Curvature effects on electric-double-layer capacitance

doi:10.1016/j.cjche.2020.10.039

中国化学工程学报 ›› 2021, Vol. 29 ›› Issue (3): 145-152.DOI: 10.1016/j.cjche.2020.10.039

• Special Issue on Frontiers of Chemical Engineering Thermodynamics • 上一篇下一篇

Curvature effects on electric-double-layer capacitance

Jie Yang¹, Alejandro Gallegos², Cheng Lian¹, Shengwei Deng³, Honglai Liu¹, Jianzhong Wu²

1 State Key Laboratory of Chemical Engineering, and School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China;
2 Department of Chemical and Environmental Engineering, University of California, Riverside, CA 92521, USA;
3 College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China

收稿日期:2020-09-14 修回日期:2020-10-10 出版日期:2021-03-28 发布日期:2021-05-13
通讯作者: Cheng Lian, Shengwei Deng, Jianzhong Wu
基金资助:
This work was sponsored by the National Natural Science Foundation of China (Nos. 91834301, 21908053, and 21808055), Shanghai Sailing Program (19YF1411700).

Curvature effects on electric-double-layer capacitance

Jie Yang¹, Alejandro Gallegos², Cheng Lian¹, Shengwei Deng³, Honglai Liu¹, Jianzhong Wu²

1 State Key Laboratory of Chemical Engineering, and School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China;
2 Department of Chemical and Environmental Engineering, University of California, Riverside, CA 92521, USA;
3 College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China

Received:2020-09-14 Revised:2020-10-10 Online:2021-03-28 Published:2021-05-13
Contact: Cheng Lian, Shengwei Deng, Jianzhong Wu
Supported by:
This work was sponsored by the National Natural Science Foundation of China (Nos. 91834301, 21908053, and 21808055), Shanghai Sailing Program (19YF1411700).

摘要/Abstract

摘要： Understanding the microscopic structure and thermodynamic properties of electrode/electrolyte interfaces is central to the rational design of electric-double-layer capacitors (EDLCs). Whereas practical applications often entail electrodes with complicated pore structures, theoretical studies are mostly restricted to EDLCs of simple geometry such as planar or slit pores ignoring the curvature effects of the electrode surface. Significant gaps exist regarding the EDLC performance and the interfacial structure. Herein the classical density functional theory (CDFT) is used to study the capacitance and interfacial behavior of spherical electric double layers within a coarse-grained model. The capacitive performance is associated with electrode curvature, surface potential, and electrolyte concentration and can be correlated with a regression-tree (RT) model. The combination of CDFT with machine-learning methods provides a promising quantitative framework useful for the computational screening of porous electrodes and novel electrolytes.

关键词: Electric double layer, Electrodes/electrolyte interface, Curvature effects, Classical density functional theory, Machine learning

Abstract: Understanding the microscopic structure and thermodynamic properties of electrode/electrolyte interfaces is central to the rational design of electric-double-layer capacitors (EDLCs). Whereas practical applications often entail electrodes with complicated pore structures, theoretical studies are mostly restricted to EDLCs of simple geometry such as planar or slit pores ignoring the curvature effects of the electrode surface. Significant gaps exist regarding the EDLC performance and the interfacial structure. Herein the classical density functional theory (CDFT) is used to study the capacitance and interfacial behavior of spherical electric double layers within a coarse-grained model. The capacitive performance is associated with electrode curvature, surface potential, and electrolyte concentration and can be correlated with a regression-tree (RT) model. The combination of CDFT with machine-learning methods provides a promising quantitative framework useful for the computational screening of porous electrodes and novel electrolytes.

Key words: Electric double layer, Electrodes/electrolyte interface, Curvature effects, Classical density functional theory, Machine learning

Jie Yang, Alejandro Gallegos, Cheng Lian, Shengwei Deng, Honglai Liu, Jianzhong Wu. Curvature effects on electric-double-layer capacitance[J]. 中国化学工程学报, 2021, 29(3): 145-152.

