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Title: Computational Studies of Electrode Materials in Sodium-Ion Batteries

Abstract

Sodium‐ion batteries have gained extensive interest as a promising solution for large‐scale electrochemical energy storage, owing to their low cost, materials abundance, good reversibility, and decent energy density. For sodium‐ion batteries to achieve comparable performance to current lithium‐ion batteries, significant improvements are still required in cathode, anode, and electrolyte materials. Understanding the functioning and degradation mechanisms of the materials is essential. Computational techniques have been widely applied in tandem with experimental investigations to provide crucial fundamental insights into electrode materials and to facilitate the development of materials for sodium‐ion batteries. In this research, the authors review computational studies on electrode materials in sodium‐ion batteries. The authors summarize the current state‐of‐the‐art computational techniques and their applications in investigating the structure, ordering, diffusion, and phase transformation in cathode and anode materials for sodium‐ion batteries. The unique capability and the obtained knowledge of computational studies as well as the perspectives for sodium‐ion battery materials are discussed in this review.

Authors:
 [1];  [2];  [2]; ORCiD logo [1]
  1. Univ. of Maryland, College Park, MD (United States)
  2. Georgia Inst. of Technology, Atlanta, GA (United States)
Publication Date:
Research Org.:
Univ. of Maryland, College Park, MD (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V); National Science Foundation (NSF); China Scholarship CounciL; US Department of the Navy, Office of Naval Research (ONR)
OSTI Identifier:
1608912
Alternate Identifier(s):
OSTI ID: 1425510
Grant/Contract Number:  
EE0007807; DMR‐1410936; CBET‐1706723
Resource Type:
Accepted Manuscript
Journal Name:
Advanced Energy Materials
Additional Journal Information:
Journal Volume: 8; Journal Issue: 17; Journal ID: ISSN 1614-6832
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; anodes; cathodes; first principles calculations; sodium ion batteries; sodium‐ion intercalation

Citation Formats

Bai, Qiang, Yang, Lufeng, Chen, Hailong, and Mo, Yifei. Computational Studies of Electrode Materials in Sodium-Ion Batteries. United States: N. p., 2018. Web. doi:10.1002/aenm.201702998.
Bai, Qiang, Yang, Lufeng, Chen, Hailong, & Mo, Yifei. Computational Studies of Electrode Materials in Sodium-Ion Batteries. United States. doi:10.1002/aenm.201702998.
Bai, Qiang, Yang, Lufeng, Chen, Hailong, and Mo, Yifei. Fri . "Computational Studies of Electrode Materials in Sodium-Ion Batteries". United States. doi:10.1002/aenm.201702998. https://www.osti.gov/servlets/purl/1608912.
@article{osti_1608912,
title = {Computational Studies of Electrode Materials in Sodium-Ion Batteries},
author = {Bai, Qiang and Yang, Lufeng and Chen, Hailong and Mo, Yifei},
abstractNote = {Sodium‐ion batteries have gained extensive interest as a promising solution for large‐scale electrochemical energy storage, owing to their low cost, materials abundance, good reversibility, and decent energy density. For sodium‐ion batteries to achieve comparable performance to current lithium‐ion batteries, significant improvements are still required in cathode, anode, and electrolyte materials. Understanding the functioning and degradation mechanisms of the materials is essential. Computational techniques have been widely applied in tandem with experimental investigations to provide crucial fundamental insights into electrode materials and to facilitate the development of materials for sodium‐ion batteries. In this research, the authors review computational studies on electrode materials in sodium‐ion batteries. The authors summarize the current state‐of‐the‐art computational techniques and their applications in investigating the structure, ordering, diffusion, and phase transformation in cathode and anode materials for sodium‐ion batteries. The unique capability and the obtained knowledge of computational studies as well as the perspectives for sodium‐ion battery materials are discussed in this review.},
doi = {10.1002/aenm.201702998},
journal = {Advanced Energy Materials},
number = 17,
volume = 8,
place = {United States},
year = {2018},
month = {6}
}

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Cited by: 11 works
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Advances and Challenges in Metal Sulfides/Selenides for Next-Generation Rechargeable Sodium-Ion Batteries
journal, June 2017


