Frequency-dependent force fields for QMMM calculations
文献情報
Ignat Harczuk, Olav Vahtras, Hans Ågren
We outline the construction of frequency-dependent polarizable force fields. The force fields are derived from analytic response theory for different frequencies using a generalization of the LoProp algorithm giving a decomposition of a molecular dynamical polarizability to localized atomic dynamical polarizabilities. These force fields can enter in a variety of applications – we focus on two such applications in this work: firstly, they can be incorporated in a physical, straightforward, way for current existing methods that use polarizable embeddings, and we can show, for the first time, the effect of the frequency dispersion within the classical environment of a quantum mechanics–molecular mechanics (QMMM) method. Our methodology is here evaluated for some test cases comprising water clusters and organic residues. Secondly, together with a modified Silberstein–Applequist procedure for interacting inducible point-dipoles, these frequency-dependent polarizable force fields can be used for a classical determination of frequency-dependent cluster polarizabilities. We evaluate this methodology by comparing with the corresponding results obtained from quantum mechanics or QMMM where the absolute mean is determined with respect to the size of the QM and MM parts of the total system.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.









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