This review examines fabrication techniques and challenges of solid-state polymer electrolytes, highlighting machine learning's role in optimization.
Solid‐state electrochemical energy storage (EES) devices are gaining prominence due to their superior safety, energy density, and sustainability compared to conventional liquid electrolyte systems. Solid‐state polymer electrolytes (SSPEs) are central to this advancement, offering not only enhanced structural integrity and mechanical flexibility but also the potential for optimized ionic transport pathways. This review systematically examines the major fabrication techniques for SSPEs, including solution casting, hot pressing, melt processing, spin coating, and 3D printing, with a particular emphasis on solvent‐free and environmentally benign strategies. The discussion highlights how fabrication parameters govern polymer chain mobility, morphology, and segmental dynamics, directly influencing ionic conductivity and device performance. Key challenges such as residual solvents, non‐uniform film morphology, and a lack of processing standardization are critically analyzed. Furthermore, emerging strategies, including the integration of machine learning (ML) and computational modeling, are identified as promising tools to accelerate process optimization and establish reliable structure–property–performance relationships. This review provides a comprehensive framework for advancing scalable and sustainable SSPE fabrication tailored for next‐generation all‐solid‐state batteries and flexible EES technologies.
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Fuzlin et al. (2025) studied this question.
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