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Title: Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores

Abstract

Structure-property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A2B2O7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material. No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. This work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.

Authors:
; ORCiD logo; ; ; ; ; ORCiD logo
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC). Basic Energy Sciences (BES) (SC-22); USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1348946
Alternate Identifier(s):
OSTI ID: 1361477; OSTI ID: 1508075
Report Number(s):
LA-UR-16-23806
Journal ID: ISSN 0897-4756
Grant/Contract Number:  
AC52-06NA25396; EP/L005581/1; EP/L006170/1
Resource Type:
Published Article
Journal Name:
Chemistry of Materials
Additional Journal Information:
Journal Name: Chemistry of Materials Journal Volume: 29 Journal Issue: 6; Journal ID: ISSN 0897-4756
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEAR CHEMISTRY

Citation Formats

Pilania, Ghanshyam, Whittle, Karl R., Jiang, Chao, Grimes, Robin W., Stanek, Christopher R., Sickafus, Kurt E., and Uberuaga, Blas Pedro. Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores. United States: N. p., 2017. Web. doi:10.1021/acs.chemmater.6b04666.
Pilania, Ghanshyam, Whittle, Karl R., Jiang, Chao, Grimes, Robin W., Stanek, Christopher R., Sickafus, Kurt E., & Uberuaga, Blas Pedro. Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores. United States. https://doi.org/10.1021/acs.chemmater.6b04666
Pilania, Ghanshyam, Whittle, Karl R., Jiang, Chao, Grimes, Robin W., Stanek, Christopher R., Sickafus, Kurt E., and Uberuaga, Blas Pedro. Fri . "Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores". United States. https://doi.org/10.1021/acs.chemmater.6b04666.
@article{osti_1348946,
title = {Using Machine Learning To Identify Factors That Govern Amorphization of Irradiated Pyrochlores},
author = {Pilania, Ghanshyam and Whittle, Karl R. and Jiang, Chao and Grimes, Robin W. and Stanek, Christopher R. and Sickafus, Kurt E. and Uberuaga, Blas Pedro},
abstractNote = {Structure-property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A2B2O7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material. No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. This work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.},
doi = {10.1021/acs.chemmater.6b04666},
journal = {Chemistry of Materials},
number = 6,
volume = 29,
place = {United States},
year = {Fri Mar 03 00:00:00 EST 2017},
month = {Fri Mar 03 00:00:00 EST 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1021/acs.chemmater.6b04666

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Cited by: 28 works
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Works referenced in this record:

From Organized High-Throughput Data to Phenomenological Theory using Machine Learning: The Example of Dielectric Breakdown
journal, February 2016


X-ray diffraction study of the Y2Ti2O7 pyrochlore disordering sequence under irradiation
journal, November 2016


Finding Density Functionals with Machine Learning
journal, June 2012


Ion irradiation-induced phase transformation of pyrochlore and zirconolite
journal, January 1999

  • Wang, S. X.; Wang, L. M.; Ewing, R. C.
  • Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, Vol. 148, Issue 1-4
  • DOI: 10.1016/S0168-583X(98)00847-7

An introduction to kernel-based learning algorithms
journal, March 2001

  • Muller, K. -R.; Mika, S.; Ratsch, G.
  • IEEE Transactions on Neural Networks, Vol. 12, Issue 2
  • DOI: 10.1109/72.914517

Accelerated materials property predictions and design using motif-based fingerprints
journal, July 2015

  • Huan, Tran Doan; Mannodi-Kanakkithodi, Arun; Ramprasad, Rampi
  • Physical Review B, Vol. 92, Issue 1
  • DOI: 10.1103/PhysRevB.92.014106

Ion Beam-Induced Amorphization of the Pyrochlore Structure-Type: A Review
journal, January 2003


Heavy-ion irradiation effects on structures and acid dissolution of pyrochlores
journal, February 2001


