Deep-Learning-Based Deconvolution of Mechanical Stimuli with Ti3C2Tx MXene Electromagnetic Shield Architecture via Dual-Mode Wireless Signal Variation Mechanism-Reference-Cited by-同舟云学术

Deep-Learning-Based Deconvolution of Mechanical Stimuli with Ti3C2Tx MXene Electromagnetic Shield Architecture via Dual-Mode Wireless Signal Variation Mechanism

Published:2020-08-19 Issue:9 Volume:14 Page:11962-11972
ISSN:1936-0851
Container-title:ACS Nano
language:en
Short-container-title:ACS Nano

Author:

Lee Gun-Hee¹,Lee Gang San²,Byun Junyoung³,Yang Jun Chang¹,Jang Chorom⁴,Kim Seongrak¹,Kim Hyeonji¹,Park Jin-Kwan⁴,Lee Ho Jin²,Yook Jong-Gwan⁴,Kim Sang Ouk²,Park Steve¹

Affiliation:

1. Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

2. National Creative Research Initiative Center for Multi-dimensional Directed Nanoscale Assembly, Department of Materials Science and Engineering, KAIST Institute for Nanocentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

3. School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

4. School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea

Funder

National Research Foundation of Korea

Korea Institute of Science and Technology

KAIST

Multi-Dimensional Directed Nanoscale Assembly Center

Publisher

American Chemical Society (ACS)

Subject

General Physics and Astronomy,General Engineering,General Materials Science

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