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The fabrication of atomically thin-MoS_(2) based photoanodes for photoelectrochemical energy conversion and environment remediation:A review

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Green Energy & Environment 2022年第3期7卷 372-393页

作者： zexu Chi Jingyun Zhao Yi zhang Han Yu Hongbing Yu College of Environment Science and Engineering Nankai UniversityTianjin300350China Department of Water Resources Engineering Lund UniversityLund22100Sweden

Photoelectrochemical(PEC) technology has been proved a promising approach to solve the problems of energy shortages and environmental pollution damages.It can convert unlimited solar energy resources into energy forms needed by mankind.The development of highly efficient photoanodes is a key step in realizing the large-scale practical application of PEC systems.However,the development of PEC photoanodes has been severely hindered by the issues of easy recombination of photo-generated charge carriers,low photon-to-electron conversion efficiency,poor photo-corrosion resistance,and low catalytic activity.Therefore,constructing high-performance and stable photoanodes is an urgent research field to promote the progress of PEC technology.The atomically thin molybdenum disulfide(AT-MoS_(2)) with unique physical and chemical properties has been widely applied in the fabrication of PEC photoanodes.The AT-MoS_(2) based photoanodes have exhibited excellent PEC performance,which providing promising candidates for ideal PEC application.Here,we summarize the fundamental natures of MoS_(2) and present the research efforts in the preparation of AT-MoS_(2) based photoanodes.Strategies for the fabrication of high-efficient AT-MoS_(2) based photoanodes are emphasized to provide guidelines to advance emerging PEC photoanodes.Besides,perspectives for the development of more efficient AT-MoS_(2) based photoanodes are proposed.

关键词： energy atomic molybdenum

Defective TiO_(2)hollow nanospheres as photo-electrocatalysts for photo-assisted Li-O_(2)batteries

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Chinese Chemical Letters 2022年第8期33卷 4008-4012页

作者： Hailiang Jiao Guiru Sun Yan Wang Zexu Zhang Zhao Wang Hairui Wang Haibo Li Ming Feng Key Laboratory of Functional Materials Physics and Chemistry of the Ministry of Education Jilin Normal UniversityChangchun 130103China Key Laboratory of Preparation and Applications of Environmental Friendly Materials of the Ministry of Education Jilin Normal UniversityChangchun 130103China

The large overpotential for conventional Li-O_(2) batteries is an enormous challenge,which impedes their practical application.Here,we prepare a defective TiO_(2)(Ov-TiO_(2)) hollow nanosphere as photoelectrocatalyst for photo-assisted Li-O_(2) batteries to reduce the overpotential.Under illumination,the oxygen vacancies as a charge separation center contribute to the separation of electrons and holes.The generated electrons could promote reducing O_(2) to Li_(2)O_(2) during oxygen reduction reaction(ORR)process,while the generated holes are beneficial to Li_(2)O_(2) decomposition during oxygen evolution reaction(OER)process.Additionally,the proper concentration of oxygen vacancies will decrease the recombination rate between electrons and holes.The photo-assisted Li-O_(2) batteries with Ov-TiO_(2)-650 exhibit advanced performances,such as the low overpotential(0.70 V),the fine rate capability,and the considerable reversibility accompanied with the formation/decomposition of Li_(2)O_(2).We expect that these results could open a new mind to design of highly efficient photo-electrocatalysts for photo-assisted Li-O_(2) battery.

关键词： TiO_(2) Hollow nanospheres Oxygen vacancies Photo-electrocatalyst Li-O_(2)battery

Deep Reinforcement Learning Based Bi-layer Optimal Scheduling for Microgrids Considering Flexible Load Control

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CSEE Journal of Power and Energy Systems 2023年第3期9卷 949-962页

作者： Zitong zhang Jing Shi Wangwang Yang Zhaofang Song zexu Chen Dengquan Lin the State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074China

In this paper,the bi-layer scheduling method for microgrids,based on deep reinforcement learning,is proposed to achieve economic and environmentally friendly operations.First,considering the uncertainty of renewable energy,the framework of day-ahead and intra-day scheduling is established,and the implementation scheme for both price-based and incentive-based demand response(DR)for the flexible load is determined.Then,comprehensively considering the operating characteristics of the microgrid in the day-ahead and intra-day time scales,a bi-layer scheduling model of the microgrid is established.In terms of algorithms,since day-ahead scheduling has no strict requirement for dispatching time,the particle swarm optimization(PSO)algorithm is used to optimize the time-of-use electricity price and distributed power output for the next day.Considering the environmental fluctuations and requirements for rapidity of intra-day online scheduling,the deep reinforcement learning(DRL)algorithm is adopted for optimization.Finally,based on the data from the actual microgrid,the rationality and effectiveness of the proposed scheduling method is verified.The results show that the proposed bi-layer scheduling based on the PSO and DRL algorithms achieves the optimization of scheduling cost and calculation speed,and is suitable for microgrid online scheduling.

