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Institution

Beijing University of Technology

EducationBeijing, Beijing, China
About: Beijing University of Technology is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Microstructure & Computer science. The organization has 31929 authors who have published 31987 publications receiving 352112 citations. The organization is also known as: Běijīng Gōngyè Dàxué & Beijing Polytechnic University.


Papers
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Journal ArticleDOI
TL;DR: This survey investigates some of the work that has been done to enable the integrated blockchain and edge computing system and discusses the research challenges, identifying several vital aspects of the integration of blockchain andEdge computing: motivations, frameworks, enabling functionalities, and challenges.
Abstract: Blockchain, as the underlying technology of crypto-currencies, has attracted significant attention. It has been adopted in numerous applications, such as smart grid and Internet-of-Things. However, there is a significant scalability barrier for blockchain, which limits its ability to support services with frequent transactions. On the other side, edge computing is introduced to extend the cloud resources and services to be distributed at the edge of the network, but currently faces challenges in its decentralized management and security. The integration of blockchain and edge computing into one system can enable reliable access and control of the network, storage, and computation distributed at the edges, hence providing a large scale of network servers, data storage, and validity computation near the end in a secure manner. Despite the prospect of integrated blockchain and edge computing systems, its scalability enhancement, self organization, functions integration, resource management, and new security issues remain to be addressed before widespread deployment. In this survey, we investigate some of the work that has been done to enable the integrated blockchain and edge computing system and discuss the research challenges. We identify several vital aspects of the integration of blockchain and edge computing: motivations, frameworks, enabling functionalities, and challenges. Finally, some broader perspectives are explored.

488 citations

Journal ArticleDOI
TL;DR: In this article, a solid electrolyte is injected into the grain boundaries of the secondary particles of the Ni-rich layered lithium transition metal oxides to prevent penetration of liquid electrolyte into the boundaries, and eliminate the detrimental factors, which include cathode-liquid electrolyte interfacial reactions, intergranular cracking and layered-to-spinel phase transformation.
Abstract: A critical challenge for the commercialization of layer-structured nickel-rich lithium transition metal oxide cathodes for battery applications is their capacity and voltage fading, which originate from the disintegration and lattice phase transition of the cathode particles. The general approach of cathode particle surface modification could partially alleviate the degradation associated with surface processes, but it still fails to resolve this critical barrier. Here, we report that infusing the grain boundaries of cathode secondary particles with a solid electrolyte dramatically enhances the capacity retention and voltage stability of the cathode. We find that the solid electrolyte infused in the boundaries not only acts as a fast channel for lithium-ion transport, it also, more importantly, prevents penetration of the liquid electrolyte into the boundaries, and consequently eliminates the detrimental factors, which include cathode–liquid electrolyte interfacial reactions, intergranular cracking and layered-to-spinel phase transformation. This grain-boundary engineering approach provides design ideas for advanced cathodes for batteries. The development of Ni-rich layered lithium transition metal oxides is plagued by their voltage and capacity fading on battery cycling. Here, the authors demonstrate an effective approach to treat these problems by infusing a solid electrolyte into the grain boundaries of the secondary particles of these layered materials.

483 citations

Journal ArticleDOI
TL;DR: Inconel 718 superalloy has been fabricated by selective laser melting technology (SLM), and its microstructure and mechanical properties were studied under solution+aging (SA) standard heat treatment, homogenization+solution+solutionsolution + aging (HSA), and as-fabricated conditions as discussed by the authors.
Abstract: Inconel 718 superalloy has been fabricated by selective laser melting technology (SLM). Its microstructure and mechanical properties were studied under solution+aging (SA) standard heat treatment, homogenization+solution+aging (HSA) standard heat treatment and as-fabricated conditions. Precipitated phases and microstructures were examined using OM, SEM, TEM and X-ray analysis methods. The fine dendrite structures with an average dendrite arm spacing of approximately 698 nm accompanying some interdendritic Laves phases and carbide particles can be observed in the as-fabricated materials. After standard heat treatments, dendrite microstructures are substituted by recrystallization grains, and Laves phases also dissolve into the matrix to precipitate strengthening phases and δ particles. The test values of all specimens meet Aerospace Material Specification for cast Inconel 718 alloy, and the transgranular ductile fracture mode exists for the three conditions. The strength and hardness of heat-treated SLM materials increase and are comparable with wrought Inconel 718 alloy, whereas their ductility decreases significantly compared with the as-fabricated material. This is because of the precipitation of fine γˊ and γ〞strengthening phases and needle-like δ phases. For the as-fabricated alloy, the formation of finer dislocated cellular structures that develop into a ductile dimple fracture shows excellent ductility. Due to dislocation pinning from γˊ and γ〞strengthening phases and the impediment of dislocation motion caused by the needle-like δ phases, the ductility of the SA materials decreases and causes a transgranular fracture, compared with the as-fabricated samples.

467 citations

Journal ArticleDOI
TL;DR: The impact of the gradient in-plane strain on the carrier dynamics of the strained perovskite films and optimize the device efficiency is studied to enhance PCEs up to 20.7% (certified) in devices via rational strain engineering.
Abstract: The mixed halide perovskites have emerged as outstanding light absorbers for efficient solar cells. Unfortunately, it reveals inhomogeneity in these polycrystalline films due to composition separation, which leads to local lattice mismatches and emergent residual strains consequently. Thus far, the understanding of these residual strains and their effects on photovoltaic device performance is absent. Herein we study the evolution of residual strain over the films by depth-dependent grazing incident X-ray diffraction measurements. We identify the gradient distribution of in-plane strain component perpendicular to the substrate. Moreover, we reveal its impacts on the carrier dynamics over corresponding solar cells, which is stemmed from the strain induced energy bands bending of the perovskite absorber as indicated by first-principles calculations. Eventually, we modulate the status of residual strains in a controllable manner, which leads to enhanced PCEs up to 20.7% (certified) in devices via rational strain engineering. The residual strains in the mixed halide perovskite thin films and their effects on the solar cell devices are less understood. Here Zhu et al. study the impact of the gradient in-plane strain on the carrier dynamics of the strained perovskite films and optimize the device efficiency.

455 citations

Journal ArticleDOI
TL;DR: The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies and paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands.
Abstract: A recent surge of interest in building energy consumption has generated a tremendous amount of energy data, which boosts the data-driven algorithms for broad application throughout the building industry. This article reviews the prevailing data-driven approaches used in building energy analysis under different archetypes and granularities, including those methods for prediction (artificial neural networks, support vector machines, statistical regression, decision tree and genetic algorithm) and those methods for classification (K-mean clustering, self-organizing map and hierarchy clustering). The review results demonstrate that the data-driven approaches have well addressed a large variety of building energy related applications, such as load forecasting and prediction, energy pattern profiling, regional energy-consumption mapping, benchmarking for building stocks, global retrofit strategies and guideline making etc. Significantly, this review refines a few key tasks for modification of the data-driven approaches in the context of application to building energy analysis. The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies. It also paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands. All these will be useful to establish a better long-term strategy for urban sustainability.

447 citations


Authors

Showing all 32228 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Pulickel M. Ajayan1761223136241
James M. Tour14385991364
Dacheng Tao133136268263
Lei Zhang130231286950
Hong-Cai Zhou11448966320
Xiaodong Li104130049024
Lin Li104202761709
Ming Li103166962672
Wenjun Zhang9697638530
Lianzhou Wang9559631438
Miroslav Krstic9595542886
Zhiguo Yuan9363328645
Xiang Gao92135942047
Xiao-yan Li8552831861
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023124
2022611
20213,573
20203,341
20193,075
20182,523