dr. Nguelcheu actively collaborates with researchers across Cameroon and internationally, emphasizing sustainable and intelligent energy management. His research interests include machine learning for energy systems, renewable energy integration, and smart maintenance strategies. He is dedicated to advancing innovative and eco-efficient technologies that support the global shift toward clean and sustainable energy.

Profiles : Research Gate | Scopus

Featured Publications

Nguelcheu, U. N., Ndjiya, N., Kenmoe Fankem, E. D., Ngnassi Djami, A. B., Guidkaya, G., & Effa, J. Y. (2025). Harnessing artificial neural networks for improved control of wind turbines based on brushless doubly fed induction generator. Engineering Applications of Artificial Intelligence, 154, 110925.

Nguelcheu, U. N., Ndjiya, N., Kenmoe Fankem, E. D., Ngnassi Djami, A. B., Guidkaya, G., & Dountio, T. (2023). Literature review on the control of brushless doubly-fed induction machines. Global Journal of Engineering and Technology Advances, 16(3), 51–69.

Ngnassi Djami, A. B., Nguelcheu, U. N., & Yamigno, S. D. (2023). Formulation, characterization and future potential of composite materials from natural resources: The case of kenaf and date palm fibers. Online Journal of Mechanical Engineering.