流动电极电容去离子去除铵根离子模型及优化

doi:10.16085/j.issn.1000-6613.2021-0725

摘要/Abstract

摘要：

为了更直观地研究流动电极电容去离子（flow electrode capacitive deionization, FCDI）除氨工艺的机理并进行高效改进，本文构建了FCDI装置去除NH $4 +$ 的电化学稳态模型，实验结果模拟准确率达到93.8%。利用该模型研究了FCDI除氨工艺在进水流量、电流密度、电极液中活性炭质量分数等工况条件下的能耗和去除效率变化趋势，计算离子选择性和去除速率两个指标，定性阐明操作参数对去除氨的影响机理，筛选出较优化工况。研究结果表明，FCDI除氨工艺在进水流量1.25mL/min、电流密度21.26A/m²、活性炭质量分数为10%时，除氨效率为74.5%，能耗为29.62kWh/kg N，达到较为理想的状态。在优化的工况条件下，讨论了NH $4 +$ 在FCDI装置内部的微观传输情况，考虑到过长的流道长度会增强电流密度的极化现象，降低装置除氨性能，提出了串联装置的建议。保持流道长度和工况条件不变，串联的装置可以比原装置的去除效率提升32.9%，同时去除单位质量N的能耗降低22.0%，表明装置的改进是有效的。优化后的FCDI除氨工艺比同类处理工艺更有优势，NH $4 +$ 去除效率更高，能耗更低，具有广泛应用前景。

关键词: 流动电极电容去离子, 电化学, 模型, 废水, 氨氮

Abstract:

In order to more intuitively study the mechanism of the flow electrode capacitive deionization (FCDI) ammonia removal process and make efficient improvements, an electrochemical steady-state model for the removal of ammonium ions by the FCDI device was constructed, and the simulation accuracy of the experimental results reached 93.8%. The model was used to study the energy consumption and removal efficiency change trend of the FCDI ammonia removal process under the conditions of inlet water flow, current density, and active carbon mass fraction in the electrode solution. Two indicators of ion selectivity and removal rate were calculated which qualitatively explained the influence mechanism of operating parameters on the removal of ammonia to optimize working conditions. The results showed that when the FCDI ammonia removal process has an inlet water flow of 1.25mL/min, a current density of 21.26A/m², and an activated carbon mass fraction in the electrode solution of 10%, the ammonia removal efficiency is 74.5%, and the energy consumption is 29.62kWh/kg N, which has reached the comparatively ideal result. Under the optimized working conditions, the situation that the microscopic transmission of ammonium ions in the FCDI device was discussed. Considering that the excessively long flow channel length would increase the polarization of the current and reduce the ammonia removal performance of the device, suggestions for series installation were put forward. Keeping the length of the flow channel and the working conditions unchanged, the series-connected device can increase the removal efficiency by 32.9% compared with the original device, and at the same time can reduce the energy consumption per unit mass of N by 22.0%, indicating that the improvement of the device is effective. The optimized FCDI ammonia removal process with higher ammonium ions removal efficiency, lower energy consumption, and broad application prospects has more advantages than similar treatment processes.

Key words: flow electrode capacitive deionization (FCDI), electrochemistry, model, waste water, ammonia nitrogen

中图分类号:

X703.1

李翱, 王宏洋, 孙宇巍, 王旭, 汪霞, 朱光灿. 流动电极电容去离子去除铵根离子模型及优化[J]. 化工进展, 2022, 41(4): 2123-2131.

LI Ao, WANG Hongyang, SUN Yuwei, WANG Xu, WANG Xia, ZHU Guangcan. Model and optimization of flow electrode capacitive deionization for ammonium ion removal[J]. Chemical Industry and Engineering Progress, 2022, 41(4): 2123-2131.

图/表 11

图1 模型构型图1—脱盐室；2—阴极室；3—阳极室；4—阳离子交换膜；5—阴离子交换膜；6, 7—边界层

图2 数学模型结构示意图

图3 FCDI除氨过程中各部分电势分布的等效电路示意图USt—Stern电势；UD—Donnan电势；UT—Nernst-Plank方程中的离子传输电势；UO—欧姆损失电势

图4 装置结构示意图

表1 实验工况表

操作条件	序号	电流密度 /A·m^-2	进水流量 /mL·min^-1	活性炭质量分数 /%
恒电流	1	11.76	1.69	10
恒电流	2	16.81	1.69	10
恒电流	3	21.85	1.69	10
恒电流	4	31.93	1.69	10
进水流量	5	21.85	0.7	10
进水流量	6	21.85	1.2	10
进水流量	7	21.85	1.69	10
进水流量	8	21.85	2.4	10
进水流量	9	21.85	3.1	10
活性炭质量分数	10	31.93	1.69	5
活性炭质量分数	11	31.93	1.69	7
活性炭质量分数	12	31.93	1.69	10
活性炭质量分数	13	31.93	1.69	15

