采用泡沫铜电极的热再生氨电池性能数值模拟

doi:10.11949/0438-1157.20200126

化工学报 ›› 2020, Vol. 71 ›› Issue (8): 3770-3779.DOI: 10.11949/0438-1157.20200126

采用泡沫铜电极的热再生氨电池性能数值模拟

张永胜^1,²(),张亮^1,²(),李俊^1,²,付乾^1,²,朱恂^1,²,廖强^1,²,石雨^1,²

^1.低品位能源利用技术与系统教育部重点实验室，重庆 400030
^2.重庆大学工程热物理研究所，重庆 400030

收稿日期:2020-02-10 修回日期:2020-03-28 出版日期:2020-08-05 发布日期:2020-08-05
通讯作者: 张亮
作者简介:张永胜（1994—），男，硕士研究生，zysvictor@hotmail.com
基金资助:
国家自然科学基金面上项目(51976018);国家自然科学基金青年基金项目(51606022);重庆市基础科学与前沿技术项目(cstc2017jcyjAX0203);重庆市留学人员创业创新支持计划创新资助重点项目(cx2017020);中央高校基本科研业务费专项资金(10611 2016CDJXY 145504);低品位能源利用技术及系统教育部重点实验室固定人员科研基金(LLEUTS-2018005)

Numerical simulation of performance of thermally regenerative ammonia-based battery with copper foam electrode

Yongsheng ZHANG^1,²(),Liang ZHANG^1,²(),Jun LI^1,²,Qian FU^1,²,Xun ZHU^1,²,Qiang LIAO^1,²,Yu SHI^1,²

^1.Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Ministry of Education, Chongqing 400030, China
^2.Institute of Engineering Thermophysics, Chongqing University, Chongqing 400030, China

Received:2020-02-10 Revised:2020-03-28 Online:2020-08-05 Published:2020-08-05
Contact: Liang ZHANG

摘要/Abstract

摘要：

以采用泡沫铜电极的热再生氨电池（thermally regenerative ammonia-based battery，TRAB）为研究对象，建立了多孔介质内物质传输与电化学反应耦合的稳态模型，计算获得了电池性能及多孔电极内物质传输特性，并研究了电解质浓度和电极孔隙率对电池性能的影响。研究结果表明，从主流区界面到多孔电极内部，阳极氨和阴极铜离子浓度逐渐降低，存在一定的浓度梯度，而且随着反应电流的增大，浓度梯度明显增大。在一定的范围内分别增大阳极氨浓度和阴极铜离子浓度，从主流区向多孔电极内物质传输增强，电池性能均能不断提升；随着硫酸铵浓度的增大，电解质电导率增大，电池性能逐渐提升，但增幅逐渐减小。此外，多孔电极孔隙率也会影响电池性能，本研究中TRAB在电极孔隙率为0.6时获得最高的最大功率(15.3 mW)。

关键词: 热再生氨电池, 多孔泡沫电极, 数值模拟, 电化学, 传质, 最大功率, 孔隙率

Abstract:

A steady-state mathematical model that coupled the mass transfer and electrochemical reaction in a porous medium was proposed for a thermally regenerative ammonia-based battery (TRAB) with copper foam electrode. The battery performance and internal mass transfer characteristics of the porous electrode were obtained and the effects of electrolyte concentration and electrode porosity on battery performance were studied. The results showed that the anode ammonia and cathode copper ions were gradually consumed from the mainstream to the inside of the porous electrode, which led to a concentration gradient. With the increase of the reaction current, the concentration gradient increased obviously. In a certain range, with the increase of the concentration of anodic ammonia and cathode copper ions, the material transfer from the main flow area to the porous electrode improved. As the concentration of ammonium sulfate increases, the electrolyte conductivity increases, and the battery performance gradually improves, but the increase decreases gradually. In addition, the porous electrode porosity will also affect the battery performance. In this study, TRAB obtained the highest maximum power (15.3 mW) when the electrode porosity was 0.6.