The Application of Metal Sulfides in Sodium Ion Batteries
journal, November 2016

  • Xiao, Ying; Lee, Seon Hwa; Sun, Yang-Kook
  • Advanced Energy Materials, Vol. 7, Issue 3
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Enhancing Sodium Ion Battery Performance by Strongly Binding Nanostructured Sb 2 S 3 on Sulfur-Doped Graphene Sheets
journal, November 2016


Unveiling the Unique Phase Transformation Behavior and Sodiation Kinetics of 1D van der Waals Sb 2 S 3 Anodes for Sodium Ion Batteries
journal, December 2016

  • Yao, Shanshan; Cui, Jiang; Lu, Ziheng
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Sodiation Kinetics of Metal Oxide Conversion Electrodes: A Comparative Study with Lithiation
journal, August 2015


Na 2 Ti 3 O 7 : Lowest Voltage Ever Reported Oxide Insertion Electrode for Sodium Ion Batteries
journal, September 2011

  • Senguttuvan, Premkumar; Rousse, Gwenaëlle; Seznec, Vincent
  • Chemistry of Materials, Vol. 23, Issue 18
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Na2Ti6O13: a potential anode for grid-storage sodium-ion batteries
journal, January 2013

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Na2Ti3O7: an intercalation based anode for sodium-ion battery applications
journal, January 2013

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Microspherical Na2Ti3O7 prepared by spray-drying method as anode material for sodium-ion battery
journal, September 2014


Composition and Evolution of the Solid-Electrolyte Interphase in Na 2 Ti 3 O 7 Electrodes for Na-Ion Batteries: XPS and Auger Parameter Analysis
journal, April 2015

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Direct atomic-scale confirmation of three-phase storage mechanism in Li4Ti5O12 anodes for room-temperature sodium-ion batteries
journal, May 2013

  • Sun, Yang; Zhao, Liang; Pan, Huilin
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Understanding Na 2 Ti 3 O 7 as an ultra-low voltage anode material for a Na-ion battery
journal, January 2014

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  • Chem. Commun., Vol. 50, Issue 83
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Anomalously high Na + and low Li + mobility in intercalated Na 2 Ti 6 O 13
journal, January 2017

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Rationalization of Intercalation Potential and Redox Mechanism for A 2 Ti 3 O 7 (A = Li, Na)
journal, December 2013

  • Rousse, Gwenaelle; Arroyo-de Dompablo, M. Elena; Senguttuvan, Premkumar
  • Chemistry of Materials, Vol. 25, Issue 24
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Sodium Storage and Transport Properties in Layered Na 2 Ti 3 O 7 for Room-Temperature Sodium-Ion Batteries
journal, May 2013


Na 2+ x Ti 6 O 13 as Potential Negative Electrode Material for Na-Ion Batteries
journal, July 2014

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  • Inorganic Chemistry, Vol. 53, Issue 16
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Spinel Li[sub 4]Ti[sub 5]O[sub 12] Nanowires for High-Rate Li-Ion Intercalation Electrode
journal, January 2007

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Boron-doped graphene as a promising anode for Na-ion batteries
journal, January 2014

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Ab initio characterization of layered MoS2 as anode for sodium-ion batteries
journal, December 2014


Exploring the possibilities of two-dimensional transition metal carbides as anode materials for sodium batteries
journal, January 2015

  • Yang, Eunjeong; Ji, Hyunjun; Kim, Jaehoon
  • Physical Chemistry Chemical Physics, Vol. 17, Issue 7
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A promising anode material for sodium-ion battery with high capacity and high diffusion ability: graphyne and graphdiyne
journal, January 2016

  • Xu, Zhenming; Lv, Xiaojun; Li, Jie
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MoS 2 /Graphene Composite Anodes with Enhanced Performance for Sodium-Ion Batteries: The Role of the Two-Dimensional Heterointerface
journal, January 2015

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  • Advanced Functional Materials, Vol. 25, Issue 9
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Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013

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  • APL Materials, Vol. 1, Issue 1
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Study of Li atom diffusion in amorphous Li3PO4 with neural network potential
journal, December 2017

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  • The Journal of Chemical Physics, Vol. 147, Issue 21
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Accurate force field for molybdenum by machine learning large materials data
journal, September 2017


Perspective: Machine learning potentials for atomistic simulations
journal, November 2016

  • Behler, Jörg
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