化工学报 ›› 2022, Vol. 73 ›› Issue (6): 2529-2542.doi: 10.11949/0438-1157.20220135

• 流体力学与传递现象 • 上一篇    下一篇

基于模拟退火算法的真实多孔电极中热-质传递的研究

黄盼1(),练成1,2(),刘洪来1,2()   

  1. 1.华东理工大学化工学院,上海 200237
    2.华东理工大学化学与分子工程学院,上海 200237
  • 收稿日期:2022-01-25 修回日期:2022-03-22 出版日期:2022-06-05 发布日期:2022-06-30
  • 通讯作者: 练成,刘洪来 E-mail:panhuang@mail.ecust.edu.cn;liancheng@ecust.edu.cn;hlliu@ecust.edu.cn
  • 作者简介:黄盼(1997—),男,博士研究生,panhuang@mail.ecust.edu.cn
  • 基金资助:
    国家自然科学基金项目(91834301);国家自然科学基金创新群体项目(51621002);上海市青年科技启明星计划项目(21QA1401900);能源清洁利用国家重点实验室开放基金(ZJUCEU2021005)

Heat-mass transfer in real porous electrode based on simulated annealing algorithm

Pan HUANG1(),Cheng LIAN1,2(),Honglai LIU1,2()   

  1. 1.School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
    2.School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
  • Received:2022-01-25 Revised:2022-03-22 Published:2022-06-05 Online:2022-06-30
  • Contact: Cheng LIAN,Honglai LIU E-mail:panhuang@mail.ecust.edu.cn;liancheng@ecust.edu.cn;hlliu@ecust.edu.cn

摘要:

电极中的离子-电子传递和传热显著影响着电化学储能性能。深入研究多孔电极中的热-质传递现象这一典型的介尺度问题,对高性能电化学储能器件的设计具有重要意义。采用一种基于改进的状态更新的随机重建方法和动态退火系数相结合的模拟退火算法,将图像分割后的二维SEM图重构为真实的三维多孔电极。通过重构多孔电极和PNP方程与傅里叶定律,建立真实多孔电极中的离子传递和电极导热模型。结果表明,当充电时间为0.1个平板充电弛豫时间时,离子主要吸附在多孔电极骨架相与体相的接触面上,且离子倾向于从截面边缘往中心迁移。由于实际的导热距离远小于多孔电极厚度,多孔电极中的热弛豫时间远小于平板的热弛豫时间。

关键词: 多孔电极, 热-质传递, 模拟退火算法, 离子传递, 电极导热

Abstract:

The ion-electron transfer and heat transfer in the electrode significantly affect the electrochemical energy storage performance. The study of heat - mass transfer in porous electrodes, as a typical mesoscale problem, is of great significance to the design of high-performance electrochemical energy storage devices. At present, the simplified model of porous electrode can only approximate the real pore size distribution to a certain extent, and it is difficult to represent the diversified surface morphology and the complex distribution of catalytic active sites, which limits the in-depth study of heat-mass transfer in porous electrode. Therefore, a simulated annealing algorithm based on improved state updating random reconstruction method and dynamic annealing coefficient was used to reconstruct the two-dimensional SEM image after image segmentation into a real three-dimensional porous electrode. Then, the ion transport and electrode heat conduction models in real porous electrodes were established by reconstructing the PNP equation and Fourier law. The results show that when the charging time is 0.1 plate charging relaxation time, the ions mainly adsorb on the contact surface between the skeleton phase of the porous electrode and bulk phase, and the ions tend to migrate from the edge of the cross section to the center. In addition, since the actual thermal conduction distance is much smaller than the thickness of the porous electrode, the thermal relaxation time in the porous electrode is much smaller than that of the flat plate.

