The present paper describes ways of increasing the accuracy of measurements of thermophysical properties (namely, thermal diffusivity) of materials. The knowledge of these characteristics is very important for modeling industrial processes, since their high-accuracy determination can reduce wasteful consumption of energy resources while developing novel thermal insulation materials, technologies, as well as methods for building construction.The method proposed herein is based on periodic heating and can be used to improve the measurement accuracy and find the optimal parameters for producing thermal insulation materials. Periodic temperature oscillations were generated by means of the Peltier element. Mathematical and physical models were developed, and the measurement setup was automated using the LabView graphical programming environment. The analysis of possible error sources was performed, and the ways of decreasing error values were suggested.The equipment was experimentally calibrated using a standard material (Plexiglas), and the obtained data proved the appropriateness of the developed mathematical model. Moreover, a number of tests were performed with a nanomaterial, namely, graphene nanoplatelets (GNPs). The proposed method and the experimental measurement setup made it possible to reveal a strong dependence between the thermal diffusivity of the GNPs and the moisture content. This finding will be considered in further studies concerning the above-mentioned nanomaterial.
KeywordsPeriodic heating; thermal insulation materials; graphene nanoplatelets (GNPs); thermal diffusivity; measurement error. oscillations; ADC Δ -random error introduced by the data acquisition board; U inp -input voltage range for the analog-todigital converter, mV; n -resolution of the analog-to-digital converter; emf Δ -disturbance caused by external magnetic fields.