Key words: thermally regenerative ammonia-based battery, porous foam electrode, numerical simulation, electrochemistry, mass transfer, maximal power, porosity

中图分类号:

TM 911.3

张永胜, 张亮, 李俊, 付乾, 朱恂, 廖强, 石雨. 采用泡沫铜电极的热再生氨电池性能数值模拟[J]. 化工学报, 2020, 71(8): 3770-3779.

Yongsheng ZHANG, Liang ZHANG, Jun LI, Qian FU, Xun ZHU, Qiang LIAO, Yu SHI. Numerical simulation of performance of thermally regenerative ammonia-based battery with copper foam electrode[J]. CIESC Journal, 2020, 71(8): 3770-3779.

图/表 11

图1 采用泡沫铜电极的TRAB计算模型及网格划分

Fig.1 Calculation model and meshing of the TRAB with copper foam electrodes

表1 几何区域尺寸参数

Table 1 Dimensional parameters of geometrical domain

参数	符号	数值/mm
阳极腔室长度	L_AL	30
阴极腔室长度	L_CL	30
泡沫铜阳极厚度	L_AC	4
泡沫铜阴极厚度	L_CC	4
阴离子交换膜厚度	L_AEM	1
电极高度	H	30

表2 模型中所使用的参数

Table 2 Parameters used in the model

参数	符号	数值	来源
Cu²⁺扩散系数/(m²/s)	$D C u 2 +$	1.5×10^-9	文献[33]
$C u (N H 3) 4 2 +$ 扩散系数/ (m²/s)	$D C u (N H 3) 4 2 +$	0.6 ×10^-9	文献[33]
NH₃扩散系数/ (m²/s)	$D N H 3$	1.7×10^-9	文献[33]
$N H 4 +$ 扩散系数/ (m²/s)	$D N H 4 +$	0.95 ×10^-9	文献[33]
电极孔隙率	$ε$	0.9	—
电极活性比表面积/ (m²/m³)	$a V$	4985	测量
Cu²⁺参考浓度/ (mol/L)	$c C u 2 +, r e f$	1	—
操作温度/K	T	298.15	测量
阳极电解质电导率/ (S/m)	$κ a$	6.3	测量
阴极电解质电导率/ (S/m)	$κ c$	7.8	测量
阳极反应速度常量/ (m/s)	$K 0 a$	7 ×10^-7	文献[33]
阴极反应速度常量/(m/s)	$K 0 c$	5 ×10^-6	文献[33]
Cu²⁺初始浓度/ (mol/L)	$c C u 2 + 0$	0.1	—
$N H 4 +$ 初始浓度/ (mol/L)	$c N H 4 + 0$	0.5	—
$C u (N H 3) 4 2 +$ 初始浓度/ (mol/L)	$c C u (N H 3) 4 2 + 0$	0.1	—
NH₃?H₂O初始浓度/ (mol/L)	$c N H 3 0$	0.6	—
反应(9)阴极传递系数	$α c c$	0.36	—
反应(10)阴极传递系数	$α c a$	0.64	—
式(11)阳极传递系数	$α a c$	0.5	—
式(12)阳极传递系数	$α a a$	0.5	—

表2 模型中所使用的参数

Table 2 Parameters used in the model

参数	符号	数值	来源
Cu²⁺扩散系数/(m²/s)	$D C u 2 +$	1.5×10^-9	文献[33]
$C u (N H 3) 4 2 +$ 扩散系数/ (m²/s)	$D C u (N H 3) 4 2 +$	0.6 ×10^-9	文献[33]
NH₃扩散系数/ (m²/s)	$D N H 3$	1.7×10^-9	文献[33]
$N H 4 +$ 扩散系数/ (m²/s)	$D N H 4 +$	0.95 ×10^-9	文献[33]
电极孔隙率	$ε$	0.9	—
电极活性比表面积/ (m²/m³)	$a V$	4985	测量
Cu²⁺参考浓度/ (mol/L)	$c C u 2 +, r e f$	1	—
操作温度/K	T	298.15	测量
阳极电解质电导率/ (S/m)	$κ a$	6.3	测量
阴极电解质电导率/ (S/m)	$κ c$	7.8	测量
阳极反应速度常量/ (m/s)	$K 0 a$	7 ×10^-7	文献[33]
阴极反应速度常量/(m/s)	$K 0 c$	5 ×10^-6	文献[33]
Cu²⁺初始浓度/ (mol/L)	$c C u 2 + 0$	0.1	—
$N H 4 +$ 初始浓度/ (mol/L)	$c N H 4 + 0$	0.5	—
$C u (N H 3) 4 2 +$ 初始浓度/ (mol/L)	$c C u (N H 3) 4 2 + 0$	0.1	—
NH₃?H₂O初始浓度/ (mol/L)	$c N H 3 0$	0.6	—
反应(9)阴极传递系数	$α c c$	0.36	—
反应(10)阴极传递系数	$α c a$	0.64	—
式(11)阳极传递系数	$α a c$	0.5	—
式(12)阳极传递系数	$α a a$	0.5	—

