Designing All-Solid-State Batteries by Theoretical Computation: A Review

Shu Zhang , Jun Ma , Shanmu Dong , Guanglei Cui

Electrochemical Energy Reviews ›› 2023, Vol. 6 ›› Issue (1)

PDF
Electrochemical Energy Reviews ›› 2023, Vol. 6 ›› Issue (1) DOI: 10.1007/s41918-022-00143-9
Review Article

Designing All-Solid-State Batteries by Theoretical Computation: A Review

Author information +
History +
PDF

Abstract

All-solid-state batteries (ASSBs) with solid-state electrolytes and lithium-metal anodes have been regarded as a promising battery technology to alleviate range anxiety and address safety issues due to their high energy density and high safety. Understanding the fundamental physical and chemical science of ASSBs is of great importance to battery development. To confirm and supplement experimental study, theoretical computation provides a powerful approach to probe the thermodynamic and kinetic behavior of battery materials and their interfaces, resulting in the design of better batteries. In this review, we assess recent progress in the theoretical computations of solid electrolytes and the interfaces between the electrodes and electrolytes of ASSBs. We review the role of theoretical computation in studying the following: ion transport mechanisms, grain boundaries, phase stability, chemical and electrochemical stability, mechanical properties, design strategies and high-throughput screening of inorganic solid electrolytes, mechanical stability, space-charge layers, interface buffer layers and dendrite growth at electrode/electrolyte interfaces. Finally, we provide perspectives on the shortcomings, challenges and opportunities of theoretical computation in regard to ASSBs.

Graphical abstract

Cite this article

Download citation ▾
Shu Zhang, Jun Ma, Shanmu Dong, Guanglei Cui. Designing All-Solid-State Batteries by Theoretical Computation: A Review. Electrochemical Energy Reviews, 2023, 6(1): DOI:10.1007/s41918-022-00143-9

登录浏览全文

4963

注册一个新账户 忘记密码

References

Funding

Key-Area Research and Development Program of Guangdong Province(2020B090919005)

National Natural Science Foundation of China(21975274)

Shandong Provincial Natural Science Foundation(ZR2020KE032)

Youth Innovation Promotion Association of CAS(2021210)

Shandong Energy Institute (SEI)(SEI I202117)

Taishan Scholar Foundation of Shandong Province(ts201511063)

AI Summary AI Mindmap
PDF

273

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/