Defect Genome of Cubic Perovskites for Fuel Cell Applications

Balachandran, Janakiraman; Lin, Lianshan; Anchell, Jonathan S.; Bridges, Craig A.; Ganesh, P.

doi:10.1021/acs.jpcc.7b08716

Title: Defect Genome of Cubic Perovskites for Fuel Cell Applications

Journal Article · Tue Oct 10 00:00:00 EDT 2017 · Journal of Physical Chemistry. C

DOI:https://doi.org/10.1021/acs.jpcc.7b08716· OSTI ID:1424465

^[1]; Lin, Lianshan ^[2]; Anchell, Jonathan S. ^[1];

^[3]; Ganesh, P. ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Materials Science and Technology Division
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Chemical Sciences Division

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defects (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Organization:: USDOE Office of Science (SC); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1424465

Journal Information:: Journal of Physical Chemistry. C, Vol. 121, Issue 48; ISSN 1932-7447

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 18 works

Citation information provided by
Web of Science

References (60)

The high-throughput highway to computational materials design Curtarolo, Stefano; Hart, Gus L. W.; Nardelli, Marco Buongiorno Nature Materials, Vol. 12, Issue 3 https://doi.org/10.1038/nmat3568	journal	February 2013
Opportunities and challenges for first-principles materials design and applications to Li battery materials Ceder, Gerbrand MRS Bulletin, Vol. 35, Issue 9 https://doi.org/10.1557/mrs2010.681	journal	September 2010
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy APL Materials, Vol. 1, Issue 1 https://doi.org/10.1063/1.4812323	journal	July 2013
The AFLOW standard for high-throughput materials science calculations Calderon, Camilo E.; Plata, Jose J.; Toher, Cormac Computational Materials Science, Vol. 108 https://doi.org/10.1016/j.commatsci.2015.07.019	journal	October 2015
Genomic materials design: The ferrous frontier Olson, G. B. Acta Materialia, Vol. 61, Issue 3 https://doi.org/10.1016/j.actamat.2012.10.045	journal	February 2013
Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD) Saal, James E.; Kirklin, Scott; Aykol, Muratahan JOM, Vol. 65, Issue 11 https://doi.org/10.1007/s11837-013-0755-4	journal	September 2013
Large scale computational screening and experimental discovery of novel materials for high temperature CO ₂ capture Dunstan, Matthew T.; Jain, Anubhav; Liu, Wen Energy & Environmental Science, Vol. 9, Issue 4 https://doi.org/10.1039/C5EE03253A	journal	January 2016
A database to enable discovery and design of piezoelectric materials de Jong, Maarten; Chen, Wei; Geerlings, Henry Scientific Data, Vol. 2, Issue 1 https://doi.org/10.1038/sdata.2015.53	journal	September 2015
Spectral descriptors for bulk metallic glasses based on the thermodynamics of competing crystalline phases Perim, Eric; Lee, Dongwoo; Liu, Yanhui Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms12315	journal	August 2016
Identification of Potential Photovoltaic Absorbers Based on First-Principles Spectroscopic Screening of Materials Yu, Liping; Zunger, Alex Physical Review Letters, Vol. 108, Issue 6 https://doi.org/10.1103/PhysRevLett.108.068701	journal	February 2012
Point Defects in Oxides: Tailoring Materials Through Defect Engineering Tuller, Harry L.; Bishop, Sean R. Annual Review of Materials Research, Vol. 41, Issue 1 https://doi.org/10.1146/annurev-matsci-062910-100442	journal	August 2011
First-principles calculations for point defects in solids Freysoldt, Christoph; Grabowski, Blazej; Hickel, Tilmann Reviews of Modern Physics, Vol. 86, Issue 1 https://doi.org/10.1103/RevModPhys.86.253	journal	March 2014
Rational design of all organic polymer dielectrics Sharma, Vinit; Wang, Chenchen; Lorenzini, Robert G. Nature Communications, Vol. 5, Issue 1 https://doi.org/10.1038/ncomms5845	journal	September 2014
A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds de Jong, Maarten; Chen, Wei; Notestine, Randy Scientific Reports, Vol. 6, Issue 1 https://doi.org/10.1038/srep34256	journal	October 2016
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert Physical Review Letters, Vol. 108, Issue 5 https://doi.org/10.1103/PhysRevLett.108.058301	journal	January 2012
Interplay between intrinsic defects, doping, and free carrier concentration in SrTiO $_{3}$ thin films Ertekin, Elif; Srinivasan, Varadharajan; Ravichandran, Jayakanth Physical Review B, Vol. 85, Issue 19 https://doi.org/10.1103/PhysRevB.85.195460	journal	May 2012
Electrostatics-based finite-size corrections for first-principles point defect calculations Kumagai, Yu; Oba, Fumiyasu Physical Review B, Vol. 89, Issue 19 https://doi.org/10.1103/PhysRevB.89.195205	journal	May 2014
High-Throughput Computational Screening of Perovskites for Thermochemical Water Splitting Applications Emery, Antoine A.; Saal, James E.; Kirklin, Scott Chemistry of Materials, Vol. 28, Issue 16 https://doi.org/10.1021/acs.chemmater.6b01182	journal	July 2016
