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231225s2017 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.25066
|2 doi
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|a pubmed24n0920.xml
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|a DE-627
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|a eng
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|a Khanjari, Neda
|e verfasserin
|4 aut
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|a Adaptive-numerical-bias metadynamics
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|c 2017
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Revised 20.11.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2017 Wiley Periodicals, Inc.
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|a A metadynamics scheme is presented in which the free energy surface is filled with progressively adding adaptive biasing potentials, obtained from the accumulated probability distribution of the collective variables. Instead of adding Gaussians with assigned height and width in conventional metadynamics method, here we add a more realistic adaptive biasing potential to the Hamiltonian of the system. The shape of the adaptive biasing potential is adjusted on the fly by sampling over the visited states. As the top of the barrier is approached, the biasing potentials become wider. This decreases the problem of trapping the system in the niches, introduced by the addition of Gaussians of fixed height in metadynamics. Our results for the free energy profiles of three test systems show that this method is more accurate and converges more quickly than the conventional metadynamics, and is quite comparable (in accuracy and convergence rate) with the well-tempered metadynamics method. © 2017 Wiley Periodicals, Inc
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a adaptive biasing potentials
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|a free energy calculations
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|a metadynamics
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|a potential of mean force
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|a sampling rare events
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|a Eslami, Hossein
|e verfasserin
|4 aut
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|a Müller-Plathe, Florian
|e verfasserin
|4 aut
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 38(2017), 31 vom: 05. Dez., Seite 2721-2729
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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|g volume:38
|g year:2017
|g number:31
|g day:05
|g month:12
|g pages:2721-2729
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|u http://dx.doi.org/10.1002/jcc.25066
|3 Volltext
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