图5 FCDI装置对Na+和NH4+的去除效率随操作条件的变化趋势图

图6 流量（0.5~3.3mL/min）对FCDI装置除氨性能影响的Ragone图

图7 电流密度（8.4~33.6A/m2）对FCDI装置除氨性能影响的Ragone图

图8 电极液中活性炭质量分数（4%~16%）对FCDI装置除氨性能影响的Ragone图

图9 进水处流体单元的离子迁移状态随其在流道中的流动时间的变化趋势

图10 模型微元中电极对离子的吸附速率和选择性随装置内部相对位置变化的Ragone图

参考文献 22

1	SUN C, CHEN L, ZHAI L M, et al. National assessment of nitrogen fertilizers fate and related environmental impacts of multiple pathways in China[J]. Journal of Cleaner Production, 2020, 277: 123519.
2	DAHIYA S, MISHRA B K. Enhancing understandability and performance of flow electrode capacitive deionisation by optimizing configurational and operational parameters: a review on recent progress[J]. Separation and Purification Technology, 2020, 240: 116660.
3	JEON S I, PARK H R, YEO J G, et al. Desalination via a new membrane capacitive deionization process utilizing flow-electrodes[J]. Energy & Environmental Science, 2013, 6(5): 1471.
4	MA J X, HE C, HE D, et al. Analysis of capacitive and electrodialytic contributions to water desalination by flow-electrode CDI[J]. Water Research, 2018, 144: 296-303.
5	ZHANG C Y, MA J X, HE D, et al. Capacitive membrane stripping for ammonia recovery (CapAmm) from dilute wastewaters[J]. Environmental Science & Technology Letters, 2018, 5(1): 43-49.
6	FANG K, GONG H, HE W Y, et al. Recovering ammonia from municipal wastewater by flow-electrode capacitive deionization[J]. Chemical Engineering Journal, 2018, 348: 301-309.
7	MA J J, ZHANG C Y, YANG F, et al. Carbon black flow electrode enhanced electrochemical desalination using single-cycle operation[J]. Environmental Science & Technology, 2020, 54(2): 1177-1185.
8	ROMMERSKIRCHEN A, OHS B, HEPP K A, et al. Modeling continuous flow-electrode capacitive deionization processes with ion-exchange membranes[J]. Journal of Membrane Science, 2018, 546: 188-196.
9	WANG L, ZHANG C Y, HE C, et al. Equivalent film-electrode model for flow-electrode capacitive deionization: experimental validation and performance analysis[J]. Water Research, 2020, 181: 115917.
10	BAZANT M Z, THORNTON K, AJDARI A. Diffuse-charge dynamics in electrochemical systems[J]. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 2004, 70(2 Pt 1): 021506.
11	DE LINT W B S, BIESHEUVEL P M, VERWEIJ H. Application of the charge regulation model to transport of ions through hydrophilic membranes: one-dimensional transport model for narrow pores (nanofiltration)[J]. Journal of Colloid and Interface Science, 2002, 251(1): 131-142.
12	BIESHEUVEL P M, FU Y, BAZANT M Z. Electrochemistry and capacitive charging of porous electrodes in asymmetric multicomponent electrolytes[J]. Russian Journal of Electrochemistry, 2012, 48(6): 580-592.
13	BIESHEUVEL P M, ZHAO R, PORADA S, et al. Theory of membrane capacitive deionization including the effect of the electrode pore space[J]. Journal of Colloid and Interface Science, 2011, 360(1): 239-248.
14	MUBITA T M, DYKSTRA J E, BIESHEUVEL P M, et al. Selective adsorption of nitrate over chloride in microporous carbons[J]. Water Research, 2019, 164: 114885.
15	SHAPOSHNIK V A, VASIL’EVA V I, GRIGORCHUK O V. Diffusion boundary layers during electrodialysis[J]. Russian Journal of Electrochemistry, 2006, 42(11): 1202-1207.
16	NEWMAN J S. Electrochemical systems[M]. New York: Prentice Englewood Cliffs, 1973: 17.
17	MA J J, MA J X, ZHANG C Y, et al. Water recovery rate in short-circuited closed-cycle operation of flow-electrode capacitive deionization (FCDI)[J]. Environmental Science & Technology, 2019, 53(23): 13859-13867.
18	KIM T, YOON J. CDI ragone plot as a functional tool to evaluate desalination performance in capacitive deionization[J]. RSC Advances, 2015, 5(2): 1456-1461.
19	ZHANG X D, ZUO K C, ZHANG X R, et al. Selective ion separation by capacitive deionization (CDI) based technologies: a state-of-the-art review[J]. Environmental Science: Water Research & Technology, 2020, 6(2): 243-257.
20	YANG Y, SHIN J, JASPER J T, et al. Multilayer heterojunction anodes for saline wastewater treatment: design strategies and reactive species generation mechanisms[J]. Environmental Science & Technology, 2016, 50(16): 8780-8787.
21	REN S T, LI M C, SUN J Y, et al. A novel electrochemical reactor for nitrogen and phosphorus recovery from domestic wastewater[J]. Frontiers of Environmental Science & Engineering, 2017, 11(4): 1-6.
22	DESLOOVER J, ABATE WOLDEYOHANNIS A, VERSTRAETE W, et al. Electrochemical resource recovery from digestate to prevent ammonia toxicity during anaerobic digestion[J]. Environmental Science & Technology, 2012, 46(21):12209-12216.

