Simulating the coupled electronic and nuclear response of a molecule to light excitation requires the application of nonadiabatic molecular dynamics. However, when faced with a specific photophysical or photochemical problem, selecting the most suitable th ...
With the advancement of high harmonic generation and X-ray free-electron lasers (XFELs) to the attosecond domain, the studies of the ultrafast electron and spin dynamics became possible. Yet, the methods for efficient control and measurement of the quantum ...
Over the past decade, computational atomistic modeling, driven by machine learning (ML), has become indispensable to scientific endeavors, improving our understanding and accelerating the search for compounds with enhanced properties. Traditional atomistic ...
The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of density functional theory (DFT). However, running large simulation cells with DFT is computationally demanding, wh ...
Hydrogen hydrates exhibit a rich phase diagram influenced by both pressure and temperature, with the so-called C2 phase emerging prominently above 2.5 GPa. In this phase, hydrogen molecules are densely packed within a cubic icelike lattice and the interact ...
The human colon hosts hundreds of commensal bacterial species, many of which ferment complex dietary carbohydrates. To transform these fibers into metabolically accessible compounds, microbes often express a series of dedicated enzymes homologous to the st ...
The increasing demand for precision, reproducibility, and scalability in scientific research has driven the development of advanced robotic systems for laboratory automation. This thesis presents the design, implementation, and validation of a mobile robot ...
Deep learning methods outperform human capabilities in pattern recognition and data processing problems and now have an increasingly important role in scientific discovery. A key application of machine learning in molecular science is to learn potential en ...
Motivated by the need to perform large-scale kinetic Monte Carlo (KMC) simulations, in the context of unravelling complex phenomena such as catalyst reconstruction and pattern formation, we extend the work of Ravipati et al. [S. Ravipati, G. D. Savva, I.-A ...
Supported palladium catalysts are the most active ones toward the complete oxidation of methane. However, the presence of relevant amounts of water hinders the catalytic activity and long-term stability, due to competition between methane and water for the ...