Jie Yang, Alejandro Gallegos, Cheng Lian, Shengwei Deng, Honglai Liu, Jianzhong Wu. Curvature effects on electric-double-layer capacitance[J]. Chinese Journal of Chemical Engineering, 2021, 29(3): 145-152.

参考文献

[1] P. Simon, Y. Gogotsi, Materials for electrochemical capacitors, Nat. Mat. 7 (2008) 845-854.
[2] A. Noori, M.F. El-Kady, M.S. Rahmanifar, R.B. Kaner, M.F. Mousavi, Towards establishing standard performance metrics for batteries, supercapacitors and beyond, Chem. Soc. Rev. 48 (2019) 1272-1341.
[3] P.K. Adusei, S. Gbordzoe, S.N. Kanakaraj, Y.Y. Hsieh, N.T. Alvarez, Y. Fang, K. Johnson, C. McConnell, V. Shanov, Fabrication and study of supercapacitor electrodes based on oxygen plasma functionalized carbon nanotube fibers, J. Energy Chem. 40 (2020) 120-131.
[4] C. Zhong, Y. Deng, W. Hu, J. Qiao, L. Zhang, J. Zhang, A review of electrolyte materials and compositions for electrochemical supercapacitors, Chem. Soc. Rev. 44 (2015) 7484-7539.
[5] D.E. Jiang, J. Wu, Microscopic insights into the electrochemical behavior of nonaqueous electrolytes in electric double-layer capacitors, J. Phys. Chem. Lett. 4 (2013) 1260-1267.
[6] Y. Shao, M.F. El-Kady, L.J. Wang, Q. Zhang, Y. Li, H. Wang, M.F. Mousavi, R.B. Kaner, Graphene-based materials for flexible supercapacitors, Chem. Soc. Rev. 44 (2015) 3639-3665.
[7] M.V. Fedorov, A.A. Kornyshev, Ionic liquids at electrified interfaces, Chem. Rev. 114 (2014) 2978-3036.
[8] E. Frackowiak, Q. Abbas, F. Béguin, Carbon/carbon supercapacitors, J. Energy Chem. 22 (2013) 226-240.
[9] G. Feng, J.S. Zhang, R. Qiao, Microstructure and capacitance of the electrical double layers at the interface of ionic liquids and planar electrodes, J. Phys. Chem. C. 113 (2009) 4549-4559.
[10] C. Largeot, C. Portet, J. Chmiola, P.L. Taberna, Y. Gogotsi, P. Simon, Relation between the ion size and pore size for an electric double-layer capacitor, J. A. Chem. Soc. 130 (2008) 2730-2731.
[11] R. Burt, G. Birkett, X.S. Zhao, A review of molecular modelling of electric double layer capacitors, Phys. Chem. Chem. Phys. 16 (2014) 6519-6538.
[12] P. Simon, Y. Gogotsi, Capacitive energy storage in nanostructured carbon-electrolyte systems, Acc. Chem. Res. 46 (2013) 1094-1103.
[13] Q. Dou, L. Liu, B. Yang, J. Lang, X. Yan, Silica-grafted ionic liquids for revealing the respective charging behaviors of cations and anions in supercapacitors, Nat. Commun. 8 (2017) 2188.
[14] C. Lian, M. Janssen, H. Liu, R. van Roij, Blessing and Curse: How a supercapacitor’s large capacitance causes its slow charging, Phys. Rev. Lett. 124 (2020) 076001.
[15] J. Chmiola, G. Yushin, Y. Gogotsi, C. Portet, P. Simon, P.L. Taberna, Anomalous increase in carbon capacitance at pore sizes less than 1 nanometer, Science 313 (2006) 1760.
[16] T.A. Centeno, O. Sereda, F. Stoeckli, Capacitance in carbon pores of 0.7 to 15 nm: a regular pattern, Phys. Chem. Chem. Phys. 13 (2011) 12403-12406.
[17] A. García-Gómez, G. Moreno-Fernández, B. Lobato, T.A. Centeno, Constant capacitance in nanopores of carbon monoliths, Phys. Chem. Chem. Phys. 17 (2015) 15687-15690.