[1]	徐晨阳, 都健, 张磊. 基于图神经网络的化学反应优劣评价[J]. 化工进展, 2023, 42(S1): 205-212.
[2]	张明焱, 刘燕, 张雪婷, 刘亚科, 李从举, 张秀玲. 非贵金属双功能催化剂在锌空气电池研究进展[J]. 化工进展, 2023, 42(S1): 276-286.
[3]	胡喜, 王明珊, 李恩智, 黄思鸣, 陈俊臣, 郭秉淑, 于博, 马志远, 李星. 二硫化钨复合材料制备与储钠性能研究进展[J]. 化工进展, 2023, 42(S1): 344-355.
[4]	张杰, 白忠波, 冯宝鑫, 彭肖林, 任伟伟, 张菁丽, 刘二勇. PEG及其复合添加剂对电解铜箔后处理的影响[J]. 化工进展, 2023, 42(S1): 374-381.
[5]	许春树, 姚庆达, 梁永贤, 周华龙. 共价有机框架材料功能化策略及其对Hg(Ⅱ)和Cr(Ⅵ)的吸附性能研究进展[J]. 化工进展, 2023, 42(S1): 461-478.
[6]	赵景超, 谭明. 表面活性剂对电渗析减量化工业含盐废水的影响[J]. 化工进展, 2023, 42(S1): 529-535.
[7]	陈林, 徐培渊, 张晓慧, 陈杰, 徐振军, 陈嘉祥, 密晓光, 冯永昌, 梅德清. 液化天然气绕管式换热器壳侧混合工质流动及传热特性[J]. 化工进展, 2023, 42(9): 4496-4503.
[8]	张帆, 陶少辉, 陈玉石, 项曙光. 基于改进恒热传输模型的精馏模拟初始化[J]. 化工进展, 2023, 42(9): 4550-4558.
[9]	雷伟, 姜维佳, 王玉高, 和明豪, 申峻. N、S共掺杂煤基碳量子点的电化学氧化法制备及用于Fe³⁺检测[J]. 化工进展, 2023, 42(9): 4799-4807.
[10]	王晨, 白浩良, 康雪. 大功率UV-LED散热与纳米TiO₂光催化酸性红26耦合系统性能[J]. 化工进展, 2023, 42(9): 4905-4916.
[11]	王琦, 寇丽红, 王冠宇, 王吉坤, 刘敏, 李兰廷, 王昊. 焦化废水生物出水中可溶解性有机物的分子识别[J]. 化工进展, 2023, 42(9): 4984-4993.
[12]	史天茜, 石永辉, 武新颖, 张益豪, 秦哲, 赵春霞, 路达. Fe²⁺对厌氧氨氧化EGSB反应器运行性能的影响[J]. 化工进展, 2023, 42(9): 5003-5010.
[13]	张振, 李丹, 陈辰, 吴菁岚, 应汉杰, 乔浩. 吸附树脂对唾液酸的分离纯化[J]. 化工进展, 2023, 42(8): 4153-4158.
[14]	张智琛, 朱云峰, 成卫戍, 马守涛, 姜杰, 孙冰, 周子辰, 徐伟. 高压聚乙烯失控分解研究进展：反应机理、引发体系与模型[J]. 化工进展, 2023, 42(8): 3979-3989.
[15]	王耀刚, 韩子姗, 高嘉辰, 王新宇, 李思琪, 杨全红, 翁哲. 铜基催化剂电还原二氧化碳选择性的调控策略[J]. 化工进展, 2023, 42(8): 4043-4057.