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Statistical uncertainty quantification to augment CDI electrode design and operation optimization
Chemical Engineering Journal ( IF 15.1 ) Pub Date : 2023-06-01 , DOI: 10.1016/j.cej.2023.143825
Yunfeng Mao , Shunnan Long , Xingyu Kuai , Longqian Xu , Hua Zhang , Weidong Wu , Deli Wu

Capacitive deionization (CDI) is considered to be one of the most promising technologies to deionize water with low/medium concentration. Great attention has been paid to improve its performance by optimizing electrode architectures and operation conditions. However, no guidelines are built for developing such strategies due to the nonlinear impact of the parameters concerning electrodes and operations. Therefore, our work quantitatively reveals the influence of some key parameters involving electrode characteristics, operation conditions and ion properties using the statistical analysis based on uncertainty quantification. We find the porosity solely has a small influence on all the performance metrics. But the pore might play a significant role by the pore size distribution and connectivity that greatly determine the effective diffusion coefficient of salt ions. The high diffusion coefficient obviously raises the salt adsorption by facilitating ion transport, which also reduces the energy consumption while most of the consumed energy could even be recovered. The current exerts an opposite influence by shortening the charging period in the constant current (CC) mode. The salt concentration in the inflow water increases the adsorption capacity but decreases the removal efficiency. The decreased removal efficiency requires less external energy, enabling the usage of CDI as an economic pre-treatment unit. We highlight the ion transport resistance and its influence on CDI performance by acting upon charging time in the CC mode. We also suggest the application of the constant voltage mode to the low-salinity wastewater instead of the CC mode due to the high resistance. Our work addressed the importance of proper electrode and operation condition for high desalination performance and energy efficiency.



中文翻译:

统计不确定性量化以增强 CDI 电极设计和操作优化

电容去离子(CDI)被认为是最有前途的低/中浓度水去离子技术之一。通过优化电极结构和操作条件来提高其性能得到了极大的关注。然而,由于有关电极和操作的参数的非线性影响,没有为开发此类策略制定指南。因此,我们的工作使用基于不确定性量化的统计分析,定量揭示了电极特性、操作条件和离子特性等一些关键参数的影响。我们发现孔隙率对所有性能指标的影响很小。但孔隙可能通过孔径分布和连通性发挥重要作用,这极大地决定了盐离子的有效扩散系数。高扩散系数通过促进离子传输明显提高了盐的吸附,这也降低了能量消耗,而且大部分消耗的能量甚至可以回收。通过缩短恒流 (CC) 模式下的充电时间,电流会产生相反的影响。流入水中的盐浓度增加了吸附能力但降低了去除效率。降低的去除效率需要更少的外部能量,使 CDI 成为一种经济的预处理装置。我们通过作用于 CC 模式下的充电时间来强调离子传输阻力及其对 CDI 性能的影响。由于高电阻,我们还建议将恒压模式应用于低盐度废水,而不是 CC 模式。我们的工作解决了适当电极和操作条件对于高脱盐性能和能源效率的重要性。

更新日期:2023-06-06
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