|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Insight into the influence of high temperature annealing on the onset potential of Ti-doped hematite photoanodes for solar water splitting显示文摘For Ti-doped hematite photoanodes, high temperature annealing drastically increases the water oxidation plateau photocurrent, but also induces an anodic shift of onset potential by about 100 m V, thus hindering the performance under low applied bias. To the best of our knowledge, the effects of high temperature annealing on the onset potential have been rarely studied. Herein, both X-ray photoelectron spectroscopy(XPS) measurements and theoretical calculations indicated that the increase of surface Ti/Fe atomic ratio after high temperature annealing decreased the adsorption capacity of hydroxide ions on the hematite surface. Subsequently, the flatband potential(i.e., the theoretical onset potential) of Ti doped hematite photoanodes positively shifted, which was supported by the Mott-Schottky measurements. | Yaodong Zhu Qinfeng Qian Guozheng Fan Zhili Zhu Xin Wang Zhaosheng Li Zhigang Zou | 2018 | Chinese Chemical Letters2018，29，6： | 1 |
| 2 | Perovskite bridging PbS quantum dot/polymer interface enables efficient solar cells显示文摘Conjugated polymers have been explored as promising hole-transporting layer(HTL)in lead sulfide(PbS)quantum dot(QD)solar cells.The fine regulation of the inorganic/organic interface is pivotal to realize high device performance.In this work,we propose using CsPbI_(3) QDs as the interfacial layer between PbS QD active layer and organic polymer HTL.The relative soft perovskite can mediate the interface and form favorable energy level alignment,improving charge extraction and reducing interfacial charge recombination.As a result,the photovoltaic performance can be efficiently improved from 10.50%to 12.32%.This work may provide new guidelines to the device structural design of QD optoelectronics by integrating different solutionprocessed semiconductors. | Xing Meng Yifan Chen Fan Yang Jieqi Zhang Guozheng Shi Yannan Zhang Haodong Tang Wei Chen Yang Liu Lin Yuan Shaojuan Li Kai Wang Qi Chen Zeke Liu Wanli Ma | 2022 | Nano Research2022，15，7： | 1 |
| 3 | An Open Communication Architecture for Distribution Automation Based on IEC 61850显示文摘 | Guozheng Han Bingyin Xu Kaijun Fan | 2013 | International Journal of Electrical Power and Energy Systems2013，，： | 1 |
| 4 | Achieving work hardening by forming boundaries on the nanoscale in a Ti-based metallic glass matrix composite显示文摘Achieving work hardening in metallic glass matrix composites(MGMCs) is the key to the extensive use of these attractive materials in structural and functional applications.In this study,we investigated the formation of nanoscale boundaries resulted from the interaction between matrix and dendrites,which favors the work-hardening deformation in an in-situ Ti41Zr32Ni6 Ta7 Be14 MGMC with β-Ti dendrites in a glassy matrix at room temperature.The microstructures of samples after tension were observed by highresolution transmission electron microscopy(HRTEM) and X-ray diffraction(XRD).The work-hardening mechanism of the present composites involves:(1) appearance of dense dislocation walls(DDWs),(2)proliferation of shear bands,(3) fo rmation of boundaries on the nanoscale,and(4) interactions between hard and soft phases.A theoretical model combined with experimental data reveals the deformation mechanisms in the present work,proving that the in-situ dendrites with outstanding hardening ability in the glass matrix can provide the homogeneous deformation under tensile loading at room temperature. | Jing Fan Wei Rao Junwei Qiao PKLiaw Daniel Sopu Daniel Kiener Jürgen Eckert Guozheng Kang Yucheng Wu | 2020 | Journal of Materials Science & Technology2020，47，15： | 0 |
| 5 | Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control显示文摘With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way. | Shixiong Fan Jianbo Guo Shicong Ma Lixin Li Guozheng Wang Haotian Xu Jin Yang Zening Zhao | 2024 | CSEE Journal of Power and Energy Systems2024，10，1： | 0 |
| 6 | Progress of Brain Network Studies on Anesthesia and Consciousness: Framework and Clinical Applications显示文摘Although the relationship between anesthesia and consciousness has been investigated for decades, our understanding of the underlying neural mechanisms of anesthesia and consciousness remains rudimentary, which limits the development of systems for anesthesia monitoring and consciousness evaluation. Moreover, the current practices for anesthesia monitoring are mainly based on methods that do not provide adequate information and may present obstacles to the precise application of anesthesia. Most recently, there has been a growing trend to utilize brain network analysis to reveal the mechanisms of anesthesia, with the aim of providing novel insights to promote practical application. This review summarizes recent research on brain network studies of anesthesia, and compares the underlying neural mechanisms of consciousness and anesthesia along with the neural signs and measures of the distinct aspects of neural activity. Using the theory of cortical fragmentation as a starting point, we introduce important methods and research involving connectivity and network analysis. We demonstrate that whole-brain multimodal network data can provide important supplementary clinical information. More importantly, this review posits that brain network methods, if simplified, will likely play an important role in improving the current clinical anesthesia monitoring systems. | Jun Liu Kangli Dong Yi Sun Ioannis Kakkos Fan Huang Guozheng Wang Peng Qi Xing Chen Delin Zhang Anastasios Bezerianos Yu Sun | 2023 | Engineering2023，，1： | 0 |
| 7 | Data-driven Transient Stability Assessment Using Sparse PMU Sampling and Online Self-check Function显示文摘Artificial intelligence technologies provide a newapproach for the real-time transient stability assessment (TSA)of large-scale power systems. In this paper, we propose a datadriven transient stability assessment model (DTSA) that combinesdifferent AI algorithms. A pre-AI based on the time-delay neuralnetwork is designed to locate the dominant buses for installingthe phase measurement units (PMUs) and reducing the datadimension. A post-AI is designed based on the bidirectionallong-short-term memory network to generate an accurate TSAwith sparse PUM sampling. An online self-check function of theonline TSA’s validity when the power system changes is furtheradded by comparing the results of the pre-AI and the post-AI.The IEEE 39-bus system and the 300-bus AC/DC hybrid systemestablished by referring to China’s existing power system areadopted to verify the proposed method. Results indicate that theproposed method can effectively reduce the computation costswith ensured TSA accuracy as well as provide feedback forits applicability. The DTSA provides new insights for properlyintegrating varied AI algorithms to solve practical problems inmodern power systems. | Guozheng Wang Jianbo Guo Shicong Ma Xi Zhang Qinglai Guo Shixiong Fan Haotian Xu | 2023 | CSEE Journal of Power and Energy Systems2023，9，3： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员