表3 物质守恒方程源项

Table 3 Source items of the mass conservation equation

源/汇	阳极	阴极
S₁( $N H 3$ )	$2 ? j a F$	0
S₂( $C u (N H 3) 4 2 +$ )	$- ? j a 2 F$	0
S₃( $C u 2 +$ )	0	$- ? j c 2 F$

表3 物质守恒方程源项

Table 3 Source items of the mass conservation equation

源/汇	阳极	阴极
S₁( $N H 3$ )	$2 ? j a F$	0
S₂( $C u (N H 3) 4 2 +$ )	$- ? j a 2 F$	0
S₃( $C u 2 +$ )	0	$- ? j c 2 F$

图2 模拟结果与实验结果对比图

Fig.2 Verification of proposed model against experimental results

图3 不同输出电压下阳极氨浓度分布(a)和阴极铜离子浓度分布(b)

Fig.3 Distribution of ammonia concentration (a) and Cu2+ concentration (b) at different voltages

图4 不同氨浓度对电池性能的影响(a)及阳极氨浓度分布(b)

Fig.4 Effects of different ammonia concentration on battery performance (a) and distribution of ammonia concentration (b)

图5 不同铜离子浓度对电池性能的影响(a)及阴极铜离子浓度分布(b)

Fig.5 Effects of different Cu2+ concentration on battery performance(a) and distribution of Cu2+ concentration(b)

表4 不同硫酸铵浓度的电解液电导率

Table 4 Conductivity of the electrolyte with different concentration of (NH4)2SO4

硫酸铵浓度/(mol/L)	阴极电解液电导率 $κ c$ /(S/m)	阳极电解液电导率 $κ a$ /(S/m)
0.5	7.8	6.3
1	13.3	11.3
1.5	22	19.9
2	25.6	23.5
2.5	28.9	26.7

表4 不同硫酸铵浓度的电解液电导率

Table 4 Conductivity of the electrolyte with different concentration of (NH4)2SO4

硫酸铵浓度/(mol/L)	阴极电解液电导率 $κ c$ /(S/m)	阳极电解液电导率 $κ a$ /(S/m)
0.5	7.8	6.3
1	13.3	11.3
1.5	22	19.9
2	25.6	23.5
2.5	28.9	26.7

