Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

MXene-derived TiO2/reduced graphene oxide composite with an enhanced capacitive capacity for Li-ion and K-ion batteries

Abstract: Li-ion and K-ion batteries present their unique advantages of high energy density and low cost, respectively. It is a challenge to explore a universal anode with efficient electrochemical performance. Herein, a two-dimensional TiO2/reduced graphene oxide (RGO) composite was prepared by a facile hydrothermal method. TiO2 nanoparticles are transformed from Ti2C MXene and connect the RGO nanosheets to form a sheet-like structure. Serving as the anode material, the TiO2/RGO presents high capacity, remarkable rate ability and long cycling performance for both Li- and K-ion batteries. The superior electrochemical performance is attributed to the short ion diffusion path due to the small particle size (15–25 nm) and the highway for electron transport provided by RGO. In addition, RGO motivates the capacitive contribution, resulting in enhanced capacity and better rate performance. Meanwhile, the electrochemical kinetics of Li/K-ion storage was investigated by quantitative kinetics analysis. This work demonstrates a possibility to introduce the capacitive capacity to realize rapid ion storage and improve the cycling stability, providing a new strategy to design efficient electrodes for metal-ion batteries.

Artificial Intelligence for Vehicle-to-Everything: A Survey

Abstract: Recently, the advancement in communications, intelligent transportation systems, and computational systems has opened up new opportunities for intelligent traffic safety, comfort, and efficiency solutions. Artificial intelligence (AI) has been widely used to optimize traditional data-driven approaches in different areas of the scientific research. Vehicle-to-everything (V2X) system together with AI can acquire the information from diverse sources, can expand the driver's perception, and can predict to avoid potential accidents, thus enhancing the comfort, safety, and efficiency of the driving. This paper presents a comprehensive survey of the research works that have utilized AI to address various research challenges in V2X systems. We have summarized the contribution of these research works and categorized them according to the application domains. Finally, we present open problems and research challenges that need to be addressed for realizing the full potential of AI to advance V2X systems.