Thesis supervisor: Béla Fiser
Location of studies (in Hungarian): Miskolci Egyetem, Kémia Intézet-FIEK Abbreviation of location of studies: AVK
Description of the research topic:
Polyurethanes (PU) are used in a range of various products (e.g. furniture). The physical and chemical properties of polyurethane-based products can be fine-tuned by using different additives (e.g. antioxidants). However, the development of new synthetic recipes to prepare better materials is usually based on trial-and-error cycles and thus, the process is expensive (time and material intensive). The development process can be accelerated by using machine learning (ML) algorithms. Therefore, the current project will combine the strength of experimental and computational tools to achieve new polyurethane types.