Ion-beam irradiation of Gd 2 Sn 2 O 7 and Gd 2 Hf 2 O 7 pyrochlore: Bond-type effect
journal, May 2004

  • Lian, Jie; Ewing, Rodney C.; Wang, L. M.
  • Journal of Materials Research, Vol. 19, Issue 5
  • DOI: 10.1557/JMR.2004.0178

Cation disorder in Mg X 2 O 4 ( X = Al, Ga, In) spinels from first principles
journal, July 2012


From ultrasoft pseudopotentials to the projector augmented-wave method
journal, January 1999


Criteria for bombardment-induced structural changes in non-metallic solids
journal, January 1975


Structural stability of Nd2Zr2O7 pyrochlore ion-irradiated in a broad energy range
journal, October 2013


Further considerations on the thermodynamics of chemical equilibria and reaction rates
journal, January 1936


Role of Antisite Disorder on Preamorphization Swelling in Titanate Pyrochlores
journal, May 2012


Opposite correlations between cation disordering and amorphization resistance in spinels versus pyrochlores
journal, October 2015

  • Uberuaga, Blas Pedro; Tang, Ming; Jiang, Chao
  • Nature Communications, Vol. 6, Issue 1
  • DOI: 10.1038/ncomms9750

Adaptive machine learning framework to accelerate ab initio molecular dynamics
journal, December 2014

  • Botu, Venkatesh; Ramprasad, Rampi
  • International Journal of Quantum Chemistry, Vol. 115, Issue 16
  • DOI: 10.1002/qua.24836

Radiation-induced amorphization of rare-earth titanate pyrochlores
journal, October 2003


Radiation Tolerance of Complex Oxides
journal, August 2000


Machine Learning Assisted Predictions of Intrinsic Dielectric Breakdown Strength of ABX 3 Perovskites
journal, June 2016

  • Kim, Chiho; Pilania, Ghanshyam; Ramprasad, Rampi
  • The Journal of Physical Chemistry C, Vol. 120, Issue 27
  • DOI: 10.1021/acs.jpcc.6b05068

Amorphization and recrystallization of the ABO3 oxides
journal, February 2002


Introduction to mathematical models for irradiation-induced phase transformations
book, January 2007


The theory of reactions involving proton transfers
journal, April 1936

  • Bell, Ronald Percy
  • Proceedings of the Royal Society of London. Series A - Mathematical and Physical Sciences, Vol. 154, Issue 882, p. 414-429
  • DOI: 10.1098/rspa.1936.0060

Structural modifications in pyrochlores caused by ions in the electronic stopping regime
journal, October 2008


Ion irradiation of novel yttrium/ytterbium-based pyrochlores: The effect of disorder
journal, December 2011


First-principles prediction of disordering tendencies in pyrochlore oxides
journal, March 2009


Probing disorder in isometric pyrochlore and related complex oxides
journal, February 2016

  • Shamblin, Jacob; Feygenson, Mikhail; Neuefeind, Joerg
  • Nature Materials, Vol. 15, Issue 5
  • DOI: 10.1038/nmat4581

Correlation of Formation Enthalpies with Critical Amorphization Temperature for Pyrochlore and Monazite
journal, January 2004


Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
journal, January 2012


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

The order–disorder transition in ion-irradiated pyrochlore
journal, March 2003


Role of composition, bond covalency, and short-range order in the disordering of stannate pyrochlores by swift heavy ion irradiation
journal, August 2016


Disorder in Pyrochlore Oxides
journal, August 2000


Accelerated search for materials with targeted properties by adaptive design
journal, April 2016

  • Xue, Dezhen; Balachandran, Prasanna V.; Hogden, John
  • Nature Communications, Vol. 7, Issue 1
  • DOI: 10.1038/ncomms11241

Ion Irradiation of Ternary Pyrochlore Oxides
journal, July 2009

  • Lumpkin, Gregory R.; Smith, Katherine L.; Blackford, Mark G.
  • Chemistry of Materials, Vol. 21, Issue 13
  • DOI: 10.1021/cm9003917

