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An adaptive modeling method (AMM) that couples a deep neural network potential and a classical force field is introduced to address the accuracy-efficiency dilemma faced by the molecular simulation community.
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Theoretical studies of enzymic reactions: dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozyme
Arieh Warshel and Michael Levitt · 1976
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Comparison of simple potential functions for simulating liquid water
William L Jorgensen, Jayaraman Chandrasekhar, Jeffry D Madura, Roger W Impey, and Michael L Klein · 1983
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HJC Berendsen, JR Grigera, and TP Straatsma · 1987
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Richard M Martin · 2004
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Adaptive resolution molecular-dynamics simulation: Changing the degrees of freedom on the fly
Matej Praprotnik, Luigi Delle Site, and Kurt Kremer · 2005
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Qm/mm: what have we learned, where are we, and where do we go from here?
Hai Lin and Donald G Truhlar · 2007
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Generalized neural-network representation of high-dimensional potential-energy surfaces
Jörg Behler and Michele Parrinello · 2007
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Some fundamental problems for an energy-conserving adaptive-resolution molecular dynamics scheme
Luigi Delle Site · 2007
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Hybrid atomistic simulation methods for materials systems
Noam Bernstein, James R Kermode, and Gabor Csanyi · 2009
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Classical to path-integral adaptive resolution in molecular simulation: towards a smooth quantum-classical coupling
AB Poma and Luigi Delle Site · 2010
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Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons
Albert P Bartók, Mike C Payne, Risi Kondor, and Gábor Csányi · 2010
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High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide
Nongnuch Artrith, Tobias Morawietz, and Jörg Behler · 2011
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Qm/mm simulation of liquid water with an adaptive quantum region
Noam Bernstein, Csilla Várnai, Ivan Solt, Steven A Winfield, Mike C Payne, István Simon, Mónika Fuxreiter, and Gábor Csányi · 2012
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Adaptive resolution molecular dynamics simulation through coupling to an internal particle reservoir
Sebastian Fritsch, Simon Poblete, Christoph Junghans, Giovanni Ciccotti, Luigi Delle Site, and Kurt Kremer · 2012
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Positive definiteness of the blended force-based quasicontinuum method
Xingjie Helen Li, Mitchell Luskin, and Christoph Ortner · 2012
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Adaptive resolution simulation in equilibrium and beyond
Han Wang and Animesh Agarwal · 2015
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Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers
Mark James Abraham, Teemu Murtola, Roland Schulz, Szilárd Páll, Jeremy C Smith, Berk Hess, and Erik Lindahl · 2015
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Molecular dynamics in a grand ensemble: Bergmann–lebowitz model and adaptive resolution simulation
Animesh Agarwal, Jinglong Zhu, Carsten Hartmann, Han Wang, and Luigi Delle Site · 2015
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How van der waals interactions determine the unique properties of water
Tobias Morawietz, Andreas Singraber, Christoph Dellago, and Jörg Behler · 2016
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Sampling the isothermal-isobaric ensemble by langevin dynamics
Xingyu Gao, Jun Fang, and Han Wang · 2016
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Fast and accurate modeling of molecular atomization energies with machine learning
Matthias Rupp, Alexandre Tkatchenko, Klaus-Robert Müller, and O Anatole Von Lilienfeld · 2012
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Adaptive resolution simulation (adress): a smooth thermodynamic and structural transition from atomistic to coarse grained resolution and vice versa in a grand canonical fashion
Han Wang, Christof Schütte, and Luigi Delle Site · 2012
Cited alongside, same era.
Tests of an adaptive qm/mm calculation on free energy profiles of chemical reactions in solution
Csilla Várnai, Noam Bernstein, Letif Mones, and Gábor Csányi · 2013
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Convergence of a force-based hybrid method in three dimensions
Jianfeng Lu and Pingbing Ming · 2013
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Grand-canonical-like molecular-dynamics simulations by using an adaptive-resolution technique
Han Wang, Carsten Hartmann, Christof Schütte, and Luigi Delle Site · 2013
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Gromacs 4.5: a high-throughput and highly parallel open source molecular simulation toolkit
S. Pronk, S. Páll, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M.R. Shirts, J.C. Smith, P.M. Kasson, D. van der Spoel, B. Hess, and E. Lindahl · 2013
Cited alongside, same era.
Theory-based benchmarking of the blended force-based quasicontinuum method
Xingjie Helen Li, Mitchell Luskin, Christoph Ortner, and Alexander V Shapeev · 2014
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Luigi Delle Site · 2016
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Molecular systems with open boundaries: Theory and simulation
Luigi Delle Site and Matej Praprotnik · 2017
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Quantum-chemical insights from deep tensor neural networks
Kristof T Schütt, Farhad Arbabzadah, Stefan Chmiela, Klaus R Müller, and Alexandre Tkatchenko · 2017
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Machine learning of accurate energy-conserving molecular force fields
Stefan Chmiela, Alexandre Tkatchenko, Huziel E Sauceda, Igor Poltavsky, Kristof T Schütt, and Klaus-Robert Müller · 2017
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Ani-1: an extensible neural network potential with dft accuracy at force field computational cost
Justin S Smith, Olexandr Isayev, and Adrian E Roitberg · 2017
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A posteriori error control for three typical force-based atomistic-to-continuum coupling methods for an atomistic chain
Hao Wang, Shaohui Liu, and Feng Yang · 2018
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Deep potential: a general representation of a many-body potential energy surface
Jequn Han, Linfeng Zhang, Roberto Car, and Weinan E · 2018
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Deep potential molecular dynamics: A scalable model with the accuracy of quantum mechanics
Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, and Weinan E · 2018
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Deepmd-kit: A deep learning package for many-body potential energy representation and molecular dynamics
Han Wang, Linfeng Zhang, Jiequn Han, and Weinan E · 2018
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