Nordstrand Johan, Dutta Joydeep
Functional Materials, Applied Physics Department, School of Engineering Sciences, KTH Royal Institute of Technology, AlbaNova universitetscentrum, 106 91 Stockholm, Sweden.
Langmuir. 2020 Jul 28;36(29):8476-8484. doi: 10.1021/acs.langmuir.0c00982. Epub 2020 Jul 15.
Lack of potable water in communities across the globe is a serious humanitarian problem promoting the desalination of saline water (seawater and brackish water) to meet the growing demands of human civilization. Multiple ionic species can be present in natural water sources in addition to sodium chloride, and capacitive deionization (CDI) is an upcoming technology with the potential to address these challenges because of its efficacy in removing charged species from water by electro-adsorption. In this work, we have investigated the effect of device operation on the preferential removal of different ionic species. A dynamic Langmuir (DL) model has been a starting point for deriving the theory, and the model predictions have been validated using data from reports in the literature. Crucially, we derive a simple relationship between the adsorption of different ionic species for short and long adsorption periods. This is leveraged to directly predict and enhance the selective ion removal in CDI. Furthermore, we demonstrate an example of how this selectivity could reduce excess removal of ions to avoid remineralization needs. In conclusion, the method could be valuable for predicting the impact of improved device operation on capacitive deionization with multi-ion compositions prevalent in natural water sources.
全球各地社区缺乏饮用水是一个严重的人道主义问题，这促使人们对咸水（海水和微咸水）进行淡化处理，以满足人类文明不断增长的需求。除氯化钠外，天然水源中还可能存在多种离子物种，而电容去离子化（CDI）是一项新兴技术，因其通过电吸附从水中去除带电物种的功效，有潜力应对这些挑战。在这项工作中，我们研究了设备运行对不同离子物种优先去除的影响。动态朗缪尔（DL）模型一直是推导该理论的起点，并且已使用文献报道中的数据对模型预测进行了验证。至关重要的是，我们得出了不同离子物种在短吸附期和长吸附期吸附之间的简单关系。这被用来直接预测和增强CDI中的选择性离子去除。此外，我们展示了一个例子，说明这种选择性如何减少离子的过度去除，以避免再矿化需求。总之，该方法对于预测改进的设备运行对天然水源中普遍存在的多离子组成的电容去离子化的影响可能是有价值的。
