Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, USA.
Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.
Water Res. 2018 Feb 1;129:327-336. doi: 10.1016/j.watres.2017.11.025. Epub 2017 Nov 11.
Here we detail a previously unappreciated loss mechanism inherent to capacitive deionization (CDI) cycling operation that has a substantial role determining performance. This mechanism reflects the fact that desalinated water inside a cell is partially lost to re-salination if desorption is carried out immediately after adsorption. We describe such effects by a parameter called the flow efficiency, and show that this efficiency is distinct from and yet multiplicative with other highly-studied adsorption efficiencies. Flow losses can be minimized by flowing more feed solution through the cell during desalination; however, this also results in less effluent concentration reduction. While the rationale outlined here is applicable to all CDI cell architectures that rely on cycling, we validate our model with a flow-through electrode CDI device operated in constant-current mode. We find excellent agreement between flow efficiency model predictions and experimental results, thus giving researchers simple equations by which they can estimate this distinct loss process for their operation.
在这里，我们详细介绍了以前未被重视的电容去离子（CDI）循环操作中的固有损耗机制，该机制在确定性能方面起着重要作用。该机制反映了一个事实，即在吸附后立即进行解吸，如果脱附，那么电池内的淡化水会部分损失而重新盐化。我们通过一个称为流量效率的参数来描述这种影响，并表明该效率与其他经过深入研究的吸附效率不同，但可以与其他效率相乘。通过在脱盐过程中使更多的进料溶液流过电池，可以最小化流量损失；但是，这也会导致流出物浓度降低更少。虽然这里概述的基本原理适用于所有依赖于循环的 CDI 电池结构，但我们使用在恒流模式下运行的流通式电极 CDI 设备对我们的模型进行了验证。我们发现流量效率模型预测与实验结果之间具有极好的一致性，从而为研究人员提供了简单的方程式，使他们可以估算出这种独特的损耗过程。