Key words: porous electrode, heat-mass transfer, simulated annealing algorithm, ion transport, electrode heat conduction

中图分类号: 

  • TQ 152

图1

储能和转换过程中的电极尺度问题及与其他尺度问题的联系"

图2

基于模拟退火算法重构的真实多孔电极中的离子传递和电极导热"

图3

多孔电极三维重构流程图"

图4

模拟退火算法流程图"

图5

中心像素在不同结构中的DPN值"

表1

模拟退火算法退出迭代的参数设置"

EthΔEthNconNiter
1×10-61×10-85001×106

表2

通过模拟退火算法重构的多孔电极的结构参数"

多孔电极尺寸/

(个立方体)

边长/μm结构参数
孔隙率比表面积/m-1分形维数曲折因子
50×50×500.410.5451.493×1073.282.36
100×100×1000.820.5451.223×1073.192.01
200×200×2001.640.5451.306×1073.112.13

图6

真实多孔电极中的离子传递和电极导热模型"

图7

重构结构的能量函数随迭代次数的变化"

图8

10-1τRC时不同位置的电势分布?/Vm"

图9

10-1τRC时不同位置的浓度分布(c++c-)/(2c0)"

图10

不同时刻下的温度分布(T-T0)/ΔT0的等值面图"

1 Kong L J, Zhong M, Shuang W, et al. Electrochemically active sites inside crystalline porous materials for energy storage and conversion[J]. Chemical Society Reviews, 2020, 49(8): 2378-2407.
2 Zhou J W, Wang B. Emerging crystalline porous materials as a multifunctional platform for electrochemical energy storage[J]. Chemical Society Reviews, 2017, 46(22): 6927-6945.
3 Sun M H, Huang S Z, Chen L H, et al. Applications of hierarchically structured porous materials from energy storage and conversion, catalysis, photocatalysis, adsorption, separation, and sensing to biomedicine[J]. Chemical Society Reviews, 2016, 45(12): 3479-3563.
4 Yang X Y, Chen L H, Li Y, et al. Hierarchically porous materials: synthesis strategies and structure design[J]. Chemical Society Reviews, 2017, 46(2): 481-558.
5 Berre I, Doster F, Keilegavlen E. Flow in fractured porous media: a review of conceptual models and discretization approaches[J]. Transport in Porous Media, 2019, 130(1): 215-236.
6 Shojaeefard M H, Molaeimanesh G R, Nazemian M, et al. A review on microstructure reconstruction of PEM fuel cells porous electrodes for pore scale simulation[J]. International Journal of Hydrogen Energy, 2016, 41(44): 20276-20293.
7 Tao H L, Lian C, Liu H L. Multiscale modeling of electrolytes in porous electrode: from equilibrium structure to non-equilibrium transport[J]. Green Energy & Environment, 2020, 5(3): 303-321.
8 Lian C, Janssen M, Liu H L, et al. Blessing and curse: how a supercapacitor's large capacitance causes its slow charging[J]. Physical Review Letters, 2020, 124(7): 076001.
9 Ali B A, Allam N K. A first-principles roadmap and limits to design efficient supercapacitor electrode materials[J]. Physical Chemistry Chemical Physics: PCCP, 2019, 21(32): 17494-17511.
10 Kong X, Jiang J, Lu D N, et al. Molecular theory for electrokinetic transport in pH-regulated nanochannels[J]. The Journal of Physical Chemistry Letters, 2014, 5(17): 3015-3020.
11 Gan Z D, Wang Y L, Wang M, et al. Ionophobic nanopores enhancing the capacitance and charging dynamics in supercapacitors with ionic liquids[J]. Journal of Materials Chemistry A, 2021, 9(29): 15985-15992.
12 Bi S, Banda H, Chen M, et al. Molecular understanding of charge storage and charging dynamics in supercapacitors with MOF electrodes and ionic liquid electrolytes[J]. Nature Materials, 2020, 19(5): 552-558.
13 Kavokine N, Netz R R, Bocquet L. Fluids at the nanoscale: from continuum to subcontinuum transport[J]. Annual Review of Fluid Mechanics, 2021, 53: 377-410.
14 Tao H L, Lin S, Lian C, et al. Microscopic insights into the ion transport in graphene-based membranes with different interlayer spacing distributions[J]. Chemical Engineering Science, 2020, 212: 115354.
15 d'Entremont A, Pilon L. First-principles thermal modeling of electric double layer capacitors under constant-current cycling[J]. Journal of Power Sources, 2014, 246: 887-898.
