Abstract
Reverse electrodialysis (RED) has emerged as a promising technology for harvesting salinity gradient energy (SGE), offering a sustainable solution to global energy challenges. This review systematically examines the critical role of solution environments, including salinity gradients, temperature, pH, ion species, and nanochannel surface properties, in governing RED performance. By integrating nanoscale ion transport mechanisms with macroscopic system optimization, we highlight how operating conditions influence key metrics such as power density, energy conversion efficiency, and ion selectivity. Special emphasis is placed on the interplay between electric double layer (EDL) dynamics, nanochannel geometry, and multi-parameter coupling effects (e.g., temperature-salinity-pH synergies). Advanced strategies, such as surface charge modulation, asymmetric nanochannel design, and machine learning (ML) -driven optimization, are discussed to address challenges like selectivity-permeability trade-offs and multivalent ion interference. The review also identifies future research directions, including molecular-scale validation and adaptive operation strategies for real-world applications. This work aims to bridge the gap between fundamental research and practical implementation, providing actionable insights for enhancing RED technology in renewable energy and desalination systems.