[18] W. Smythe, Static and Dynamic Electricity, 2rd ed., McGraw-Hill, NK, 1950.
[19] J. Huang, B.G. Sumpter, V. Meunier, Theoretical model for nanoporous carbon supercapacitors, Angew. Chem. Int. Ed. 47 (2008) 520-524.
[20] J. Huang, B.G. Sumpter, V. Meunier, A universal model for nanoporous carbon supercapacitors applicable to diverse pore regimes, carbon materials, and electrolytes, Chem. A Eur. J. 14 (2008) 6614-6626.
[21] G. Feng, R. Qiao, J. Huang, B.G. Sumpter, V. Meunier, Ion distribution in electrified micropores and its role in the anomalous enhancement of capacitance, ACS Nano 4 (2010) 2382-2390.
[22] S. Kondrat, A. Kornyshev, Superionic state in double-layer capacitors with nanoporous electrodes, J. Phys.: Condens. Matter. 23 (2011) 022201.
[23] S. Kondrat, N. Georgi, M.V. Fedorov, A.A. Kornyshev, A superionic state in nanoporous double-layer capacitors: insights from Monte Carlo simulations, Phys. Chem. Chem. Phys. 13 (2011) 11359-11366.
[24] G. Feng, D. Jiang, P.T. Cummings, Curvature effect on the capacitance of electric double layers at ionic liquid/onion-like carbon interfaces, J. Chem. Theory Comput. 8 (2012) 1058-1063.
[25] P. Wu, J. Huang, V. Meunier, B.G. Sumpter, R. Qiao, Complex capacitance scaling in ionic liquids-filled nanopores, ACS Nano 5 (2011) 9044-9051.
[26] G. Feng, P.T. Cummings, Supercapacitor capacitance exhibits oscillatory behavior as a function of nanopore size, J. Phys. Chem. Lett. 2 (2011) 2859-2864.
[27] E. Paek, A.J. Pak, G.S. Hwang, Curvature effects on the interfacial capacitance of carbon nanotubes in an ionic liquid, J. Phys. Chem. C. 117 (2013) 23539-23546.
[28] Y.X. Yu, J.Z. Wu, G.H. Gao, Ionic distribution, electrostatic potential and zeta potential at electrochemical interfaces, Chin. J. Chem. Eng. 12 (2004) 688-695.
[29] Z.D. Li, J.Z. Wu, Density functional theory for planar electric double layers: Closing the gap between simple and polyelectrolytes, J. Phys. Chem. B 7434-7487 (2006).
[30] K. Wang, Y.X. Yu, G.H. Gao, Density functional study on the structural and thermodynamic properties of aqueous DNA-electrolyte solution in the framework of cell model, J. Chem. Phys. 128 (2008) 185101.
[31] K. Wang, Y.X. Yu, G.H. Gao, G.S. Luo, Density-functional theory and Monte Carlo simulation study on the electric double layer around DNA in mixed-size counterion systems, The J. Chem. Phys. 123 (2005) 234904.
[32] B. Peng, Y.X. Yu, Ion distributions, exclusion coefficients, and separation factors of electrolytes in a charged cylindrical nanopore: A partially perturbative density functional theory study, J. Chem. Phys. 131 (2009) 134703.
[33] Y.X. Yu, J. Wu, G.H. Gao, Density-functional theory of spherical electric double layers and f potentials of colloidal particles in restricted-primitive-model electrolyte solutions, J. Chem. Phys. 120 (2004) 7223-7233.
[34] K. Yan-Shuang, W. Hai-Jun, Density functional theory approach for charged hard sphere fluids confined in spherical micro-cavity, Chin. Phys. Lett. 26 (2009) 126102.
