Automated structure discovery in atomic force microscopy-Reference-Cited by-同舟云学术

Automated structure discovery in atomic force microscopy

Published:2020-02-28 Issue:9 Volume:6 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Alldritt Benjamin¹^ORCID,Hapala Prokop¹^ORCID,Oinonen Niko¹^ORCID,Urtev Fedor¹²,Krejci Ondrej¹^ORCID,Federici Canova Filippo¹³,Kannala Juho²^ORCID,Schulz Fabian¹^ORCID,Liljeroth Peter¹^ORCID,Foster Adam S.¹⁴⁵^ORCID

Affiliation:

1. Department of Applied Physics, Aalto University, 00076 Aalto, Espoo, Finland.

2. Department of Computer Science, Aalto University, 00076 Aalto, Espoo, Finland.

3. Nanolayers Research Computing Ltd., London, UK.

4. Graduate School Materials Science in Mainz, Staudinger Weg 9, 55128, Germany.

5. WPI Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan.

Abstract

We develop a deep learning method that predicts atomic structure directly from experimental atomic force microscopy images.

Funder

European Research Council

Suomen Akatemia

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference76 articles.

1. The Art of SPM: Scanning Probe Microscopy in Materials Science

2. Atomic Force Microscope

3. Advances in atomic force microscopy

4. S. Morita F. J. Giessibl E. Meyer R. Wiesendanger Noncontact Atomic Force Microscopy (Springer International Publishing Cham 2015).

5. Generation, manipulation and characterization of molecules by atomic force microscopy

Cited by 81 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancing scanning probe microscopy simulations: A decade of development in probe-particle models;Computer Physics Communications;2024-12

2. Scanning Probe Microscopy Characterization of Biomolecules enabled by Mass‐Selective, Soft‐landing Electrospray Ion Beam Deposition;ChemPhysChem;2024-08-25

3. Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines;ACS Applied Materials & Interfaces;2024-08-20

4. How scanning probe microscopy can be supported by artificial intelligence and quantum computing?;Microscopy Research and Technique;2024-06-12

5. Crystal growth characterization of WSe2 thin film using machine learning;Materials Today Advances;2024-06