Insight into Aqueous Phase

Understanding complex aqueous systems Water remains the most fascinating liquid in our world. It is not only the “elixir of life”, but its understanding is also crucial to tackle some of the most pressing societal challenges of our time, such as climate change, ocean accidification, and clean water supply. In our research, we follow a […]

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Towards Converged Interactions

Reaching Coupled Cluster Accuracy The potential energy surface (PES) of a system, which governs all its structural, dynamic and thermodynamic properties in the Born-Oppenheimer approximation, is currently in many cases best described by coupled cluster theory. This has granted the CCDS(T) approach the title of the “gold standard” in quantum chemistry. Thus, it is desirable […]

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Machine Learning Potentials

Learning structure-energy relations Machine learning in computational chemistry has emerged as an indispensable driving force for innovation. By combining the low cost of traditional empirical potentials with the accuracy of ab initio methods, machine learning potentials deliver long time and large length scales required for insight into complex molecular systems. Instead of physically motivated forms […]

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