Effect of acceptor dopants on the proton mobility in $Ba Zr O_{3}$ : A density functional investigation Björketun, Mårten E.; Sundell, Per G.; Wahnström, Göran Physical Review B, Vol. 76, Issue 5 https://doi.org/10.1103/PhysRevB.76.054307	journal	August 2007
FireWorks: a dynamic workflow system designed for high-throughput applications: FireWorks: A Dynamic Workflow System Designed for High-Throughput Applications Jain, Anubhav; Ong, Shyue Ping; Chen, Wei Concurrency and Computation: Practice and Experience, Vol. 27, Issue 17 https://doi.org/10.1002/cpe.3505	journal	May 2015
Lowering the Temperature of Solid Oxide Fuel Cells Wachsman, E. D.; Lee, K. T. Science, Vol. 334, Issue 6058 https://doi.org/10.1126/science.1204090	journal	November 2011
Oxide-Ion Electrolytes Goodenough, John B. Annual Review of Materials Research, Vol. 33, Issue 1 https://doi.org/10.1146/annurev.matsci.33.022802.091651	journal	August 2003
Proton-Conducting Oxides Kreuer, K. D. Annual Review of Materials Research, Vol. 33, Issue 1, p. 333-359 https://doi.org/10.1146/annurev.matsci.33.022802.091825	journal	August 2003
Towards the Next Generation of Solid Oxide Fuel Cells Operating Below 600 °C with Chemically Stable Proton-Conducting Electrolytes Fabbri, Emiliana; Bi, Lei; Pergolesi, Daniele Advanced Materials, Vol. 24, Issue 2 https://doi.org/10.1002/adma.201103102	journal	September 2011
Oxide-ion and proton conducting electrolyte materials for clean energy applications: structural and mechanistic features Malavasi, Lorenzo; Fisher, Craig A. J.; Islam, M. Saiful Chemical Society Reviews, Vol. 39, Issue 11 https://doi.org/10.1039/b915141a	journal	January 2010
Proton trapping in yttrium-doped barium zirconate Yamazaki, Yoshihiro; Blanc, Frédéric; Okuyama, Yuji Nature Materials, Vol. 12, Issue 7 https://doi.org/10.1038/nmat3638	journal	May 2013
High temperature fuel and steam electrolysis cells using proton conductive solid electrolytes Iwahara, H.; Uchida, H.; Maeda, N. Journal of Power Sources, Vol. 7, Issue 3 https://doi.org/10.1016/0378-7753(82)80018-9	journal	January 1982
Proton and native-ion conductivities in Y2O3 at high temperatures Norby, T.; Kofstad, P. Solid State Ionics, Vol. 20, Issue 3 https://doi.org/10.1016/0167-2738(86)90211-0	journal	May 1986
Proton conducting alkaline earth zirconates and titanates for high drain electrochemical applications Kreuer, K. D.; Adams, St.; Münch, W. Solid State Ionics, Vol. 145, Issue 1-4 https://doi.org/10.1016/S0167-2738(01)00953-5	journal	December 2001
Readily processed protonic ceramic fuel cells with high performance at low temperatures Duan, C.; Tong, J.; Shang, M. Science, Vol. 349, Issue 6254 https://doi.org/10.1126/science.aab3987	journal	July 2015
Structure and thermodynamic stability of hydrogen interstitials in BaZrO ₃ perovskite oxide from density functional calculations Björketun, Mårten E.; Sundell, Per G.; Wahnström, Göran Faraday Discuss., Vol. 134 https://doi.org/10.1039/B602081J	journal	January 2007
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set Kresse, G.; Furthmüller, J. Physical Review B, Vol. 54, Issue 16, p. 11169-11186 https://doi.org/10.1103/PhysRevB.54.11169	journal	October 1996
Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set Kresse, G.; Furthmüller, J. Computational Materials Science, Vol. 6, Issue 1, p. 15-50 https://doi.org/10.1016/0927-0256(96)00008-0	journal	July 1996
Generalized Gradient Approximation Made Simple Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868 https://doi.org/10.1103/PhysRevLett.77.3865	journal	October 1996
Projector augmented-wave method Blöchl, P. E. Physical Review B, Vol. 50, Issue 24, p. 17953-17979 https://doi.org/10.1103/PhysRevB.50.17953	journal	December 1994
Thermodynamics of doping and vacancy formation in ${BaZrO}_{3}$ perovskite oxide from density functional calculations Sundell, Per G.; Björketun, Mårten E.; Wahnström, Göran Physical Review B, Vol. 73, Issue 10 https://doi.org/10.1103/PhysRevB.73.104112	journal	March 2006
Fully Ab Initio Finite-Size Corrections for Charged-Defect Supercell Calculations Freysoldt, Christoph; Neugebauer, Jörg; Van de Walle, Chris G. Physical Review Letters, Vol. 102, Issue 1 https://doi.org/10.1103/PhysRevLett.102.016402	journal	January 2009
A computational framework for automation of point defect calculations Goyal, Anuj; Gorai, Prashun; Peng, Haowei Computational Materials Science, Vol. 130 https://doi.org/10.1016/j.commatsci.2016.12.040	journal	April 2017
Assessment of correction methods for the band-gap problem and for finite-size effects in supercell defect calculations: Case studies for ZnO and GaAs Lany, Stephan; Zunger, Alex Physical Review B, Vol. 78, Issue 23, Article No. 235104 https://doi.org/10.1103/PhysRevB.78.235104	journal	December 2008
