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Institution

University of Electronic Science and Technology of China

EducationChengdu, China
About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Antenna (radio) & Dielectric. The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.


Papers
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Journal ArticleDOI
TL;DR: In this article, the progress of non-van der Waals (non-vdW) 2D materials with numerous chemical bonds in all three dimensions and novel chemical and electronic properties beyond those of vdW 2D material have been studied increasingly over the past decades.
Abstract: The exploration of efficient electrocatalysts for energy conversion is important for green energy development. Owing to their high surface areas and unusual electronic structure, 2D electrocatalysts have attracted increasing interest. Among them, non-van der Waals (non-vdW) 2D materials with numerous chemical bonds in all three dimensions and novel chemical and electronic properties beyond those of vdW 2D materials have been studied increasingly over the past decades. Herein, the progress of non-vdW 2D electrocatalysts is critically reviewed, with a special emphasis on electronic structure modulation. Strategies for heteroatom doping, vacancy engineering, pore creation, alloying, and heterostructure engineering are analyzed for tuning electronic structures and achieving intrinsically enhanced electrocatalytic performances. Lastly, a roadmap for the future development of non-vdW 2D electrocatalysts is provided from material, mechanism, and performance viewpoints.

157 citations

Journal ArticleDOI
TL;DR: The proportion of nosocomial infection in patients with COVID-19 was 44% in the early outbreak, and nurses and doctors were the most affected among the infected medical staff.
Abstract: Background COVID-19, a disease caused by SARS-CoV-2 coronavirus, has now spread to most countries and regions of the world. As patients potentially infected by SARS-CoV-2 need to visit hospitals, the incidence of nosocomial infection can be expected to be high. Therefore, a comprehensive and objective understanding of nosocomial infection is needed to guide the prevention and control of the epidemic. Methods We searched major international and Chinese databases: Medicine, Web of Science, Embase, Cochrane, CBM (China Biology Medicine disc), CNKI (China National Knowledge Infrastructure) and Wanfang database for case series or case reports on nosocomial infections of COVID-19, SARS (severe acute respiratory syndromes) and MERS (Middle East respiratory syndrome) from their inception to March 31st, 2020. We conducted a meta-analysis of the proportion of nosocomial infection patients in the diagnosed patients, occupational distribution of nosocomial infection medical staff. Results We included 40 studies. Among the confirmed patients, the proportions of nosocomial infections with early outbreaks of COVID-19, SARS, and MERS were 44.0%, 36.0%, and 56.0%, respectively. Of the confirmed patients, the medical staff and other hospital-acquired infections accounted for 33.0% and 2.0% of COVID-19 cases, 37.0% and 24.0% of SARS cases, and 19.0% and 36.0% of MERS cases, respectively. Nurses and doctors were the most affected among the infected medical staff. The mean numbers of secondary cases caused by one index patient were 29.3 and 6.3 for SARS and MERS, respectively. Conclusions The proportion of nosocomial infection in patients with COVID-19 was 44% in the early outbreak. Patients attending hospitals should take personal protection. Medical staff should be awareness of the disease to protect themselves and the patients.

157 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an overview of TENG enabled self-powered respiration monitoring, with a focus on the working principle, sensing materials, functional structures, and related applications in both physical respiration motion detection and chemical breath analysis.
Abstract: In mammals, physiological respiration involves respiratory cycles of inhaled and exhaled breaths, which has traditionally been an underutilized resource potentially encompassing a wealth of physiologically relevant information as well as clues to potential diseases. Recently, triboelectric nanogenerators (TENGs) have been widely adopted for self-powered respiration monitoring owing to their compelling features, such as decent biocompatibility, wearing comfort, low-cost, and high sensitivity to respiration activities in the aspect of low frequency and slight amplitude body motions. Physiological respiration behaviors and exhaled chemical regents can be precisely and continuously monitored by TENG-based respiration sensors for personalized health care. This article presents an overview of TENG enabled self-powered respiration monitoring, with a focus on the working principle, sensing materials, functional structures, and related applications in both physical respiration motion detection and chemical breath analysis. Concepts and approaches for acquisition of physical information associated with respiratory rate and depth are covered in the first part. Then the sensing mechanism, theoretical modeling, and applications related to detection of chemicals released from breathing gases are systemically summarized. Finally, the opportunities and challenges of triboelectric effect enabled self-powered respiration monitoring are comprehensively discussed and criticized.

157 citations

Journal ArticleDOI
TL;DR: A new low-temperature procedure has been used for preparing micro-mesoporous carbon-doped TiO2 photocatalysts, with anatase pore wall and substitutional carbon occupying oxygen sites, which exhibit outstanding photoc atalytic activity under visible light irradiation.

157 citations

Journal ArticleDOI
TL;DR: The results showed that the proposed consensus model can integrate opinions of participants using diverse preference formats and reach an agreement efficiently, and was proven by theoretical and simulation analyses.

157 citations


Authors

Showing all 51090 results

NameH-indexPapersCitations
Gang Chen1673372149819
Frede Blaabjerg1472161112017
Kuo-Chen Chou14348757711
Yi Yang143245692268
Guanrong Chen141165292218
Shuit-Tong Lee138112177112
Lei Zhang135224099365
Rajkumar Buyya133106695164
Lei Zhang130231286950
Bin Wang126222674364
Haiyan Wang119167486091
Bo Wang119290584863
Yi Zhang11643673227
Qiang Yang112111771540
Chun-Sing Lee10997747957
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023159
2022980
20217,384
20207,220
20196,976