Sequential piezoresponse force microscopy and the ‘small-data’ problem-Reference-Cited by-同舟云学术

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Sequential piezoresponse force microscopy and the ‘small-data’ problem

Published:2018-06-21 Issue:1 Volume:4 Page:
ISSN:2057-3960
Container-title:npj Computational Materials
language:en
Short-container-title:npj Comput Mater

Author:

Trivedi Harsh^ORCID,Shvartsman Vladimir V.^ORCID,Medeiros Marco S. A.,Pullar Robert C.,Lupascu Doru C.

Funder

European Commission (EC)

Deutsche Forschungsgemeinschaft (German Research Foundation)

Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa (FCT/UNL)

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Mechanics of Materials,General Materials Science,Modeling and Simulation

Link

http://www.nature.com/articles/s41524-018-0084-9.pdf

Reference54 articles.

1. Laanait, N., Zhang, Z. & Schleputz, C. M. Imaging nanoscale lattice variations by machine learning of x-ray diffraction. Nanotechnology 27, 374002–374011 (2016).

2. Shinzawa, H., Awa, K., Kanematsu, W. & Ozaki, Y. Multivariate data analysis for Raman spectroscopic imaging. J. Raman Spectrosc. 40, 1720–1725 (2009).

3. Kalinin, S. V. et al. Big, deep, and smart data in scanning probe microscopy. ACS NANO 10, 9068 (2016).

4. Ceguerra, A. V. et al. The rise of computational techniques in atom probe microscopy. Curr. Opin. Solid State Mater. Sci. 17, 224–235 (2013).

5. Hu, Y. et al. A nonrelational data warehouse for the analysis of field and laboratory data from multiple. IEEE J. Photovolt. 7, 230–236 (2017).

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