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FRINATEK-Fri prosj.st. mat.,naturv.,tek

Reactive path Sampling using QuanTIS

Alternative title: Reactive Path Sampling using QuanTIS

Awarded: NOK 12.1 mill.

In this project we developed an approach that can be viewed as a dynamical equivalent of Quantum Mechanics-Molecular Mechanics (QM-MM). The method is based on path sampling using the Replica Exchange Transition Interface algorithm (RETIS). The proof of principle of our method QuanTIS got published in the high-standard quality journal Journal of Chemical Theory and Computation. Still, improvements of the approach are underway and to lay down the foundations of these improved algorithms, we developed an open-source Python library that facilitates these developments and makes the existing methodology accessible for a wide public. Last year we celebrated the official release of our open-source computer program PyRETIS (www.pyretis.org) which was accompanied with paper about the pyretis code in the Journal of Computational Chemistry. Also the very first RETIS study in for a solution chemistry process about silicate oligomerization got published in PCCP. Another big success regarding method development were the new Monte Carlo moves that we invented which make path sampling a factor 12 faster. The method was published in the prestigious Journal of Chemical Physics Letters. Another high-impact journal publication was our work on water splitting that got accepted in the Proceedings of the National Academy of Sciences (PNAS). Here we managed to reach a time scale of hours! with DFT-based molecular dynamics. An absolute record. Besides, we also applied a new analysis approach for identifying 'reaction triggers' using machine learning which showed that spontaneous anomalies in the hydrogen bond network lead to dissociation. Together with the scientist in Ghent we are further developing the QuanTIS method by automating force field parameters. The determination of partial charges is hereby and essential step. This work, let to a publication together with Prof. Verstraelen van de Ghent University about the determination of partial charges at doped graphene surfaces. Oda Dahlen delivered her thesis within the QuanTIS project. Anastasia Maslechko should be finishing as well in 2019 as she has one publication and material for 2 or 3 more. The direction of research will continue and we recently got a new PhD grant based on the discovery of Reaction Triggers with Machine Learning techniques. In addition, our open-source program PyRETIS will be be taught at a dedicated workshop in Leiden, the Netherlands, for which we received funding by the Lorentz center.

-12 publications have been published. Two of those in >9 Impact Factor journals (JCPL and PNAS) -1 PhD thesis completed within the period -1 PhD thesis underway -two post docs have been trained and got funding from RCN for projects in which they were active as PI's -Open-source computer code PyRETIS has been released -PhD school related to this code was granted by the Lorentz center and will be held in March 2019. So far 42 participants subscribed. -Our PNAS article got media attention from Gemini, but also internationally (C2W and Phys.org) -Established networks with Sintef and Ghent University

Molecular simulations are the ideal tool to obtain detailed information of the molecular scale which is often invisible for experiments. However, we are still far from a situation in which industries and pharmaceutical laboratories effectively design new materials and medicines based on molecular modelling. Present simulations techniques can not reach the required system- and length scales that are required for complex chemical and biological processes or are based on inaccurate oversimplified models whi ch make them unreliable. This research proposal aims to realize the ultimate dream of every researcher in the field of molecular modelling: running efficient and accurate quantum based dynamics of chemical reactions without the necessity to develop a new forcefield for each system which is painful and time-consuming process. The method that we will develop is the dynamical equivalent of Quantum Mechanics-Molecular Mechanics (QM-MM). Just like in QM-MM we combine the best of both worlds, accurate quantum- based MD and fast classical MD simulations using an initially standardly parameterized forcefield. However, whereas QM-MM is designed to obtain large system size with QM accuracy, our method is designed to boost timescale, even beyond the point of strai ghtforward classical MD. The method is based on path sampling using the Replica Exchange Transition Interface algorithm (RETIS). This method allows for a very natural and exact approach to combine QM and classical potentials and update the classical force field parameters on-the-fly during the simulation. This method will crate an avalanche applications and scientific users since it allows to study an important category of processes, chemical reactions in a complex environment, for which an efficient method is yet lacking.

Publications from Cristin

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FRINATEK-Fri prosj.st. mat.,naturv.,tek