[35] J. Forsman, C.E. Woodward, M. Trulsson, A classical density functional theory of ionic liquids, J. Phys. Chem. B. 115 (2011) 4606-4612.
[36] R. Szparaga, C.E. Woodward, J. Forsman, Theoretical prediction of the capacitance of ionic liquid films, J. Phys. Chem. C. 116 (2012) 15946-15951.
[37] G. Shrivastav, R.C. Remsing, H.K. Kashyap, Capillary evaporation of the ionic liquid [EMIM][BF₄] in nanoscale solvophobic confinement, J. Chem. Phys. 148 (2018) 193810.
[38] K. Liu, P. Zhang, J. Wu, Does capillary evaporation limit the accessibility of nonaqueous electrolytes to the ultrasmall pores of carbon electrodes?, J. Chem. Phys. 149 (2018) 234708.
[39] C. Lian, D. Jiang, H. Liu, J. Wu, A generic model for electric double layers in porous electrodes, J. Phys. Chem. C. 120 (2016) 8704-8710.
[40] R. Kumaravadivel, R. Evans, Calculations of the surface energy of simple liquid metals, J. Phys. C: Solid State Phys. 8 (1975) 793-808.
[41] R. van Roij, M. Dijkstra, J.P. Hansen, Phase diagram of charge-stabilized colloidal suspensions: van der Waals instability without attractive forces, Phys. Rev. E. 59 (1999) 2010-2025.
[42] J. Wu, Density functional theory for chemical engineering: From capillarity to soft materials, AIChE J. 52 (2006) 1169-1193.
[43] J. Wu, Z. Li, Density-functional theory for complex fluids, Annu. Rev. Phys. Chem. 58 (2007) 85-112.
[44] Y.X. Yu, J. Wu, Structures of hard-sphere fluids from a modified fundamentalmeasure theory, J. Chem. Phys. 117 (2002) 10156-10164.
[45] Y. Rosenfeld, Free-energy model for the inhomogeneous hard-sphere fluid mixture and density-functional theory of freezing, Phys. Rev. Lett. 63 (1989) 980-983.
[46] Z. Li, J. Wu, Density functional theory for planar electric double layers: Closing the gap between simple and polyelectrolytes, J. Phys. Chem. B. 110 (2006) 7473-7484.
[47] A. Etemad-Shahidi, J. Mahjoobi, Comparison between M5' model tree and neural networks for prediction of significant wave height in Lake Superior, Ocean Eng. 36 (2009) 1175-1181.
[48] H. Sui, L. Li, X. Zhu, D. Chen, G. Wu, Modeling the adsorption of PAH mixture in silica nanopores by molecular dynamic simulation combined with machine learning, Chemosphere 144 (2016) 1950-1959.
[49] A.A. Kornyshev, Double-layer in ionic liquids: paradigm change?, J. Phys. Chem. B. 111 (2007) 5545-5557.
[50] M.Z. Bazant, B.D. Storey, A.A. Kornyshev, Double layer in ionic liquids: Overscreening versus crowding, Phys. Rev. Lett. 106 (2011) 046102.
[51] M.V. Fedorov, A.A. Kornyshev, Towards understanding the structure and capacitance of electrical double layer in ionic liquids, Electrochim. Acta. 53 (2008) 6835-6840.
[52] D. Jiang, D. Meng, J. Wu, Density functional theory for differential capacitance of planar electric double layers in ionic liquids, Chem. Phys. Lett. 504 (2011) 153-158.
[53] A. Reindl, M. Bier, S. Dietrich, Electrolyte solutions at curved electrodes. II. Microscopic approach, J. Chem. Phys. 146 (2017) 154704.

Curvature effects on electric-double-layer capacitance

Curvature effects on electric-double-layer capacitance

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