A pythagorean fuzzy decision-making framework for prioritizing performance enhancement strategies of metal–organic frameworks in liquid hydrogen energy systems

• A new Pythagorean fuzzy SIWEC–COPRAS decision model is developed. • Critical criteria for MOF based liquid hydrogen systems are identified. • Boil off gas reduction and life cycle cost are the most important factors. • MOF–polymer composite storage is the top ranked strategy. • The model offers robust and uncertainty aware decision support. The performance enhancement of metal–organic frameworks (MOFs) in liquid hydrogen energy storage and conversion systems represents a critical challenge due to the complex interaction of technical, economic, environmental, and operational factors under high uncertainty. Although a considerable body of research has examined MOF-based hydrogen storage from various technical and material perspectives, many of these studies primarily focus on material-level performance indicators. While these contributions provide valuable insights into adsorption capacity, structural design, and physicochemical properties, relatively fewer studies offer integrated analytical frameworks capable of simultaneously evaluating the technical, economic, environmental, and operational dimensions of MOF performance while supporting strategic prioritization under uncertainty. The aim of this study is to fill this gap by developing a comprehensive fuzzy decision-making framework to identify the most prioritized strategies for improving MOF-based liquid hydrogen systems. To achieve this, a novel model integrating Pythagorean fuzzy sets with the Stepwise Importance Weight Assessment Coefficient (SIWEC) and Complex Proportional Assessment (COPRAS) methods is proposed, enabling robust criteria weighting and proportional ranking of strategic alternatives under uncertainty. The results reveal that boil-off gas reduction and life cycle cost are the most influential criteria, while MOF–polymer composite storage and cryogenic MOF hydrogen storage systems emerge as the most effective strategies. The proposed model contributes to the literature by offering a transparent, flexible, and uncertainty-aware analytical tool with superior expressive power and robustness. The findings suggest that policy and investment efforts should prioritize composite material designs and cryogenic optimization strategies to enhance efficiency, sustainability, and scalability in liquid hydrogen energy applications.