图6 不同(NH4)2SO4浓度对电池性能的影响

Fig.6 Effects of different (NH4)2SO4 concentration on battery performance

图7 不同电极孔隙率对电池性能的影响

Fig.7 Effects of different electrode porosity on battery performance

参考文献 35

1	Lu H Y, Price L, Zhang Q. Capturing the invisible resource: analysis of waste heat potential in Chinese industry[J]. Applied Energy, 2016, 161: 497-511.
2	Jouhara H, Khordehgah N, Almahmoud S, et al. Waste heat recovery technologies and applications[J]. Thermal Science and Engineering Progress, 2018, 6: 268-289.
3	Woolley E, Luo Y, Simeone A. Industrial waste heat recovery: a systematic approach[J]. Sustainable Energy Technologies and Assessments, 2018, 29: 50-59.
4	陈昕, 王如竹. 一种低温余热高效利用的氨水动力循环[J]. 化工学报, 2016, 67(9): 3536-3544.
	Chen X, Wang R Z. An efficient ammonia-water power cycle in low temperature waste heat application[J]. CIESC Journal, 2016, 67(9): 3536-3544.
5	刘超, 徐进良. 一种新型天然气锅炉烟气余热回收系统[J]. 化工学报, 2013, 64(11): 4223-4230.
	Liu C, Xu J L. A novel heat recovery system for flue gas from natural gas boiler[J]. CIESC Journal, 2013, 64(11): 4223-4230.
6	路会同, 江龙, 王丽伟, 等. 低温余热驱动的无泵有机朗肯循环瞬时稳态发电性能[J]. 化工学报, 2017, 68(12): 4709-4716.
	Lu H T, Jiang L, Wang L W, et al. Instantaneous steady state of pumpless organic Rankine cycle driven by low temperature heat source[J]. CIESC Journal, 2017, 68(12): 4709-4716.
7	谢飞博, 朱彤, 高乃平. 冷源温度对小型ORC低温余热发电系统的影响[J]. 化工学报, 2016, 67(10): 4111-4117.
	Xie F B, Zhu T, Gao N P. Effect of cold source temperature on power generation of small organic Rankine cycle system with low-grade waste heat[J]. CIESC Journal, 2016, 67(10): 4111-4117.
8	Bell L E. Cooling, heating, generating power, and recovering waste heat with thermoelectric systems[J]. Science, 2008, 321(5895): 1457-1461.
9	Abraham T J, Macfarlane D R, Baughman R H, et al. Towards ionic liquid-based thermoelectrochemical cells for the harvesting of thermal energy[J]. Electrochimica Acta, 2013, 113: 87-93.
10	Rahimi M, Straub A P, Zhang F, et al. Emerging electrochemical and membrane-based systems to convert low-grade heat to electricity[J]. Energy & Environmental Science, 2018, 11(2): 276-285.
11	Straub A P, Deshmukh A, Elimelech M. Pressure-retarded osmosis for power generation from salinity gradients: is it viable?[J]. Energy & Environmental Science, 2016, 9(1): 31-48.
12	Kim T, Rahimi M, Logan B E, et al. Harvesting energy from salinity differences using battery electrodes in a concentration flow cell[J]. Environmental Science & Technology, 2016, 50(17): 9791-9797.
13	Al-Masri D, Dupont M, Yunis R, et al. The electrochemistry and performance of cobalt-based redox couples for thermoelectrochemical cells[J]. Electrochimica Acta, 2018, 269: 714-723.
14	Anari E H B, Romano M, Teh W X, et al. Substituted ferrocenes and iodine as synergistic thermoelectrochemical heat harvesting redox couples in ionic liquids[J]. Chemical Communications, 2016, 52(4): 745-748.
15	Marino M, Misuri L, Carati A, et al. Boosting the voltage of a salinity-gradient-power electrochemical cell by means of complex-forming solutions[J]. Applied Physics Letters, 2014, 105: 0339013.
16	Zhang F, Liu J, Yang W L, et al. A thermally regenerative ammonia-based battery for efficient harvesting of low-grade thermal energy as electrical power[J]. Energy & Environmental Science, 2015, 8(1): 343-349.
17	Zhu X P, Rahimi M, Gorski C A, et al. A thermally-regenerative ammonia-based flow battery for electrical energy recovery from waste heat[J]. ChemSusChem, 2016, 9(8): 873-879.
18	Zhang F, Labarge N, Yang W L, et al. Enhancing low-grade thermal energy recovery in a thermally regenerative ammonia battery using elevated temperatures[J]. ChemSusChem, 2015, 8(6): 1043-1048.
19	Rahimi M, Zhu L, Kowalski K L, et al. Improved electrical power production of thermally regenerative batteries using a poly(phenylene oxide) based anion exchange membrane[J]. Journal of Power Sources, 2017, 342: 956-963.
