Abstract

A parameterization of the ReaxFF reactive FF is performed using a Monte Carlo Simulated Annealing procedure for the modeling of a proline-catalyzed aldol reaction. Emphasis is put on the accurate reproduction of the relative stabilities of several key intermediates of the reaction, as well as, on the description of the reaction path bridging these intermediates based on quantum mechanical calculations. Our training sets include new criteria based on geometry optimizations and short Molecular Dynamics simulations to ensure that the trained ReaxFF potentials adequately predict the structures of all key intermediates. The transferability of the sets of parameters obtained is assessed for various steps of the considered aldol reaction, as well as for different substrates, catalysts, and reagents. This works indeed highlights the challenge of reaching transferable parameters for several reaction steps.

Original languageEnglish
Pages (from-to)2564-2572
Number of pages9
JournalJournal of Computational Chemistry
Volume37
Issue number29
DOIs
Publication statusPublished - 4 Sep 2016

Fingerprint

Force Field
Parameterization
Simulated annealing
Set theory
Proline
Molecular dynamics
Catalysts
Geometry
Computer simulation
Substrates
Relative Stability
Catalyst
Simulated Annealing
Molecular Dynamics Simulation
Substrate
3-hydroxybutanal
Predict
Path
Optimization
Modeling

Keywords

  • force field parameters optimization
  • Monte Carlo simulated annealing
  • proline-catalyzed aldol reaction
  • ReaxFF

Cite this

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title = "Parameterization of the ReaxFF Reactive Force Field for a Proline-Catalyzed Aldol Reaction",
abstract = "A parameterization of the ReaxFF reactive FF is performed using a Monte Carlo Simulated Annealing procedure for the modeling of a proline-catalyzed aldol reaction. Emphasis is put on the accurate reproduction of the relative stabilities of several key intermediates of the reaction, as well as, on the description of the reaction path bridging these intermediates based on quantum mechanical calculations. Our training sets include new criteria based on geometry optimizations and short Molecular Dynamics simulations to ensure that the trained ReaxFF potentials adequately predict the structures of all key intermediates. The transferability of the sets of parameters obtained is assessed for various steps of the considered aldol reaction, as well as for different substrates, catalysts, and reagents. This works indeed highlights the challenge of reaching transferable parameters for several reaction steps.",
keywords = "force field parameters optimization, Monte Carlo simulated annealing, proline-catalyzed aldol reaction, ReaxFF",
author = "Pierre Hubin and Denis Jacquemin and Laurence Leherte and Vercauteren, {Daniel P.}",
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Parameterization of the ReaxFF Reactive Force Field for a Proline-Catalyzed Aldol Reaction. / Hubin, Pierre; Jacquemin, Denis; Leherte, Laurence; Vercauteren, Daniel P.

In: Journal of Computational Chemistry, Vol. 37, No. 29, 04.09.2016, p. 2564-2572.

Research output: Contribution to journalArticle

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T1 - Parameterization of the ReaxFF Reactive Force Field for a Proline-Catalyzed Aldol Reaction

AU - Hubin, Pierre

AU - Jacquemin, Denis

AU - Leherte, Laurence

AU - Vercauteren, Daniel P.

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