M
Mingwei Chen
Researcher at Johns Hopkins University
Publications - 1108
Citations - 63568
Mingwei Chen is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 108, co-authored 536 publications receiving 51351 citations. Previous affiliations of Mingwei Chen include National Taiwan University & Chiba University.
Papers
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Journal ArticleDOI
Front-contact passivation through 2D/3D perovskite heterojunctions enables efficient bifacial perovskite/silicon tandem solar cells
Esma Ugur,Erkan Aydin,Michele De Bastiani,George T. Harrison,Bumin K. Yildirim,Sam Teale,Mingwei Chen,Jiang Liu,Mingcong Wang,Akmaral Seitkhan,Maxime Babics,Anand S. Subbiah,Ahmed Ali Said,Randi Azmi,Atteq ur Rehman,Thomas Allen,Philip Schulz,Edward H. Sargent,Frédéric Laquai,Stefaan De Wolf +19 more
TL;DR: In this paper , a structural isomer of butylammonium (BA) as a small organic cation occupied the A-site of the 2D perovskite lattice.
Journal ArticleDOI
miR-4433a-3p promotes granulosa cell apoptosis by targeting peroxisome proliferator–activated receptor alpha and inducing immune cell infiltration in polycystic ovarian syndrome
Journal ArticleDOI
Experimental investigation on heat transfer performance during electrospray cooling with ethanol–R141b mixture
Jiameng Tian,Lingwen Kong,Bu-Yang Li,Yiqi Chen,Zhentao Wang,Junfeng Wang,Mingwei Chen,Junhui Xiong +7 more
TL;DR: In this paper , an experimental investigation on the cooling performance triggered by electrospray impingement is presented, which shows that adding ethanol to R141b improves the electrohydrodynamic (EHD) atomization, namely reducing Sauter mean diameter and increasing spray angle.
Proceedings ArticleDOI
Application of Deep Learning in Microseismic Waveform Classification: A Case Study of The Yebatan Hydropower Station Project
TL;DR: In this paper , an enhanced convolutional natural network (ECNN) based on ACGAN structure was proposed for microseismic waveforms classification, where the generator is used to synthesize samples of specified type and the discriminator was used to identify class and authenticity.
Proceedings ArticleDOI
Classroom head-up rate detection based on RNN-CNN image recognition algorithm
Mingwei Chen,Zixian Gao +1 more
TL;DR: In this article , a combination of CNN and RNN was used to improve the accuracy and robustness of head rate detection in the classroom environment, which can effectively adapt to changes in the head posture of different students and environments.