Multi-Criteria Evaluation of Materials for Acoustic and Electromagnetic Wave Attenuation Applications

The increasing integration of acoustic and electromagnetic phenomena in modern sensing systems poses a significant challenge for material selection, as optimal performance in one domain may conflict with requirements in another. This study proposes a unified multicriteria framework for material selection in multiphysics sensing environments, based on the combined analysis of acoustic impedance, electromagnetic properties, and practical engineering constraints. The methodology integrates the Analytic Hierarchy Process (AHP) for criteria weighting with multiple multicriteria decision-making (MCDM) methods, including COPRAS, VIKOR, TOPSIS, PROMETHEE, and WASPAS, applied to a heterogeneous dataset of materials spanning metals, polymers, composites, porous absorbers, and textiles. In addition to physical descriptors, the framework incorporates economic (cost) and safety-related criteria, enabling a more realistic and application-oriented evaluation. The results consistently identify highly absorptive materials, such as melamine and polyurethane foams, as the most suitable candidates under acoustically driven conditions. Composite materials emerge as robust compromise solutions, while materials with balanced profiles, such as textiles and common polymers, improve their relative position when practical constraints are considered. In contrast, highly specialized materials exhibit reduced performance due to imbalances across criteria. The consistency of the obtained rankings is assessed through Spearman rank correlation analysis, revealing a high level of agreement among the evaluated MCDM methods. Showing a very high level of agreement among methods (ρ = 0.95–1.00). Identical rankings are obtained for VIKOR, TOPSIS, and PROMETHEE (ρ = 1.00), while minor deviations observed in COPRAS and WASPAS reflect differences in aggregation behavior rather than inconsistencies in the decision problem. Overall, the proposed framework demonstrates that material selection in multiphysics systems should be approached as a scenario-based decision problem rather than a deterministic optimization task. By enabling the exploration of trade-offs between competing physical and engineering criteria, the methodology provides a transparent and extensible decision-support tool with potential applications in hybrid sensing platforms, non-destructive evaluation, and advanced wave-based systems.