Curriculum Vitae:
My current research focuses on the numerical modelling of mixing-controlled precipitation of organic nanoparticulate compounds, which is in in direct cooperation with experiments (H. Trzenschiok ,LFG). Most accurate numerical methods across the entire spectrum are applied to model the coupling between fluid flow and particle formation assumption-free in order to forecast the precipiptation of organic matter in a predictive way.
- WS 08/09 – SS12 Bachelor of Science, Mechanical Engineering, FAU
- WS 12/13 – SS14 Master of Science, Mechanical Engineering, FAU
- 31. Nov 2014 – 31. Dec 2017, Institute of Fluid Mechanics, FAU
- since 1. Jan 2018, Institute of Particle Technology, FAU
Selected Publications:
A full list can be found here.
- Wang, Z., Traoré, N.E., Schikarski, T., Stiegler, L., Drobek, D., Zubiri, B.A.,... Segets, D. (2023). Population balance modeling of InP quantum dots: Experimentally enabled global optimization to identify unknown material parameters. Chemical Engineering Science, 281. https://dx.doi.org/10.1016/j.ces.2023.119062
- Biegel, M., Schikarski, T., Cardenas Lopez, P., Gromotka, L., Lübbert, C., Völkl, A.,... Peukert, W. (2023). Efficient quenching sheds light on early stages of gold nanoparticle formation. RSC Advances, 13(26), 18001-18013. https://dx.doi.org/10.1039/d3ra02195e
- Schikarski, T., Trzenschiok, H., Avila, M., & Peukert, W. (2023). Impact of solvent properties on the precipitation of active pharmaceutical ingredients. Powder Technology, 415. https://dx.doi.org/10.1016/j.powtec.2022.118032
- Bänsch, E., Pflug, L., & Schikarski, T. (2023). Highly accurate and numerical tractable coupling of nanoparticle nucleation, growth and fluid flow. Chemical Engineering Research & Design, 190, 814-828. https://dx.doi.org/10.1016/j.cherd.2022.12.029
- Schikarski, T., Avila, M., Trzenschiok, H., Güldenpfennig, A., & Peukert, W. (2022). Quantitative modeling of precipitation processes. Chemical Engineering Journal, 444. https://dx.doi.org/10.1016/j.cej.2022.136195
