Precise Surface Profiling at the Nanoscale Enabled by Deep Learning-Reference-Cited by-同舟云学术

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Precise Surface Profiling at the Nanoscale Enabled by Deep Learning

Published:2024-01-22 Issue:8 Volume:24 Page:2589-2595
ISSN:1530-6984
Container-title:Nano Letters
language:en
Short-container-title:Nano Lett.

Author:

Bonagiri Lalith Krishna Samanth¹²^ORCID,Wang Zirui³,Zhou Shan¹³^ORCID,Zhang Yingjie¹³⁴^ORCID

Affiliation:

1. Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801, United States

2. Department of Mechanical Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States

3. Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States

4. Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana, Illinois 61801, United States

Funder

Arnold and Mabel Beckman Foundation

National Science Foundation

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.nanolett.3c04712

Reference65 articles.

1. How Surface Topography Relates to Materials' Properties

2. Metrology for the next generation of semiconductor devices

3. Technology and metrology of new electronic materials and devices

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1. A review of artificial intelligent methods for machined surface roughness prediction;Tribology International;2024-11

2. Recent advances in molecular dynamics simulations for dry friction on rough substrate;Journal of Physics D: Applied Physics;2024-09-03

3. Electrical Double Layers Modulate the Growth of Solid–Electrolyte Interphases;Chemistry of Materials;2024-08-19

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