Browsing by Author "Li, Jing"

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    Application of thermal spray coatings in electrolysers for hydrogen production: advances, challenges, and opportunities
    (Wiley, 2022-10-14) Faisal, Nadimul Haque; Prathuru, Anil; Ahmed, Rehan; Rajendran, Vinooth; Hossain, Mamdud; Venkatachalapathy, Viswanathan; Katiyar, Nirmal Kumar; Li, Jing; Liu, Yuheng; Cai, Qiong; Horri, Bahman Amini; Thanganadar, Dhinesh; Sodhi, Gurpreet Singh; Patchigolla, Kumar; Fernandez, Carlos; Joshi, Shrikant; Govindarajan, Sivakumar; Kurushina, Victoria; Katikaneni, Sai; Goel, Saurav
    Thermal spray coatings have the advantage of providing thick and functional coatings from a range of engineering materials. The associated coating processes provide good control of coating thickness, morphology, microstructure, pore size and porosity, and residual strain in the coatings through selection of suitable process parameters for any coating material of interest. This review consolidates scarce literature on thermally sprayed components which are critical and vital constituents (e. g., catalysts (anode/cathode), solid electrolyte, and transport layer, including corrosion-prone parts such as bipolar plates) of the water splitting electrolysis process for hydrogen production. The research shows that there is a gap in thermally sprayed feedstock material selection strategy as well as in addressing modelling needs that can be crucial to advancing applications exploiting their catalytic and corrosion-resistant properties to split water for hydrogen production. Due to readily scalable production enabled by thermal spray techniques, this manufacturing route bears potential to dominate the sustainable electrolyser technologies in the future. While the well-established thermal spray coating variants may have certain limitations in the manner they are currently practiced, deployment of both conventional and novel thermal spray approaches (suspension, solution, hybrid) is clearly promising for targeted development of electrolysers.
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    Applications of large language models and multimodal large models in autonomous driving: a comprehensive review
    (MDPI, 2025-04-01) Li, Jing; Li, Jingyuan; Yang, Guo; Yang, Lie; Chi, Haozhuang; Yang, Lichao
    The rapid development of large language models (LLMs) and multimodal large models (MLMs) has introduced transformative opportunities for autonomous driving systems. These advanced models provide robust support for the realization of more intelligent, safer, and efficient autonomous driving. In this paper, we present a systematic review on the integration of LLMs and MLMs in autonomous driving systems. First, we provide an overview of the evolution of LLMs and MLMs, along with a detailed analysis of the architecture of autonomous driving systems. Next, we explore the applications of LLMs and MLMs in key components such as perception, prediction, decision making, planning, multitask processing, and human–machine interaction. Additionally, this paper reviews the core technologies involved in integrating LLMs and MLMs with autonomous driving systems, including multimodal fusion, knowledge distillation, prompt engineering, and supervised fine tuning. Finally, we provide an in-depth analysis of the major challenges faced by autonomous driving systems powered by large models, offering new perspectives for future research. Compared to existing review articles, this paper not only systematically examines the specific applications of LLMs and MLMs in autonomous driving systems but also delves into the key technologies and potential challenges involved in their integration. By comprehensively organizing and analyzing the current literature, this review highlights the application potential of large models in autonomous driving and offers insights and recommendations for improving system safety and efficiency.
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    High performance perovskite sub-module with sputtered SnO2 electron transport layer
    (Elsevier, 2019-03-13) Bai, Guangfeng; Wu, Zhengli; Li, Jing; Bu, Tongle; Li, Wangnan; Li, Wei; Huang, Fuzhi; Zhang, Qi; Cheng, Yi-Bing; Zhong, Jie
    Hybrid perovskite solar cells (PSC) have gained stupendous achievement in single/tandem solar cell, semitransparent solar cell and flexible devices. Aiming for potential commercialization of perovskite photovoltaic technology, up scalable processing is crucial for all function layers in PSC. Herein we present a study on room temperature magnetron sputtering of tin oxide electron transporting layer (ETL) and apply it in a large area PSC for low cost and continues manufacturing. The SnO2 sputtering targets with varied oxygen and deposition models are used. Specifically, the working gas ratio of Ar/O2 during the radio frequency sputtering process plays a crucial role to obtain optimized SnO2 film. The sputtered SnO2 films demonstrate similar morphological and crystalline properties, but significant varied defect states and carrier transportation roles in the PSC devices. With further modification of thickness of SnO2, the PSCs based on sputtered SnO2 ETL shows a champion efficiency of 18.20% in small area and an efficiency of 14.71% in sub-module with an aperture area of 16.07 cm2, which is the highest efficiency of perovskite sub module with sputtered ETLs.