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Machine Learning Optimization of P-Type Transparent Conducting Films
29 July 2019, Version 2
Working Paper
Authors
Lingfei Wei
,
Xiaojie Xu
,
Gurudayal
,
James Bullock
,
Joel Ager
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This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.
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Abstract
Strategic design of experiments combined with machine learning is used to optimize the synthesis of p-type transparent conductors.
Keywords
transparent conductors
machine learning
support vector regression
design of experiment
Supplementary materials
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SI TCM ML ChemRxvi 2019-07-29
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Now Published
Machine Learning Optimization of p-Type Transparent Conducting Films
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Lingfei Wei, Xiaojie Xu, Gurudayal, James Bullock, Joel W. Ager
journal article
Chemistry of Materials
, Volume 31, Issue 18
Online publication date: Aug 14, 2019
Version History
Jul 29, 2019 Version 2
May 20, 2019 Version 1
Version Notes
Revsed version 29 July 2019
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ND
The content is available under
CC BY NC ND 4.0
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DOI
10.26434/chemrxiv.8145986.v2
D O I: 10.26434/chemrxiv.8145986.v2 [opens in a new tab]
Funding
US Department of Energy
Author’s competing interest statement
The authors declare no competing financial interests.
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