Preprint for publication: "Assessment of the Thermal Conductivity of Internally Intricate 3D Printed Structures with Gyroid- and Other Cell-Based Geometries"

The utilisation of thermal insulation and the reduction of heat transfer rates are essential tasks in many applications and systems across all areas of engineering. Very frequently, a primary effort is to minimise heat losses, resulting in higher efficiency, lower energy consumption, and a smaller ecological footprint. A common technique is to use conventional insulation materials with low thermal conductivity, such as polystyrene and polyurethane foams, or rock wool. All these materials employ the principle of small air-trapped cells, since air is an excellent thermal insulator. In this context, 3D printing enables the additive manufacturing of structures with intricate internal geometry having similar small air-trapped cells. However, additively manufactured structures with complex internal geometries exhibit strongly structure-dependent thermal behaviour. The paper focuses on experimental evaluation of the effective thermal conductivity of additively manufactured specimens from two of the most widely used thermoplastics, PLA and PETG, containing enclosed infill structures of various geometries and densities. Measurements were performed using a steady-state plate calorimeter with calibration-based correction of parasitic heat losses. A reference XPS specimen was used to determine the calorimeter conductance constant and to assess repeatability and accuracy of the measurements. The experimental apparatus ensured a stable specimen temperature distribution and low measurement uncertainty. The effective thermal conductivity ranged from approximately 0.050 W/(m·K) for a low-density gyroid infill to 0.089 W/(m·K) for specimens with the highest infill density. Among the tested infill geometries and densities, the gyroid structure exhibited one of the lowest thermal conductivities. The results demonstrate a significant influence of internal structure on heat conduction in additively manufactured parts and provide the experimentally validated data for thermally optimized component design.