Surfactants, are chemical compounds affecting the interfacial properties between two phases, whether this interface is liquid-gas, liquid-solid, or liquid-liquid. In the semiconductor manufacturing industry, surfactants play an essential and multifaceted role in processes that demand precise control of surface and interfacial phenomena. Despite their importance, the rational design and selection of surfactants for semiconductor applications remain challenging. The vast chemical space and complex interfacial behavior of these compounds complicate both experimental characterization and predictive modeling. As a key step in the computational design of surfactant molecules, we aim to enhance an existing database ( https://pubs.rsc.org/en/content/articlelanding/2025/dd/d4dd00393d ) by computing relevant MD properties and training a regression model for surfactant property prediction on this database. To this end, we plan on running GROMACS simulations covering a wide variety of properties such as diffusion coefficients, surface tension, and viscosity characterising surfactant behaviour. All simulations are well established and can be carried out within two month on a small allocation. The database contains a total of 1600 molecules of which we have simulated 1300 already. The necessary scripts are completed and I intend to run each trajectory for 50,000,000 steps, corresponding to 10 ns of simulation time.