Key research themes
1. How are thermophysical properties of materials modeled and measured, especially thermal conductivity, specific heat, and thermal diffusivity?
This theme focuses on advancements in methodologies for determining thermophysical properties through modeling, experimental measurements, and analytical computations. Accurate knowledge of these properties is vital for material design, heat transfer calculations, and process optimization across a range of materials, including composites, foods, and industrial fluids.
2. How can temperature dependence of thermophysical properties of solids and liquids be theoretically described and accurately predicted?
This research theme investigates the temperature-dependent behavior of thermophysical parameters such as thermal expansion and heat capacity in solids and liquids. The aim is to develop physically consistent, often semi-empirical or theoretical, equations that extend predictive capabilities beyond experimental temperature ranges, especially for applications involving extreme temperatures.
3. How can machine learning improve the prediction of complex thermophysical properties such as viscosity in advanced nanofluids?
This theme explores the application of supervised ML algorithms to predict nonlinear rheological behaviors of nanofluids, focusing on improving accuracy beyond traditional empirical or theoretical models. Such predictions aid in optimizing heat transfer performance and understanding flow characteristics critical for industrial and biomedical applications.