Dataset: Automated iterative refinement of uncertain parameters in an optical floating zone experiment and temperatures obtained using optimized parameters




Files
37
2.78 MB
Samples
0
in dataset
Workflows
0
documented
Views
863
total views
Downloads
223
total downloads
Published
Mar 13, 2021
5 years ago

File Types

37 files across 2 type(s)

Composition

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Published
Published: 5 years ago
Views
863
Downloads
223
Total Size
2.78 MB
Description

This dataset contains the raw and processed data used in the manuscript in revision titled "Automated extraction of physical parameters from experimentally obtained thermal profiles using a machine learning approach". This dataset contains (1) sampled vectors and their errors at each iteration, (2) the experimental and simulated temperature profiles (using the optimized parameters) in optical floating zone experiments, and (3) the experimental and simulated time dependent temperatures (using the optimized parameters) in optical floating zone experiments. The dataset is subject to be updated in the revision process.

Excel 16 Text 21
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Related Papers
Huang, G., Zhang, M., Montiel, D., Soundararajan, P., Wang, Y., Denney, J. J., Corrao, A. A., Khalifah, P. G. and Thornton, K. Automated Extraction of Physical Parameters from Experimentally Obtained Thermal Profiles Using a Machine Learning Approach. Computational Materials Science 194, 110459, doi:10.1016/j.commatsci.2021.110459 (2021).
Funding
This work was supported as part of GENESIS: A Next Generation Synthesis Center, an Energy Frontier Research Center funded by the US Department of Energy (DOE), Office of Science, Basic Energy Sciences under award No. DE-SC0019212. This research used beamline 28-ID-1 of the National Synchrotron Light Source II, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Brookhaven National Laboratory under Contract No. DE-SC0012704.