关键词： Bi-layer optimal scheduling demand response deep reinforcement learning microgrid scheduling

Morphological and heterojunctional engineering of two-dimensional porous Mo-Ni based catalysts for highly effective catalytic reduction of aromatic nitro compounds

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中国化学快报:英文版 2023年第9期34卷 310-316页

作者： zexu Fang Ying Gu Xinran Dong Gen zhang Lin Li Xiaoguang Zhou Chungui Tian College of Chemistry Chemical Engineering and Resource UtilizationNortheast Forestry UniversityHarbin 150040China Key Laboratory of Functional Inorganic Material Chemistry Ministry of Education of the People’s Republic of ChinaHeilongjiang UniversityHarbin 150080China

Hydrogenation reactions play crucial roles on chemical synthesis and pollutant elimination.The improvement of the ability to activate reactants and increase of the contact probability between the catalysts and reactants are positive to improve the catalytic performance.Herein,we have reported the design of two-dimensional porous Ni-Ni_(3)N-Ni Mo N heterojunction sheets(2D Mo-Ni based nanosheets)for efficient catalytic hydrogenation of the aromatic nitro-compounds.The heterojunction interfaces provide plentiful active sites to improve the activating ability of the catalyst on the reactants.Additionally,the 2D porous structure facilitates not only the contact of catalytic sites with reactants but also mass transfer and diffusion,both of which are favorable to accelerating the hydrogenation process.As a result,the optimized sample of 2D Mo-Ni sheet exhibits good activity for the hydrogenation of aromatic nitro-compounds by converting 0.2 mmol/L(30 mL)of p-nitrophenol to p-aminophenol within 45 s with good recyclability.The activation energy and the reaction rate at 25℃ is 31.11 k J/mol and 0.0796 s^(-1),respectively,both of which surpass most of reported non-noble metal catalysts and rivals with most noble metal-based catalysts.The combination of late and early transition metals provides an innovative way to obtain outstanding catalysts for the hydrogenation.

关键词： Hydrogenation Nitro compounds Two-dimensional sheets Heterojunction Nitrides

Enhanced cycle stability of aprotic Li-O_(2) batteries based on a self-defensed redox mediator

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Chinese Chemical Letters 2024年第3期35卷 449-452页

作者： Guiru Sun Yan Wang Daming Yang Zexu Zhang Wei Lu Ming Feng Key Laboratory of Functional Materials Physics and Chemistry of the Ministry of Education Jilin Normal UniversityChangchun 130103China College of Information Technology Jilin Engineering Research Center of Optoelectronic Materials and DevicesJilin Normal UniversitySiping 136000China

LiBr as a promising redox mediator(RM)has been applied in Li-O_(2)batteries to improve oxygen evolution reaction kinetics and reduce overpotentials.However,the redox shuttle of Br_(3)^-can induce the unexpected reactions and thus cause the degradation of LiBr and the corrosion of Li anode,resulting in the poor cyclability and the low round-trip efficiency.Herein,MgBr_(2)is firstly employed with dual functions for Li-O_(2)batteries,which can serve as a RM and a SEI film-forming agent.The Br^(–)is beneficial to facilitating the decomposition of Li_(2)O_(2)and thus decreasing the overpotential.Additionally,a uniform SEI film containing Mg and MgO generates on Li anode surface by the in-situ spontaneous reactions of Mg^(2+)and Li anode in an O_(2)environment,which can suppress the redox shuttle of Br_(3)^-and improve the interface stability of Li anode and electrolyte.Benefiting from these advantages,the cycle life of Li-O_(2)battery with MgBr_(2)electrolyte is significantly extended.

关键词： MgBr_(2) Redox mediator Redox shuttle Li anode SEI film

Superwettable interface towards biodetection in confined space

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Nano Research 2024年第2期17卷 602-617页

作者： zexu Pang Zhikang Cao Wanlu Li Wenxia Xu Yingying zhang Qitao Zhou Jing Pan Fan Xia State Key Laboratory of Biogeology and Environmental Geology Engineering Research Center of Nano-Geomaterials of the Ministry of EducationFaculty of Materials Science and ChemistryChina University of GeosciencesWuhan 430074China

The detection of biomarkers with both high sensitivity and specificity is crucial for the diagnosis and treatment of related diseases.However,many current detections employ ex-situ detection method and non-confined condition,thus have many problems,which may eventually lead to inaccurate detection results.Compared to detection in non-confined space,detection in confined space can better reflect the real in-vivo situation.Therefore,the construction of detection for target molecules in confined space has great significance for both theoretical research and practical application.To realize the detection of target molecules in confined space,the probes should accurately enter the confined space where the target molecules reside and interact with the interface.Thus,how to explore and utilize the properties of the interface(for example,bioinspired superwettability)has always been a hot and difficult topic in this field.Herein,the recent advances and our efforts in recent 10 years on detection of bio-target molecules in confined space with superwettable interface have been introduced from the perspective of the detection methods.The suitable and most widely employed detection methods for target molecules in confined spaces are introduced firstly.Then,recent progresses for related detections based on visual,optical,and electrochemical detection methods are presented successively.Finally,the perspective for detection in confined space is discussed for the future development of biochemical detection.

