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Earth Sciences at the University of Fribourg

Bern-Fribourg Master in Earth Sciences


Details of Master Thesis Topic (Module D):
Advanced pore scale geochemical modelling using machine learning algorithm

Master Thesis title: Advanced pore scale geochemical modelling using machine learning algorithm
Description:Modern experimental studies of geochemical processes in natural rocks and technological application for nanoparticle synthesis and pharmaceutics often rely on microfluidic reactors and lab-on-a-chip experimental devices. In a typical microfluidic setup, a large variety of crystal types nucleate and grow simultaneously. The crystal characteristics: shape, morphology, chemical composition, crystallographic information and material properties, typically depend on a number of parameters including the involved chemical reactants, their relative concentration, the presence of secondary ions in trace concentrations or even the pore-size, when precipitation takes place within a porous medium. Machine learning algorithms will be used to automate the classification of reaction products, aiming in a fast on-line data analysis and feedback on for the on-fly steering of experimental conditions. Focus of the simulations and model development will be on precipitation experiments on going at the large scale Synchrotron facilities at Paul Scherrer Institute (PSI, www.psi.ch). The student will have a unique opportunity to get in touch with Synchrotron experimentally facilities of the largest research institute in Switzerland(PSI), become proficient in most advanced geochemical modelling methods and get insight into the methods of artificial intelligence.

In collaboration with Dr. Nikolaos Prasianakis and PD. Georg Kosakowski (Paul Scherrer Institute, www.psi.ch/les)
Advisors:Prof. Sergey Churakov
Specialities:EM, ERG
University: BE

University of Bern | Institute of Geological Sciences | Baltzerstrasse 1+3 | CH-3012 Bern |
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University of Fribourg | Dépt. Géosciences ; Ch. du Musée 6 - Pérolles ; CH-1700 Fribourg |
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