20	Rahimi M, D􀆳Angelo A, Gorski C A,et al. Electrical power production from low-grade waste heat using a thermally regenerative ethylenediamine battery[J]. Journal of Power Sources, 2017, 351: 45-50.
21	Rahimi M, Kim T, Gorski C A, et al. A thermally regenerative ammonia battery with carbon-silver electrodes for converting low-grade waste heat to electricity[J]. Journal of Power Sources, 2018, 373: 95-102.
22	Wang W G, Shu G Q, Tian H, et al. A bimetallic thermally-regenerative ammonia-based flow battery for low-grade waste heat recovery[J]. Journal of Power Sources, 2019, 424: 184-192.
23	王福添, 张绍志, 陈光明. 热再生氨化学电池的实验研究及热力学分析[J]. 热能动力工程, 2018, 33(9): 132-137.
	Wang F T, Zhang S Z, Chen G M. Experimental study and thermodynamic analysis on thermally regenerative ammonia battery[J]. Journal of Engineering for Thermal Energy and Power, 2018, 33(9): 132-137.
24	Rahimi M, Schoener Z, Zhu X P, et al. Removal of copper from water using a thermally regenerative electrodeposition battery[J]. Journal of Hazardous Materials, 2017, 322(B): 551-556.
25	唐志强, 张亮, 朱恂, 等. 不同Cu²⁺浓度下热再生氨电池产电及Cu²⁺去除特性[J]. 化工学报, 2019, 70(12): 4804-4810.
	Tang Z Q, Zhang L, Zhu X, et al. Effect of Cu²⁺ concentration in cathode on power generation and copper removal of thermally regenerative ammonia-based battery[J]. CIESC Journal, 2019, 70(12): 4804-4810.
26	张绍志, 王福添, 陈光明, 等. 一种输出电能的第二类吸收式热泵: 2016105464590[P]. 2016-07-13.
	Zhang S Z, Wang F T, Chen G M, et al. A second kind of absorption heat pump for energy output: 2016105464590[P]. 2016-07-13.
27	张绍志, 王福添, 陈光明, 等. 一种低品位热驱动的冷电联供系统及其应用方法: 2016109965536[P]. 2016-11-13.
	Zhang S Z, Wang F T, Chen G M, et al. A low-grade thermal driven cold electricity cogeneration system and its application method: 2016109965536[P]. 2016-11-13.
28	Vicari F, D􀆳Angelo A, Kouko Y,et al. On the regeneration of thermally regenerative ammonia batteries[J]. Journal of Applied Electrochemistry,2018, 48(12SI): 1381-1388.
29	王福添. 热再生氨化学电池的电极反应及基本循环研究[D]. 杭州: 浙江大学, 2018.
	Wang F T. Study on the electrode reaction and basic cycle of the thermally regenerative ammonia battery[D]. Hangzhou: Zhejiang University, 2018.
30	Zhang L, Li Y X, Zhu X, et al. Copper foam electrodes for increased power generation in thermally regenerative ammonia-based batteries for low-grade waste heat recovery[J]. Industrial & Engineering Chemistry Research, 2019, 58(17): 7408-7415.
31	李彦翔, 张亮, 朱恂, 等. 传质对热可再生氨电池性能的影响[J]. 工程热物理学报, 2019, (3): 668-671.
	Li Y X, Zhang L, Zhu X, et al. Effect of mass transfer on the performance of thermally regenerative ammonia-based battery[J]. Journal of Engineering Thermophysics, 2019, (3): 668-671.
32	Zhang Y S, Zhang L, Li J, et al. Performance of a thermally regenerative ammonia-based flow battery with 3D porous electrodes: effect of reactor and electrode design[J]. Electrochimica Acta, 2020, 331: 135442.
33	Wang W, Shu G, Tian H, et al. A numerical model for a thermally-regenerative ammonia-based flow battery using for low grade waste heat recovery[J]. Journal of Power Sources, 2018, 388: 32-44.
34	高明峰. 钒微流控燃料电池的数值模拟研究[D]. 长春: 吉林大学, 2012.
	Gao M F. Numerical simulation study on vanadium microfluidic fuel cell[D]. Changchun: Jilin University, 2012.
35	Wang R, Li Y, He Y. Achieving gradient-pore-oriented graphite felt for vanadium redox flow batteries: meeting improved electrochemical activity and enhanced mass transport from nano-to micro-scale[J]. Journal of Materials Chemistry A, 2019, 7(18): 10962-10970.

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采用泡沫铜电极的热再生氨电池性能数值模拟

Numerical simulation of performance of thermally regenerative ammonia-based battery with copper foam electrode

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