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A polarizable high‐rank quantum topological electrostatic potential developed using neural networks: Molecular dynamics simulations on the hydrogen fluoride dimer
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Citations
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References
2007
Year
Hf DimerEngineeringHf MoleculeComputational ChemistryChemistryElectronic StructureMolecular DynamicsMolecular DesignHydrogen Fluoride DimerQuantum SimulationMolecular SimulationComputational BiochemistryBiophysicsQuantum SciencePhysicsPhysical ChemistryNeural NetworksMolecular MechanicQuantum ChemistryLiquid HfLow-dimensional StructureNatural SciencesMolecular PropertyHydrogen-bonded LiquidMolecular Dynamics SimulationsChemical Thermodynamics
Abstract The HF molecule is a simple polar system that serves as a prototype for developing new potentials. Here we build on earlier work [Liem and Popelier, J Chem Phys 2003, 119, 4560] in which a high‐rank multipolar potential was used to simulate liquid HF. That work was the first example of high‐rank multipole moments (up to hexadecapole) being employed in conjunction with multipolar Ewald summation in a molecular dynamics simulation. This potential is now extended with polarization, which is delivered by artificial neural networks. The neural nets predict how atomic multipole moments change as the position of neighboring molecules vary. This novel approach is successfully tested on the HF dimer in vacuum. © 2007 Wiley Periodicals, Inc. Int J Quantum Chem, 2007
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