The energy and elastic dipole tensor of defects in ionic crystals calculated by the supercell method Leslie, M.; Gillan, N. J. Journal of Physics C: Solid State Physics, Vol. 18, Issue 5 https://doi.org/10.1088/0022-3719/18/5/005	journal	February 1985
Hybrid functionals based on a screened Coulomb potential Heyd, Jochen; Scuseria, Gustavo E.; Ernzerhof, Matthias The Journal of Chemical Physics, Vol. 118, Issue 18 https://doi.org/10.1063/1.1564060	journal	May 2003
Screened hybrid density functionals applied to solids Paier, J.; Marsman, M.; Hummer, K. The Journal of Chemical Physics, Vol. 124, Issue 15 https://doi.org/10.1063/1.2187006	journal	April 2006
Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis Ong, Shyue Ping; Richards, William Davidson; Jain, Anubhav Computational Materials Science, Vol. 68 https://doi.org/10.1016/j.commatsci.2012.10.028	journal	February 2013
Orthorhombic perovskite CaTiO3 and CdTiO3: structure and space group Sasaki, S.; Prewitt, C. T.; Bass, J. D. Acta Crystallographica Section C Crystal Structure Communications, Vol. 43, Issue 9 https://doi.org/10.1107/S0108270187090620	journal	September 1987
Hydration Thermodynamics of the Proton Conducting Oxygen-Deficient Perovskite Series BaTi _{1– x} M _x O _{3– x /2} with M = In or Sc Bjørheim, Tor Svendsen; Rahman, Seikh M. H.; Eriksson, Sten G. Inorganic Chemistry, Vol. 54, Issue 6 https://doi.org/10.1021/ic503006u	journal	February 2015
Proton conductivity of hexagonal and cubic BaTi _1−x Sc _x O _3−δ (0.1 ≤ x ≤ 0.8) Rahman, Seikh M. H.; Norberg, Stefan T.; Knee, Christopher S. Dalton Trans., Vol. 43, Issue 40 https://doi.org/10.1039/C4DT01280A	journal	January 2014
A New Perovskite Polytype in the High-Pressure Sequence of BaIrO ₃ Cheng, Jin-Guang; Alonso, José Antonio; Suard, Emmanuelle Journal of the American Chemical Society, Vol. 131, Issue 21 https://doi.org/10.1021/ja901829e	journal	May 2009
“Stretching” the energy landscape of oxides—Effects on electrocatalysis and diffusion Yildiz, Bilge MRS Bulletin, Vol. 39, Issue 2 https://doi.org/10.1557/mrs.2014.8	journal	February 2014
The classification of tilted octahedra in perovskites Glazer, A. M. Acta Crystallographica Section B Structural Crystallography and Crystal Chemistry, Vol. 28, Issue 11 https://doi.org/10.1107/S0567740872007976	journal	November 1972
Simple ways of determining perovskite structures Glazer, A. M. Acta Crystallographica Section A, Vol. 31, Issue 6 https://doi.org/10.1107/S0567739475001635	journal	November 1975
Formability of ABO3 perovskites Li, Chonghe; Soh, Kitty Chi Kwan; Wu, Ping Journal of Alloys and Compounds, Vol. 372, Issue 1-2 https://doi.org/10.1016/j.jallcom.2003.10.017	journal	June 2004
Efficient Band Gap Prediction for Solids Chan, M. K. Y.; Ceder, G. Physical Review Letters, Vol. 105, Issue 19 https://doi.org/10.1103/PhysRevLett.105.196403	journal	November 2010
Improved predictions of the physical properties of Zn- and Cd-based wide band-gap semiconductors: A validation of the ACBN0 functional Gopal, Priya; Fornari, Marco; Curtarolo, Stefano Physical Review B, Vol. 91, Issue 24 https://doi.org/10.1103/PhysRevB.91.245202	journal	June 2015
First principles assessment of perovskite dopants for proton conductors with chemical stability and high conductivity Kang, Sung Gu; Sholl, David S. RSC Advances, Vol. 3, Issue 10 https://doi.org/10.1039/c2ra23405j	journal	January 2013
Defect chemistry and proton-dopant association in BaZrO3 and BaPrO3 Stokes, Stephen J.; Islam, M. Saiful Journal of Materials Chemistry, Vol. 20, Issue 30 https://doi.org/10.1039/c0jm00328j	journal	January 2010
Concentration and transport of protons in oxides Norby, Truls; Larring, Yngve Current Opinion in Solid State and Materials Science, Vol. 2, Issue 5 https://doi.org/10.1016/S1359-0286(97)80051-4	journal	October 1997
Characterizing chemical stability and proton conductivity of B-site doped barium hafnate (BaHfO3) and barium stannate (BaSnO3) with first principles modeling Kang, Sung Gu; Sholl, David S. Journal of Alloys and Compounds, Vol. 693 https://doi.org/10.1016/j.jallcom.2016.09.221	journal	February 2017
Proton conductivity in perovskite type yttrium doped barium hafnate Snijkers, Frans M. M.; Buekenhoudt, Anita; Luyten, Jan J. Scripta Materialia, Vol. 51, Issue 12 https://doi.org/10.1016/j.scriptamat.2004.08.021	journal	December 2004
Syntheses, Structures, and Characterization of 5-Layer BaVO3-x (x = 0.2, 0.1, 0.0) Liu, Guo; Greedan, J. E. Journal of Solid State Chemistry, Vol. 110, Issue 2 https://doi.org/10.1006/jssc.1994.1170	journal	June 1994
High-pressure synthesis of BaVO3: A new cubic perovskite Nishimura, Kousuke; Yamada, Ikuya; Oka, Kengo Journal of Physics and Chemistry of Solids, Vol. 75, Issue 6 https://doi.org/10.1016/j.jpcs.2014.02.001	journal	June 2014

