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...
Autores principales: | , , , , , , , , , |
---|---|
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 |