Multi-objective optimisation for integrated CO2 capture and utilisation using dual-function materials

Dual-function materials (DFMs) provide an intensified route for integrated CO 2 capture and utilisation (ICCU), yet their performance at industrial scale remains largely unexplored owing to the lack of systematic proce2ss optimisation. This study develops a robust, open-source framework for the multi-objective optimisation of a DFM-based ICCU reactor operating at cyclic steady state (CSS). A detailed one-dimensional model of a NiRu–Ca/Al DFM, incorporating full mass, energy, and momentum balances, was developed. To enhance computational efficiency, a reduced surrogate model was integrated with a Bayesian-based multi-objective optimisation framework (Optuna–NSGA-II), enabling the systematic identification of optimal operating strategies and construction of Pareto fronts that capture the trade-offs among methane purity, productivity, and CO 2 recovery. The optimisation framework characterises the trade-off between productivity, purity, and recovery, providing a quantitative basis for selecting operating conditions. Gas flow rate and hydrogenation duration were identified as the dominant operational levers. The developed framework establishes a reproducible and physically grounded basis for future techno-economic analysis and the scalable design of DFM-based ICCU systems at industrial scale.