关键词： biodetection superwettability confined space interface

三维点云与图像双模态融合的空间目标部件识别方法

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宇航学报 2023年第5期44卷 796-804页

作者：袁萌萌张泽旭哈尔滨工业大学航天学院哈尔滨150001

针对二维图像目标识别准确率高但缺乏空间位置信息,三维点云几何信息精确但无语义信息的特点,为结合不同维度数据的优势,提出一种三维点云与二维图像双模态融合的空间目标部件识别方法。首先基于DeepLabv3+网络进行图像目标分割,并对分... 详细信息

针对二维图像目标识别准确率高但缺乏空间位置信息,三维点云几何信息精确但无语义信息的特点,为结合不同维度数据的优势,提出一种三维点云与二维图像双模态融合的空间目标部件识别方法。首先基于DeepLabv3+网络进行图像目标分割,并对分割目标进行语义标记;其次,提出一种最近邻查找方法降低重建位姿误差带来的三维点云与二维目标映射过程中的语义信息缺失,实现三维点云与二维图像目标间的准确语义关联;最后,利用全连接条件随机场对具备语义信息的三维点云识别结果进行优化,得到更加精细的点云语义标签,融合多视角数据得到最终点云部件识别结果。仿真结果表明相较于传统聚类分割方法,本文方法可以有效地识别出空间目标的各部件,总体识别精度优于95%。

关键词：空间目标部件识别双模态融合语义分割位姿重建全连接条件随机场

基于双层凸优化模型的月面运载器大范围转移最优轨迹规划方法

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深空探测学报（中英文） 2023年第5期10卷 470-480页

作者：乔衍迪张泽旭哈尔滨工业大学深空探测基础研究中心哈尔滨150001

针对月面大范围转移运载器垂直起降、机动次数多且着陆精度要求高的问题,提出了一种基于双层凸优化模型的最优轨迹规划方法。首先,建立运载器质心运动方程,在考虑初始位置、终端位置、速度约束与推力约束等条件下,构建大范围轨迹优化模... 详细信息

针对月面大范围转移运载器垂直起降、机动次数多且着陆精度要求高的问题,提出了一种基于双层凸优化模型的最优轨迹规划方法。首先,建立运载器质心运动方程,在考虑初始位置、终端位置、速度约束与推力约束等条件下,构建大范围轨迹优化模型,对非线性最优问题进行线性化与离散化;其次,将大范围最优轨迹规划问题转换为双层凸优化问题,将动力上升段、大范围动力飞行段、垂直下降段的最优化问题作为内层凸优化问题,通过内点法求解,同时结合燃料最优化目标,设计目标函数,作为外层凸优化问题,通过梯度下降法迭代计算,得到大范围垂直起降的燃料最优轨迹。仿真结果表明,提出的算法可得到运载器大范围转移轨迹的燃料最优解,满足月面运载器高精度软着陆的任务需求;在考虑位置误差的情况下进行蒙特卡洛仿真,结果表明算法具有较好的鲁棒性。

关键词：月面运载器大范围转移双层凸优化轨迹优化最优控制

Optical wafer defect inspection at the 10 nm technology node and beyond

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International Journal of Extreme Manufacturing 2022年第3期4卷 1-24页

作者： Jinlong Zhu Jiamin Liu Tianlai Xu Shuai Yuan Zexu Zhang Hao Jiang Honggang Gu Renjie Zhou Shiyuan Liu State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074People’s Republic of China School of Astronautics Harbin Institute of TechnologyHarbin 150001People’s Republic of China Department of Biomedical Engineering The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARPeople’s Republic of China

The growing demand for electronic devices, smart devices, and the Internet of Things constitutes the primary driving force for marching down the path of decreased critical dimension and increased circuit intricacy of integrated circuits. However, as sub-10 nm high-volume manufacturing is becoming the mainstream, there is greater awareness that defects introduced by original equipment manufacturer components impact yield and manufacturing costs. The identification, positioning, and classification of these defects, including random particles and systematic defects, are becoming more and more challenging at the 10 nm node and beyond.Very recently, the combination of conventional optical defect inspection with emerging techniques such as nanophotonics, optical vortices, computational imaging, quantitative phase imaging, and deep learning is giving the field a new possibility. Hence, it is extremely necessary to make a thorough review for disclosing new perspectives and exciting trends, on the foundation of former great reviews in the field of defect inspection methods. In this article, we give a comprehensive review of the emerging topics in the past decade with a focus on three specific areas:(a) the defect detectability evaluation,(b) the diverse optical inspection systems,and(c) the post-processing algorithms. We hope, this work can be of importance to both new entrants in the field and people who are seeking to use it in interdisciplinary work.

关键词： optical defect inspection microscopy nanophotonics integrated circuits deep learning