Cargando…

Computational Insights into Materials and Interfaces for Capacitive Energy Storage

Supercapacitors such as electric double‐layer capacitors (EDLCs) and pseudocapacitors are becoming increasingly important in the field of electrical energy storage. Theoretical study of energy storage in EDLCs focuses on solving for the electric double‐layer structure in different electrode geometri...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhan, Cheng, Lian, Cheng, Zhang, Yu, Thompson, Matthew W., Xie, Yu, Wu, Jianzhong, Kent, Paul R. C., Cummings, Peter T., Jiang, De‐en, Wesolowski, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5515120/
https://www.ncbi.nlm.nih.gov/pubmed/28725531
http://dx.doi.org/10.1002/advs.201700059
_version_ 1783250952379170816
author Zhan, Cheng
Lian, Cheng
Zhang, Yu
Thompson, Matthew W.
Xie, Yu
Wu, Jianzhong
Kent, Paul R. C.
Cummings, Peter T.
Jiang, De‐en
Wesolowski, David J.
author_facet Zhan, Cheng
Lian, Cheng
Zhang, Yu
Thompson, Matthew W.
Xie, Yu
Wu, Jianzhong
Kent, Paul R. C.
Cummings, Peter T.
Jiang, De‐en
Wesolowski, David J.
author_sort Zhan, Cheng
collection PubMed
description Supercapacitors such as electric double‐layer capacitors (EDLCs) and pseudocapacitors are becoming increasingly important in the field of electrical energy storage. Theoretical study of energy storage in EDLCs focuses on solving for the electric double‐layer structure in different electrode geometries and electrolyte components, which can be achieved by molecular simulations such as classical molecular dynamics (MD), classical density functional theory (classical DFT), and Monte‐Carlo (MC) methods. In recent years, combining first‐principles and classical simulations to investigate the carbon‐based EDLCs has shed light on the importance of quantum capacitance in graphene‐like 2D systems. More recently, the development of joint density functional theory (JDFT) enables self‐consistent electronic‐structure calculation for an electrode being solvated by an electrolyte. In contrast with the large amount of theoretical and computational effort on EDLCs, theoretical understanding of pseudocapacitance is very limited. In this review, we first introduce popular modeling methods and then focus on several important aspects of EDLCs including nanoconfinement, quantum capacitance, dielectric screening, and novel 2D electrode design; we also briefly touch upon pseudocapactive mechanism in RuO(2). We summarize and conclude with an outlook for the future of materials simulation and design for capacitive energy storage.
format Online
Article
Text
id pubmed-5515120
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-55151202017-07-19 Computational Insights into Materials and Interfaces for Capacitive Energy Storage Zhan, Cheng Lian, Cheng Zhang, Yu Thompson, Matthew W. Xie, Yu Wu, Jianzhong Kent, Paul R. C. Cummings, Peter T. Jiang, De‐en Wesolowski, David J. Adv Sci (Weinh) Reviews Supercapacitors such as electric double‐layer capacitors (EDLCs) and pseudocapacitors are becoming increasingly important in the field of electrical energy storage. Theoretical study of energy storage in EDLCs focuses on solving for the electric double‐layer structure in different electrode geometries and electrolyte components, which can be achieved by molecular simulations such as classical molecular dynamics (MD), classical density functional theory (classical DFT), and Monte‐Carlo (MC) methods. In recent years, combining first‐principles and classical simulations to investigate the carbon‐based EDLCs has shed light on the importance of quantum capacitance in graphene‐like 2D systems. More recently, the development of joint density functional theory (JDFT) enables self‐consistent electronic‐structure calculation for an electrode being solvated by an electrolyte. In contrast with the large amount of theoretical and computational effort on EDLCs, theoretical understanding of pseudocapacitance is very limited. In this review, we first introduce popular modeling methods and then focus on several important aspects of EDLCs including nanoconfinement, quantum capacitance, dielectric screening, and novel 2D electrode design; we also briefly touch upon pseudocapactive mechanism in RuO(2). We summarize and conclude with an outlook for the future of materials simulation and design for capacitive energy storage. John Wiley and Sons Inc. 2017-04-24 /pmc/articles/PMC5515120/ /pubmed/28725531 http://dx.doi.org/10.1002/advs.201700059 Text en © 2017 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Zhan, Cheng
Lian, Cheng
Zhang, Yu
Thompson, Matthew W.
Xie, Yu
Wu, Jianzhong
Kent, Paul R. C.
Cummings, Peter T.
Jiang, De‐en
Wesolowski, David J.
Computational Insights into Materials and Interfaces for Capacitive Energy Storage
title Computational Insights into Materials and Interfaces for Capacitive Energy Storage
title_full Computational Insights into Materials and Interfaces for Capacitive Energy Storage
title_fullStr Computational Insights into Materials and Interfaces for Capacitive Energy Storage
title_full_unstemmed Computational Insights into Materials and Interfaces for Capacitive Energy Storage
title_short Computational Insights into Materials and Interfaces for Capacitive Energy Storage
title_sort computational insights into materials and interfaces for capacitive energy storage
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5515120/
https://www.ncbi.nlm.nih.gov/pubmed/28725531
http://dx.doi.org/10.1002/advs.201700059
work_keys_str_mv AT zhancheng computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT liancheng computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT zhangyu computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT thompsonmattheww computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT xieyu computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT wujianzhong computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT kentpaulrc computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT cummingspetert computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT jiangdeen computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage
AT wesolowskidavidj computationalinsightsintomaterialsandinterfacesforcapacitiveenergystorage