Author
Listed:
- Zhang, Nianchun
- Chen, Hao
Abstract
Multistage reverse electrodialysis (MS-RED) is an efficient technology for harvesting salinity gradient energy. Although multiphysics modeling is essential to elucidate the power generation mechanism, full-scale simulations are prohibitive with conventional computational resources. Herein, we propose an analytical and cyclic boundaries modeling method and develop a multiphysics model coupling flow, concentration, and electric fields for MS-RED. This model adopts a cell-pair unit as the computational domain, where flow boundaries are determined analytically by flow conservation and the outlet concentrations are cyclically assigned as the inlet concentrations for the next computational steps, achieving global prediction with less than 3% average error without simulating the entire system. Based on this, the global evolution of flow, ion transport, electrical behavior, and interstage performance is analyzed, and the influences of key parameters on MS-RED performance are investigated, yielding engineering implications to advance deployment. Spacer filaments force ionic current to detour and induce flow stagnation zones, leading to stage-wise intensified localized concentration polarization and pressure perturbations. The concentration gradient and cell-pair number are the crucial factors governing interstage performance. Increasing stage number or channel length introduces a trade-off between power density and energy performance, making large-scale systems more suitable for high salinity gradients. An optimal low flow window exists, allowing performance tuning for diverse water source conditions and power supply requirements. This work develops a novel modeling method, providing a comprehensive analysis and design tool for MS-RED.
Suggested Citation
Zhang, Nianchun & Chen, Hao, 2026.
"Multistage reverse electrodialysis for efficient salinity gradient energy harvesting: Global multiphysics analysis from a unit domain,"
Energy, Elsevier, vol. 358(C).
Handle:
RePEc:eee:energy:v:358:y:2026:i:c:s0360544226015008
DOI: 10.1016/j.energy.2026.141394
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