Literature DB >> 26263275

Intrinsic Material Properties Dictating Oxygen Vacancy Formation Energetics in Metal Oxides.

Ann M Deml1,2, Aaron M Holder3, Ryan P O'Hayre1, Charles B Musgrave3, Vladan Stevanović1,2.   

Abstract

Oxygen vacancies (V(O)) in oxides are extensively used to manipulate vital material properties. Although methods to predict defect formation energies have advanced significantly, an understanding of the intrinsic material properties that govern defect energetics lags. We use first-principles calculations to study the connection between intrinsic (bulk) material properties and the energy to form a single, charge neutral oxygen vacancy (E(V)). We investigate 45 binary and ternary oxides and find that a simple model which combines (i) the oxide enthalpy of formation (ΔH(f)), (ii) the midgap energy relative to the O 2p band center (E(O 2p) + (1/2)E(g)), and (iii) atomic electronegativities reproduces calculated E(V) within ∼0.2 eV. This result provides both valuable insights into the key properties influencing E(V) and a direct method to predict E(V). We then predict the E(V) of ∼1800 oxides and validate the predictive nature of our approach against direct defect calculations for a subset of 18 randomly selected materials.

Entities:  

Keywords:  High-throughput; Materials genome; Point defects; Rapid screening

Year:  2015        PMID: 26263275     DOI: 10.1021/acs.jpclett.5b00710

Source DB:  PubMed          Journal:  J Phys Chem Lett        ISSN: 1948-7185            Impact factor:   6.475


  6 in total

1.  Trends in Surface Oxygen Formation Energy in Perovskite Oxides.

Authors:  Yoyo Hinuma; Shinya Mine; Takashi Toyao; Ken-Ichi Shimizu
Journal:  ACS Omega       Date:  2022-05-24

2.  Universal machine learning framework for defect predictions in zinc blende semiconductors.

Authors:  Arun Mannodi-Kanakkithodi; Xiaofeng Xiang; Laura Jacoby; Robert Biegaj; Scott T Dunham; Daniel R Gamelin; Maria K Y Chan
Journal:  Patterns (N Y)       Date:  2022-02-14

3.  Design and Analysis of Metal Oxides for CO2 Reduction Using Machine Learning, Transfer Learning, and Bayesian Optimization.

Authors:  Ryo Iwama; Koji Takizawa; Kenichi Shinmei; Eisuke Baba; Noritoshi Yagihashi; Hiromasa Kaneko
Journal:  ACS Omega       Date:  2022-03-17

4.  Discovery of zirconium dioxides for the design of better oxygen-ion conductors using efficient algorithms beyond data mining.

Authors:  Joohwi Lee; Nobuko Ohba; Ryoji Asahi
Journal:  RSC Adv       Date:  2018-07-16       Impact factor: 4.036

5.  Search for high-capacity oxygen storage materials by materials informatics.

Authors:  Nobuko Ohba; Takuro Yokoya; Seiji Kajita; Kensuke Takechi
Journal:  RSC Adv       Date:  2019-12-17       Impact factor: 3.361

6.  Design principles of perovskites for solar-driven thermochemical splitting of CO2.

Authors:  Miriam Ezbiri; Michael Takacs; Boris Stolz; Jeffrey Lungthok; Aldo Steinfeld; Ronald Michalsky
Journal:  J Mater Chem A Mater       Date:  2017-07-03
  6 in total

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