16 Sakaguchi H, Baba R. Charging dynamics of the electric double layer in porous media[J]. Physical Review E, 2007, 76(1): 011501.
17 Webman I. Effective-medium approximation for diffusion on a random lattice[J]. Physical Review Letters, 1981, 47(21): 1496-1499.
18 Lian C, Su H P, Li C Z, et al. Non-negligible roles of pore size distribution on electroosmotic flow in nanoporous materials[J]. ACS Nano, 2019, 13(7): 8185-8192.
19 Gostick J, Aghighi M, Hinebaugh J, et al. OpenPNM: a pore network modeling package[J]. Computing in Science & Engineering, 2016, 18(4): 60-74.
20 Sadeghi M A, Aganou M, Kok M, et al. Exploring the impact of electrode microstructure on redox flow battery performance using a multiphysics pore network model[J]. Journal of the Electrochemical Society, 2019, 166(10): A2121-A2130.
21 Agnaou M, Sadeghi M A, Tranter T G, et al. Modeling transport of charged species in pore networks: solution of the Nernst-Planck equations coupled with fluid flow and charge conservation equations[J]. Computers & Geosciences, 2020, 140: 104505.
22 Conroy G C, Vannier M W. Noninvasive three-dimensional computer imaging of matrix-filled fossil skulls by high-resolution computed tomography[J]. Science, 1984, 226(4673): 456-458.
23 Pan T. Computed tomography: from photon statistics to modern cone-beam CT[J]. Journal of Nuclear Medicine, 2009, 50(7): 1194.
24 Kunanusont N, Shimoyama Y. Porous carbon electrode for Li-air battery fabricated from solvent expansion during supercritical drying[J]. The Journal of Supercritical Fluids, 2018, 133: 77-85.
25 Bousige C, Ghimbeu C M, Vix-Guterl C, et al. Realistic molecular model of kerogen's nanostructure[J]. Nature Materials, 2016, 15(5): 576-582.
26 van Breugel K. Numerical simulation of hydration and microstructural development in hardening cement-based materials (Ⅰ): Theory[J]. Cement and Concrete Research, 1995, 25(2): 319-331.
27 Ankit K, Urai J L, Nestler B. Microstructural evolution in bitaxial crack-seal veins: a phase-field study[J]. Journal of Geophysical Research: Solid Earth, 2015, 120(5): 3096-3118.
28 Torquato S, Haslach H W. Random heterogeneous materials: microstructure and macroscopic properties[J]. Applied Mechanics Reviews, 2002, 55(4): B62-B63.
29 Torquato S, Lu B. Chord-length distribution function for two-phase random media[J]. Physical Review E, 1993, 47(4): 2950-2953.
30 Okabe H, Blunt M J. Prediction of permeability for porous media reconstructed using multiple-point statistics[J]. Physical Review E, 2004, 70(6): 066135.
31 Yeong C L Y, Torquato S. Reconstructing random media[J]. Physical Review E, 1998, 57(1): 495-506.
32 Karsanina M V, Gerke K M, Skvortsova E B, et al. Universal spatial correlation functions for describing and reconstructing soil microstructure[J]. PLoS One, 2015, 10(5): e0126515.
33 Mariethoz G, Renard P, Straubhaar J. The Direct Sampling method to perform multiple-point geostatistical simulations[J]. Water Resources Research, 2010, 46(11): W11536.
34 Wu W, Jiang F M. Simulated annealing reconstruction and characterization of the three-dimensional microstructure of a LiCoO2 lithium-ion battery cathode[J]. Materials Characterization, 2013, 80: 62-68.
35 Habte B T, Jiang F M. Microstructure reconstruction and impedance spectroscopy study of LiCoO2, LiMn2O4 and LiFePO4 Li-ion battery cathodes[J]. Microporous and Mesoporous Materials, 2018, 268: 69-76.
36 Habte B T, Jiang F M. Effect of microstructure morphology on Li-ion battery graphite anode performance: electrochemical impedance spectroscopy modeling and analysis[J]. Solid State Ionics, 2018, 314: 81-91.
