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In adsorption heat pumps, the properties of the porous adsorbent and the refrigerant determine the performance. Major parameters for this working pair are the total uptake of the adsorptive, its kinetics, and the heat transfer characteristics. In the technical application despite powdered adsorbents, thin consolidated layers of the adsorbent can be attractive and obtained by a binder‐based approach but likely result in competing material properties. Thus, for a process optimization, the accessible parameter space and interdependencies have to be known and were deduced in this work for model porous carbons (carbide‐derived carbons derived from TiC and ZrC) and methanol as well as the addition of different amounts of boron nitride, silver, and graphite as heat‐conductive agents and the use of two binders.

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In process engineering, optimization is usually carried out without the simultaneous consideration of material and process. This issue is addressed in the following contribution. A model-based optimization is presented to improve the performance of adsorption heat pumps. Optimization is carried out in two steps. First, we optimize the operational parameters, the cycle time, and the thickness of the adsorbent for a given adsorption material. In a second step we use a material model to predict heat and mass transfer and adsorption capacity from structural material parameters. This allows us to vary the structural material parameters and calculate the optimal operational parameters for each adsorbent. The two-step optimization thus identifies optimal material properties together with corresponding optimal operational parameters. As constraints, a minimum specific cooling power (SCP) and the passive mass of heat transfer pipes are used. The coefficient of performance (COP) is taken as the objective function. We exemplarily demonstrate the approach for a two-bed adsorption chiller, carbide-derived carbon as the adsorbent, methanol as the sorptive and boron-nitrate as additive to improve heat conductivity. The approach can be easily extended to multi-bed installations and more sophisticated material models.