Cited By (1)

Superior electrocatalytic hydrogen evolution at engineered non-stoichiometric two-dimensional transition metal dichalcogenide edges Hu, Guoxiang; Fung, Victor; Sang, Xiahan Journal of Materials Chemistry A, Vol. 7, Issue 31 https://doi.org/10.1039/c9ta05546k	journal	January 2019

Similar Records

Intermittent Defect Fluctuations in Oxide Heterostructures

Journal Article · Fri Sep 08 00:00:00 EDT 2023 · Advanced Materials · OSTI ID:1424465

Zhang, Qingteng; Wan, Gang; Starchenko, Vitalii; +12 more

Theory-Guided Exploration of the Sr ₂ Nb ₂ O ₇ System for Increased Dielectric and Piezoelectric Properties and Synthesis of Vanadium-Alloyed Sr ₂ Nb ₂ O ₇

Journal Article · Thu Sep 22 00:00:00 EDT 2022 · Chemistry of Materials · OSTI ID:1424465

Ling, Handong; Megha Acharya, ; Martin, Lane W.; +1 more

Energy Frontier Research Center Center for Materials Science of Nuclear Fuels

Technical Report · Tue Apr 01 00:00:00 EDT 2014 · OSTI ID:1424465

Allen, Todd

Related Subjects

36 MATERIALS SCIENCE
30 DIRECT ENERGY CONVERSION
high-throughput
materials genome
defect genome
perovskites
point defects
fuel cells
proton conductors
oxides

Title: Defect Genome of Cubic Perovskites for Fuel Cell Applications

Citation Formats

References (60)

Cited By (1)

Similar Records

Related Subjects