Abstract

Access to and use of energy resources are now crucial components of modern human existence thanks to the exponential growth of technology. Traditional energy sources provide significant challenges, such as pollution, scarcity, and excessive prices. As a result, there is more need than ever before to replace depleting resources with brand-new, reliable, and environmentally friendly ones. With the aid of reverse electrodialysis, the salinity gradient between rivers and seawater as a clean supply with easy and infinite availability is a viable choice for energy generation. The development of nanofluidic-based reverse electrodialysis (NRED) as a novel high-efficiency technology is attributable to the progress of nanoscience. However, understanding the predominant mechanisms of this process at the nanoscale is necessary to develop and disseminate this technology. One viable option to gain insight into these systems while saving expenses is to employ simulation tools. In this study, we looked at how a layer-by-layer (LBL) soft layer influences ion transport and energy production in charged nanochannels. We solved the steady-state Poisson-Nernst-Planck (PNP) and Navier-Stokes (NS) equations for three different types of nanochannels with a trumpet geometry, where the narrow part is covered with a built-up LbL soft layer and the rest is a hard wall with a surface charge density of σ = -10, 0, or +10 mC/m2. The findings show that in type (I) nanochannels, at NPEL/NA = 100 mol/m3 and pH = 7, the maximum power output rises 675-fold as the concentration ratio rises from 10 to 1000. The results of this study can aid in a better understanding of energy harvesting processes using nanofluidic-based reverse electrodialysis in order to identify optimal conditions for the design of an intelligent route with great controllability and minimal pollution.

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