Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning-Reference-Cited by-同舟云学术

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Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning

Published:2022-06-22 Issue:7 Volume:16 Page:10314-10326
ISSN:1936-0851
Container-title:ACS Nano
language:en
Short-container-title:ACS Nano

Author:

Cha Eunju¹^ORCID,Chung Hyungjin²^ORCID,Jang Jaeduck¹^ORCID,Lee Junho¹^ORCID,Lee Eunha¹^ORCID,Ye Jong Chul³^ORCID

Affiliation:

1. Samsung Advanced Institute of Technology, Samsung Electronics, Gyeonggi-do 16678, Republic of Korea

2. Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

3. Kim Jae Chul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

Funder

Samsung Advanced Institute of Technology

Publisher

American Chemical Society (ACS)

Subject

General Physics and Astronomy,General Engineering,General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsnano.2c00168

Reference33 articles.

1. A bimodal tomographic reconstruction technique combining EDS-STEM and HAADF-STEM

2. Correlative HAADF-STEM and EDX-STEM Tomography for the 3D Morphological and Elemental Analysis of FinFET Semiconductor Devices

3. Semiconductor Clusters, Nanocrystals, and Quantum Dots

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