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Thin Oxide Film Ellipsometry for ML Applications

Description: A series of over 13,000 measurements taken with an FS-1 ellipsometer, and the parameters of a multi-oscillator model found using Gaussian Regression. Intended for use in material discovery.
Authors: Marchione, Olivia A. C.; University of Waterloo
Keywords: Nanomaterials
Machine learning
GPR
AI
Artificial intelligence
Oxides
Atomic layer deposition
Thin films
Semiconductors
Field of Research: 
Materials engineering and resources engineering
>
Materials engineering
>
Materials engineering, not elsewhere classified
Publication Date: 2023-09-19
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
Funder: University of Waterloo; The University of Waterloo Faculty of Engineering Advanced Manufacturing Doctoral Fellowship
University of Waterloo; The University of Waterloo Deans Entrance Fellowship
Natural Sciences and Engineering Research Council of Canada; The NSERC Discovery Program; RGPIN-2017-04212
Natural Sciences and Engineering Research Council of Canada; The NSERC Discovery Program; RGPAS-2017-507977
Canadian Foundation for Innovation; John R. Evans Leaders Fund; Project 35552
Canada Foundation for Innovation; Exceptional Opportunities Fund COVID-19; Project 41017
Ontario Research Fund; The Ontario Research Fund - Research Infrastructure; Project 35552
URI: https://doi.org/10.20383/103.0805
Geographic Coverage: 
City
Waterloo
Province /
Province / Territory
Ontario
Territory
 
Country
Canada

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Access to this dataset is subject to the following terms:
Creative Commons Public Domain Dedication (CC0 1.0) https://creativecommons.org/publicdomain/zero/1.0/
Citation
Marchione, O. (2023). Thin Oxide Film Ellipsometry for ML Applications. Federated Research Data Repository. https://doi.org/10.20383/103.0805