37 Stenzel O, Westhoff D, Manke I, et al. Graph-based simulated annealing: a hybrid approach to stochastic modeling of complex microstructures[J]. Modelling and Simulation in Materials Science and Engineering, 2013, 21(5): 055004.
38 Prokop M, Vesely M, Capek P, et al. High-temperature PEM fuel cell electrode catalyst layers(Ⅰ): Microstructure reconstructed using FIB-SEM tomography and its calculated effective transport properties[J]. Electrochimica Acta, 2022, 413: 140133.
39 He S, Habte B T, Jiang F. LBM prediction of effective electric and species transport properties of lithium-ion battery graphite anode[J]. Solid State Ionics, 2016, 296: 146-153.
40 Vinodh R, Gopi C V V M, Kummara V G R, et al. A review on porous carbon electrode material derived from hypercross-linked polymers for supercapacitor applications[J]. Journal of Energy Storage, 2020, 32: 101831.
41 Vandaele J, Louis B, Liu K Z, et al. Structural characterization of fibrous synthetic hydrogels using fluorescence microscopy[J]. Soft Matter, 2020, 16(17): 4210-4219.
42 Laurent L, Bart R, Diederik J, et al. Nested multiresolution hierarchical simulated annealing algorithm for porous media reconstruction[J]. Physical Review E, 2019, 100(5): 053316.
43 Tang T, Teng Q, He X, et al. A pixel selection rule based on the number of different-phase neighbours for the simulated annealing reconstruction of sandstone microstructure[J]. Journal of Microscopy, 2009, 234(3): 262-268.
44 Talukdar S, Torsæter O, Ioannidis M, et al. Stochastic reconstruction of chalk from 2D images[J]. Transport in Porous Media, 2002, 48(1): 101-123.
45 Foroutan-pour K, Dutilleul P, Smith D L. Advances in the implementation of the box-counting method of fractal dimension estimation[J]. Applied Mathematics and Computation, 1999, 105(2): 195-210.
46 Fernández-Martínez M, Sánchez-Granero M A. Fractal dimension for fractal structures: a Hausdorff approach revisited[J]. Journal of Mathematical Analysis and Applications, 2014, 409(1): 321-330.
47 Flandrin P. Wavelet analysis and synthesis of fractional Brownian motion[J]. IEEE Transactions on Information Theory, 1992, 38(2): 910-917.
48 Kim A S, Chen H Q. Diffusive tortuosity factor of solid and soft cake layers: a random walk simulation approach[J]. Journal of Membrane Science, 2006, 279(1/2): 129-139.
49 Janssen M, Bier M. Transient response of an electrolyte to a thermal quench[J]. Physical Review E, 2019, 99(4): 042136.
50 Nightingale E R. Phenomenological theory of ion solvation. Effective radii of hydrated ions[J]. The Journal of Physical Chemistry, 1959, 63(9): 1381-1387.
51 Wang M, Li P, Yu F Q. Hierarchical porous carbon foam-based phase change composite with enhanced loading capacity and thermal conductivity for efficient thermal energy storage[J]. Renewable Energy, 2021, 172: 599-605.
52 Kilic M S, Bazant M Z, Ajdari A. Steric effects in the dynamics of electrolytes at large applied voltages(Ⅰ): Double-layer charging[J]. Physical Review E, 2007, 75(2): 021502.
53 Kilic M S, Bazant M Z, Ajdari A. Steric effects in the dynamics of electrolytes at large applied voltages(Ⅱ): Modified Poisson-Nernst-Planck equations[J]. Physical Review E, 2007, 75(2): 021503.
54 Saurabh K, Solovchuk M A, Sheu T W H. Lattice Boltzmann method to simulate three-dimensional ion channel flow using fourth order Poisson-Nernst-Planck-Bikerman model[J]. Physics of Fluids, 2021, 33(8): 081910.
55 Raissi M, Karniadakis G E. Hidden physics models: machine learning of nonlinear partial differential equations[J]. Journal of Computational Physics, 2018, 357: 125-141.
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