Scientific Highlights

John Provis is studying concrete and the complex interplay between its many components. The aim is to develop a better understanding of this building material and make it more sustainable. © Paul Scherrer Institute PSI/Mahir Dzambegovic

Prasianakis, N. I., et al.

Thanks to the recent progress in numerical methods and computer technology, the application fields of artificial intelligence (AI) and machine learning methods (ML) are growing at a very fast pace. The field of geochemistry for nuclear waste management has recently started using ML for the acceleration of numerical simulations of reactive transport processes, for the improvement of multiscale and multiphysics couplings efficiency, and for uncertainty quantification and sensitivity analysis......

Even as a student, Athanasios Mokos was excited by the dynamics of fluids. Today at the Paul Scherrer Institute PSI, he models complex processes such as the formation of deposits on reactor fuel rods.

Researchers at the Paul Scherrer Institute PSI have shown that artificial neural networks have the potential to determine very precisely the characteristics of rock layers, like their mineralogical composition, solely on the basis of drill core images. This could speed up future geological investigation efforts while simultaneously optimising costs.

Zeolites are a class of shapely, colourful minerals with very special properties, making them omnipresent in our surroundings. They accelerate chemical reactions, absorb hazardous contaminants and water to a high degree, for example. Their only limitation is that they usually lose their peculiar crystalline structure at high temperatures. Now researchers at the University of Bern have found an unexpected exception.

Yanting Qian has received the MSc/PhD competition award in the FISA2022-EURADWASTE'22 conference. She works on the retention of redox-sensitive Tc on Fe-bearing clay minerals.

Water boiling control evolution of natural geothermal systems is widely exploited in industrial processes due to the unique non-linear thermophysical behavior. Even though the properties of water both in the liquid and gas state have been extensively studied experimentally and by numerical simulations, there is still a fundamental knowledge gap in understanding the mechanism of the heterogeneous nucleate boiling controlling evaporation and condensation. In this study, the molecular mechanism of bubble nucleation at the hydrophilic and hydrophobic solid–water interface was determined by performing unbiased molecular dynamics simulations using the transition path sampling scheme. Analyzing the liquid to vapor transition path, the initiation of small void cavities (vapor bubbles nuclei) and their subsequent merging mechanism, leading to successively growing vacuum domains (vapor phase), has been elucidated. The simulations reveal the impact of the surface functionality on the adsorbed thin water molecules film structuring and the location of high probability nucleation sites.