Employing Computational-Mathematical Techniques for Optimizing Cold Spray Deposition Efficiency

The integration of 2D (nano)materials with a metallic matrix offers enhanced thermal and electrical conductivity, alongside improved mechanical strength and stability on larger scales. This advantageous combination of properties has garnered increasing attention toward 2DMMCs. Graphene and boron nitride are among the most commonly used 2D materials, often incorporated into a copper matrix to further enhance its inherent thermal and electrical conductivity.

In this study, we propose cold spray as a viable method for depositing Gr-Cu 2DMMCs, aiming to preserve the integrity of the components while achieving desirable properties. We briefly discuss the process parameter selection. Then, we proceed to analyze the most significant structural and mechanical properties of the achieved coating, such as porosity, hardness, adhesion and tensile strength.

The results offer valuable insights into how 2D material content influences the efficiency of cold spray deposition in 2DMMCs compared to pure metallic feedstock. Analyzing these findings can aid in more clearly identifying the optimal 2DMMC composition needed to achieve a balanced set of thermo-mechanical properties when using cold spray deposition.