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Institution

University of Science and Technology Beijing

EducationBeijing, China
About: University of Science and Technology Beijing is a education organization based out in Beijing, China. It is known for research contribution in the topics: Microstructure & Alloy. The organization has 41558 authors who have published 44473 publications receiving 623229 citations. The organization is also known as: Beijing Steel and Iron Institute.


Papers
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Journal ArticleDOI
TL;DR: The study emphasized the significance of effective environmental management, particularly to ensure food security near battery facilities, and the non-cancer risks to children were 3-10 times higher than the acceptable level of 1, while the cancer risks were 5-200 times higher.

150 citations

Journal ArticleDOI
TL;DR: In this paper, the corrosion behavior of AZ91 magnesium alloy in dilute NaCl solutions was studied using electrochemical measurements, whereby a corrosion map in terms of electrode potential and chloride concentration [Cl − ] was obtained.

150 citations

Journal ArticleDOI
TL;DR: This paper develops a framework that enables the robot to learn both movement and stiffness features from the human tutor and can be efficiently realized by the proposed framework.
Abstract: One promising approach for robots efficiently learning skills is to learn manipulation skills from human tutors by demonstration and then generalize these learned skills to complete new tasks. Traditional learning and generalization methods, however, have not well considered human impedance features, which makes the skills less humanlike and restricted in physical human–robot interaction scenarios. In particular, stiffness generalization has not been well considered. This paper develops a framework that enables the robot to learn both movement and stiffness features from the human tutor. To this end, the upper limb muscle activities of the human tutor are monitored to extract variable stiffness in real time, and the estimated human arm endpoint stiffness is properly mapped into the robot impedance controller. Then, a dynamic movement primitives model is extended and employed to simultaneously encode the movement trajectories and the stiffness profiles. In this way, both position trajectory and stiffness profile are considered for robot motion control in this paper to realize a more complete skill transfer process. More importantly, stiffness generalization and movement generalization can be efficiently realized by the proposed framework. Experimental tests have been performed on a dual-arm Baxter robot to verify the effectiveness of the proposed method.

150 citations

Journal ArticleDOI
TL;DR: The designed unique architecture allows efficient use of pseudo‐capacitive Mn2O3 nanomaterials for charge storage with facilitated transport for both ions and electrons, rendering them high specific capacitance, good rate capability, and remarkable cycling performance.
Abstract: Multi-shelled Mn2O3 hollow microspheres have been achieved through a pH-regulated method and used as supercapacitor electrodes. The designed unique architecture allows efficient use of pseudo-capacitive Mn2O3 nanomaterials for charge storage with facilitated transport for both ions and electrons, rendering them high specific capacitance, good rate capability, and remarkable cycling performance.

150 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a hybrid liquid air energy storage (LAES) configuration, whereby the excess heat of compression is used as a heat source to power an organic Rankine Cycle (ORC), whereas a Vapor Compression Refrigeration Cycle (VCRC) acts as aheat sink, leading to the production of additional electricity.

150 citations


Authors

Showing all 41904 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Yang Yang1712644153049
Jun Chen136185677368
Jun Lu135152699767
Jie Liu131153168891
Shuai Liu129109580823
Jian Zhou128300791402
Chao Zhang127311984711
Shaobin Wang12687252463
Tao Zhang123277283866
Jian Liu117209073156
Xin Li114277871389
Jianhui Hou11042953265
Hong Wang110163351811
Baoshan Xing10982348944
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023161
2022807
20214,664
20204,369
20194,164
20183,586