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Title: Automatized convergence of optoelectronic simulations using active machine learning

Authors:
ORCiD logo [1];  [2];  [3];  [4]; ORCiD logo [5]
  1. Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, United Kingdom, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA, Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
  2. Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, United Kingdom, Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
  3. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA, Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
  4. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
  5. Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, United Kingdom
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1372511
Grant/Contract Number:  
20140013DR
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Applied Physics Letters
Additional Journal Information:
Journal Name: Applied Physics Letters Journal Volume: 111 Journal Issue: 4; Journal ID: ISSN 0003-6951
Publisher:
American Institute of Physics
Country of Publication:
United States
Language:
English

Citation Formats

Rouet-Leduc, Bertrand, Hulbert, Claudia, Barros, Kipton, Lookman, Turab, and Humphreys, Colin J. Automatized convergence of optoelectronic simulations using active machine learning. United States: N. p., 2017. Web. doi:10.1063/1.4996233.
Rouet-Leduc, Bertrand, Hulbert, Claudia, Barros, Kipton, Lookman, Turab, & Humphreys, Colin J. Automatized convergence of optoelectronic simulations using active machine learning. United States. doi:10.1063/1.4996233.
Rouet-Leduc, Bertrand, Hulbert, Claudia, Barros, Kipton, Lookman, Turab, and Humphreys, Colin J. Mon . "Automatized convergence of optoelectronic simulations using active machine learning". United States. doi:10.1063/1.4996233.
@article{osti_1372511,
title = {Automatized convergence of optoelectronic simulations using active machine learning},
author = {Rouet-Leduc, Bertrand and Hulbert, Claudia and Barros, Kipton and Lookman, Turab and Humphreys, Colin J.},
abstractNote = {},
doi = {10.1063/1.4996233},
journal = {Applied Physics Letters},
number = 4,
volume = 111,
place = {United States},
year = {2017},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1063/1.4996233

Citation Metrics:
Cited by: 1 work
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Works referenced in this record:

An overtraining-resistant stochastic modeling method for pattern recognition
journal, December 1996


Big Data of Materials Science: Critical Role of the Descriptor
journal, March 2015


Accelerating materials property predictions using machine learning
journal, September 2013

  • Pilania, Ghanshyam; Wang, Chenchen; Jiang, Xun
  • Scientific Reports, Vol. 3, Issue 1
  • DOI: 10.1038/srep02810

Designing rules and probabilistic weighting for fast materials discovery in the Perovskite structure
journal, May 2014

  • Castelli, I. E.; Jacobsen, K. W.
  • Modelling and Simulation in Materials Science and Engineering, Vol. 22, Issue 5
  • DOI: 10.1088/0965-0393/22/5/055007

On the asymptotics of random forests
journal, April 2016


Neural Networks in Materials Science.
journal, January 1999


Materials Prediction via Classification Learning
journal, August 2015

  • Balachandran, Prasanna V.; Theiler, James; Rondinelli, James M.
  • Scientific Reports, Vol. 5, Issue 1
  • DOI: 10.1038/srep13285

Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
journal, June 2010

  • Hautier, Geoffroy; Fischer, Christopher C.; Jain, Anubhav
  • Chemistry of Materials, Vol. 22, Issue 12
  • DOI: 10.1021/cm100795d

Random Forests
journal, January 2001


Efficient band-structure calculations of strained quantum wells
journal, April 1991


Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning
journal, April 2016

  • Rouet-Leduc, Bertrand; Barros, Kipton; Lookman, Turab
  • Scientific Reports, Vol. 6, Issue 1
  • DOI: 10.1038/srep24862

Materials informatics
journal, October 2005


Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013

  • Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy
  • APL Materials, Vol. 1, Issue 1
  • DOI: 10.1063/1.4812323

The random subspace method for constructing decision forests
journal, January 1998

  • Tin Kam Ho,
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, Issue 8
  • DOI: 10.1109/34.709601