Machine learning bandgaps of double perovskites
journal, January 2016

  • Pilania, G.; Mannodi-Kanakkithodi, A.; Uberuaga, B. P.
  • Scientific Reports, Vol. 6, Issue 1
  • DOI: 10.1038/srep19375

Nature of the chemical bond and prediction of radiation tolerance in pyrochlore and defect fluorite compounds
journal, April 2007

  • Lumpkin, Gregory R.; Pruneda, Miguel; Rios, Susana
  • Journal of Solid State Chemistry, Vol. 180, Issue 4
  • DOI: 10.1016/j.jssc.2007.01.028

Effect of Structure and Thermodynamic Stability on the Response of Lanthanide Stannate Pyrochlores to Ion Beam Irradiation
journal, February 2006

  • Lian, J.; Helean, K. B.; Kennedy, B. J.
  • The Journal of Physical Chemistry B, Vol. 110, Issue 5
  • DOI: 10.1021/jp055266c

Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
journal, October 1996


Defect formation energies in A 2 B 2 O 7 pyrochlores
journal, October 2015


Learning scheme to predict atomic forces and accelerate materials simulations
journal, September 2015


Key Role of the Cation Interstitial Structure in the Radiation Resistance of Pyrochlores
journal, April 2009


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


Radiation-induced amorphization resistance and radiation tolerance in structurally related oxides
journal, February 2007

  • Sickafus, Kurt E.; Grimes, Robin W.; Valdez, James A.
  • Nature Materials, Vol. 6, Issue 3
  • DOI: 10.1038/nmat1842

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics
journal, February 2016

  • Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan
  • Scientific Reports, Vol. 6, Issue 1
  • DOI: 10.1038/srep20952

Formation enthalpies of rare earth titanate pyrochlores
journal, June 2004


Predicted structure and stability of A 4 B 3 O 12 δ -phase compositions
journal, November 2009


Special quasirandom structures
journal, July 1990


Heavy-ion irradiation effects in Gd2(Ti2−xZrx)O7 pyrochlores
journal, February 2001


Kernel methods in machine learning
journal, June 2008

  • Hofmann, Thomas; Schölkopf, Bernhard; Smola, Alexander J.
  • The Annals of Statistics, Vol. 36, Issue 3
  • DOI: 10.1214/009053607000000677

Nuclear waste disposal—pyrochlore (A2B2O7): Nuclear waste form for the immobilization of plutonium and “minor” actinides
journal, June 2004

  • Ewing, Rodney C.; Weber, William J.; Lian, Jie
  • Journal of Applied Physics, Vol. 95, Issue 11
  • DOI: 10.1063/1.1707213

Immobilisation of high level nuclear reactor wastes in SYNROC
journal, March 1979

  • Ringwood, A. E.; Kesson, S. E.; Ware, N. G.
  • Nature, Vol. 278, Issue 5701
  • DOI: 10.1038/278219a0

Molecular dynamics simulation of displacement cascades in Cu and Ni: Thermal spike behavior
journal, June 1989

  • de la Rubia, T. Diaz; Averback, R. S.; Hsieh, Horngming
  • Journal of Materials Research, Vol. 4, Issue 3
  • DOI: 10.1557/JMR.1989.0579

Thermal spike model in the electronic stopping power regime
journal, March 1993

  • Toulemonde, M.; Paumier, E.; Dufour, C.
  • Radiation Effects and Defects in Solids, Vol. 126, Issue 1-4
  • DOI: 10.1080/10420159308219709

Thermal spike recrystallisation: Molecular dynamics simulation of radiation damage in polymorphs of titania
journal, June 2008

  • Marks, N. A.; Thomas, B. S.; Smith, K. L.
  • Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, Vol. 266, Issue 12-13
  • DOI: 10.1016/j.nimb.2008.03.098