Area of research
Biomedical Engineering · Mechanical Engineering
Research interest
Research interests include Thermochemical Biomass Conversion Processes, Coal Combustion and Slurry Processing, Coal and Its By-products, and Advancements in Battery Materials.
Strain and doping engineerings unlocking power density and cyclability of microspherical TiNb2O7 anodes of lithium-ion batteries
Two-dimensional nitrogen-doped carbon nanosheets-coated porous SiO composites sponges for durable anode materials of high-energy lithium-ion batteries
Fe/FeO Nanoparticles‐Decorated Porous SiOC Hierarchical Spheres Enable Robust LiF‐Rich Solid Electrolyte Interphase and Ultrastable Lithium‐Ion Storage
EEG signature orchestrating expression of ictal behavior in mesial temporal lobe epilepsy
Bi Nanoparticle/Bi<sub>4</sub>Ti<sub>3</sub>O<sub>12</sub> Nanosheet/g-C<sub>3</sub>N<sub>4</sub> Nanowire Heterojunction for the Piezocatalytic H<sub>2</sub>O<sub>2</sub> Production
Nanocellulose-based functional materials towards water treatment
Research on the Energy Management Strategy of a Hybrid Tractor OS-ECVT Based on a Dynamic Programming Algorithm
Boosting Uniformity and Efficiency of Large‐Area Inverted Organic Photovoltaics Via ZnO Surface Energy Modulation
Origin of the Slope Capacity of Sodium-Ion Storage in Hydrogen-Rich Carbon Nanoribbon
Polyamine Anabolism Promotes Chemotherapy‐Induced Breast Cancer Stem Cell Enrichment
Non-intubated video-assisted thoracoscopic surgery vs. intubated video-assisted thoracoscopic surgery for thoracic disease: a systematic review and meta-analysis of 1,684 cases
I-Corps: Translation Potential of Bitwise Dependence Detection
FRG: Collaborative Research: Mathematical and Statistical Analysis of Compressible Data on Compressive Networks
Binary Expansion Statistics: A Nonparametric Inference Framework for Big Data
BIGDATA: Collaborative Research: F: Statistical Theory and Methods Beyond the Dimensionality Barrier
Geometric Perspectives on the Correlation
Collaborative Research: Inference for Linear Model Parameters in Model-free Populations