A deep understanding of the thermodynamics of immiscible liquid mixtures (i.e., liquid-liquid mixtures with a large difference in molar mass) opens up the possibility of building innovative, energy-efficient machines for refrigeration, air conditioning, heating, and energy technology. Unfortunately, the data needed to gain these insights is scattered all over the internet. With the help of AI tools, we’ll work with you to find ways to catalog and digitize it.

Using AI tools, you will search the Internet for diagrams based on specified criteria, digitize them, and develop an architecture for storing them. In subsequent work, this will serve as the basis for a fluid data engine designed to calculate and predict liquid-liquid immiscible mixtures.

Basic knowledge of the physics and chemistry of liquid mixtures (e.g., the difference between oil droplets on water, water-oil emulsions, and alcohol in water) and their properties, such as viscosity, solubility, vapor pressure, heat capacity, etc. Basic programming skills using common programming environments, ideally including databases. Interest in working with AI tools and the digitization of thermodynamic diagrams.

Since our internships and the supervision of student projects are primarily intended to provide practical experience and career guidance, we ask for your understanding that no compensation is provided. However, we would be happy to issue you a formal internship certificate and nominate your student project for the annual academic award presented by the Association for the Promotion of Air Conditioning and Refrigeration Technology (Verein zur Förderung der Luft- und Kältetechnik e.V.).