Open AccessLangmuir-Based Modeling Produces Steady Two-Dimensional Simulations of Capacitive Deionization via Relaxed Adsorption-Flow Coupling
Author(s) -
Johan Nordstrand,
Joydeep Dutta
Publication year - 2022
Publication title -
langmuir
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.042
H-Index - 333
eISSN - 1520-5827
pISSN - 0743-7463
DOI - 10.1021/acs.langmuir.1c02806
Subject(s) - capacitive deionization , langmuir , multiscale modeling , computer science , coupling (piping) , desalination , scale (ratio) , flow (mathematics) , stability (learning theory) , computation , adsorption , process engineering , nanotechnology , biological system , materials science , mechanics , chemistry , algorithm , physics , engineering , computational chemistry , machine learning , biochemistry , quantum mechanics , membrane , metallurgy , biology
The growing world population creates an ever-increasing demand for fresh drinkable water, and many researchers have discovered the emerging capacitive deionization (CDI) technique to be highly promising for desalination. Traditional modeling of CDI has focused on charge storage in electrical double layers, but recent studies have presented a dynamic Langmuir (DL) approach as a simple and stable alternative. We here demonstrate, for the first time, that a Langmuir-based approach can simulate CDI in multiple dimensions. This provides a new perspective of different physical pictures that could be used to describe the detailed CDI processes. As CDI emerges, effective modeling of large-scale and pilot CDI modules is becoming increasingly important, but such a modeling could also be especially complex. Leveraging the stability of the DL model, we propose an alternative fundamental approach based on relaxed adsorption-flow computations that can dissolve these complexity barriers. Literature data extensively validate the findings, which show how the Langmuir-based approach can simulate and predict how key changes in operational and structural conditions affect the CDI performance. Crucially, the method is tractable for simple simulations of large-scale and structurally complex systems. Put together, this work presents new avenues for approaching the challenges in modeling CDI.