NanoTherm Research Group

Our group develops physics-informed AI methods for thermal and interfacial transport problems. Recent work uses physics-informed neural networks and topology optimization to model thin-film evaporation in hierarchical porous structures, where heat transfer, capillarity, evaporation, and geometry are strongly coupled.

These approaches combine governing equations with data-driven learning so that predictions remain connected to conservation laws and transport physics. Current directions include PINN-guided design of porous hierarchical structures for extreme thin-film evaporation, physics-informed topology optimization, and predictive AI models for evaporation in complex structures.

Ice formation and frost growth are governed by coupled heat transfer, nucleation, phase change, and surface interactions. Our research examines how water freezes on surfaces, how ice adheres to different materials, and how surface structure and mechanics can be used to reduce ice accumulation or promote ice shedding.

Related publications include studies of ice nucleation and growth on surfaces, predictive models of ice adhesion, fracture-controlled ice-shedding surfaces, and magnetic slippery icephobic surfaces. This work connects surface physics with practical problems in anti-icing, de-icing, and frost management.

Solar energy is one of the renewable energy resources with hourly incident solar flux on earth surface greater than the global energy consumption in a year. Photo-thermal applications for harvesting solar energy currently suffer from low efficiency and require high concentration of sunlight, which adds complexity and cost to the solar energy harvesting systems.

In solar-thermal systems, high conversion efficiency is in significant demand. Localization of heat is a promising approach to achieve these high efficiencies. The localization of heat leads to locally elevated temperature while minimizing dissipated energy. This localization can be incorporated in all forms of phase-change processes, including evaporation, boiling, condensation, and freezing.

In early research in this field, scientists utilized plasmonic nanoparticles to reach locally elevated temperatures for a broad range of applications. There is a significant unexplored gap in fundamental understanding of this localization. The key challenge for increasing efficiency is the design of material structures for energy conversion. Through heat localization, we developed a material structure leading to solar steam generation at low optical concentration with an efficiency of 85%. This high efficiency is reached by a combination of properties in the developed material structures and supports highly efficient solar-assisted phase-change phenomena.

During liquid-to-vapor transformation, phase change occurs at an interface with a thickness of only a few nanometers, comparable to several molecular lengths. In this region, molecular density, interfacial transport, and thermodynamic properties can differ significantly from bulk phases.

Our work studies the physics of liquid-vapor transformation at small scales, with emphasis on evaporation, thin films, nano/molecular confinement, and heat-fluid-surface interactions. We combine modeling, simulation, and experiments to understand how interfaces control energy transport and how this understanding can improve thermal systems.