DL_FFLUX: a parallel, quantum chemical topology force field

Symons, Ben; Bane, Michael; Popelier, Paul L. A.

doi:10.26434/chemrxiv-2021-7mm36

Cited by 3 publications

(4 citation statements)

References 45 publications

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“…For simulations of systems larger than a monomer, nonbonded parameters are used as a measure of dispersion and repulsion although, in theory, these can also be trained for in the GPR model. The methodology behind FFLUX has been explained elsewhere, 14,15 but a brief overview is provided as part of this work.…”

Section: Methodsmentioning

confidence: 99%

“…These approximations, among others, mean that classical force fields are not accurate enough in practice to determine the typically few kJ mol −1 energy differences between polymorphs of crystal structures. 13 FFLUX 14,15 is a next-generation force field that aims to address these shortcomings. FFLUX is based on the quantum theory of atoms in molecules (QTAIM) 16 and the interacting quantum atoms (IQA) 17 energy partitioning scheme.…”

Section: Introductionmentioning

confidence: 99%

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Construction of a Gaussian Process Regression Model of Formamide for Use in Molecular Simulations

2023

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FFLUX, a novel force field based on quantum chemical topology, can perform molecular dynamics simulations with flexible multipole moments that change with geometry. This is enabled by Gaussian process regression machine learning models, which accurately predict atomic energies and multipole moments up to the hexadecapole. We have constructed a model of the formamide monomer at the B3LYP/aug-cc-pVTZ level of theory capable of sub-kJ mol −1 accuracy, with the maximum prediction error for the molecule being 0.8 kJ mol −1 . This model was used in FFLUX simulations along with Lennard-Jones parameters to successfully optimize the geometry of formamide dimers with errors smaller than 0.1 Å compared to those obtained with D3corrected B3LYP/aug-cc-pVTZ. Comparisons were also made to a force field constructed with static multipole moments and Lennard-Jones parameters. FFLUX recovers the expected energy ranking of dimers compared to the literature, and changes in C�O and C−N bond lengths associated with hydrogen bonding were found to be consistent with density functional theory.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Construction of a Gaussian Process Regression Model of Formamide for Use in Molecular Simulations

2023

Self Cite

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“…Note that DL_FFLUX has recently been parallelised with domain decomposition MPI. More information on timings is available in reference 35 . predicting.…”

Section: Technical Detailsmentioning

confidence: 99%

Application of quantum chemical topology force field FFLUX to condensed matter simulations: liquid water

Popelier

Symons

2022

Preprint

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We present here the first application of the quantum chemical topology force field FFLUX to condensed matter simulations. FFLUX offers many‐body potential energy surfaces learnt exclusively from ab initio data using Gaussian process regression. FFLUX also includes high‐rank, polarisable multipole moments (up to quadrupole moments in this work) that are learnt from the same ab initio calculations as the potential energy surfaces. Many‐body effects (where a body is an atom) and polarisation are captured by the machine learning models. The choice to use machine learning in this way allows the force field’s representation of reality to be improved (e.g. by including higher order many‐body effects) with no detriment to the computational scaling of the code. In this manner, FFLUX is inherently future‐proof. The “plug and play" nature of the machine learning models also ensures that FFLUX can be applied to any system of interest, not just liquid water. In this work we study liquid water across a range of temperatures and compare the predicted bulk properties to experiment as well as other state‐of‐the‐art force fields AMOEBA(+CF), HIPPO, MB‐Pol and SIBFA21. We find that FFLUX finds a place amongst these.

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“…10,28 ML approaches have also been developed to predict multipole moments directly from molecular geometry 19 and were recently used in a dynamics study. 29 However, such approaches are still at their explorative stage and are yet to be applied to the simulation of larger, conformationally flexible molecules.…”

Section: Introductionmentioning

confidence: 99%

Molecular Dynamics with Conformationally Dependent, Distributed Charges

Boittier

Devereux

Meuwly

2022

J. Chem. Theory Comput.

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Accounting for geometry-induced changes in the electronic distribution in molecular simulation is important for capturing effects such as charge flow, charge anisotropy, and polarization. Multipolar force fields have demonstrated their ability to correctly represent chemically significant features such as anisotropy and sigma holes. It has also been shown that off-center point charges offer a compact alternative with similar accuracy. Here, it is demonstrated that allowing relocation of charges within a minimally distributed charge model (MDCM) with respect to their reference atoms is a viable route to capture changes in the molecular charge distribution depending on geometry, i.e., intramolecular polarization. The approach, referred to as “flexible MDCM” (fMDCM), is validated on a number of small molecules and provides accuracies in the electrostatic potential (ESP) of 0.5 kcal/mol on average compared with reference data from electronic structure calculations, whereas MDCM and point charges have root mean squared errors of a factor of 2 to 5 higher. In addition, MD simulations in the NVE ensemble using fMDCM for a box of flexible water molecules with periodic boundary conditions show a width of 0.1 kcal/mol for the fluctuation around the mean at 300 K on the 10 ns time scale. For water, the equilibrium valence angle in the gas phase is found to increase by 2° for simulations in the condensed phase which is consistent with experiment. The accuracy in capturing the geometry dependence of the ESP together with the long-time stability in energy conserving simulations makes fMDCM a promising tool to introduce advanced electrostatics into atomistic simulations.

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DL_FFLUX: a parallel, quantum chemical topology force field

Cited by 3 publications

References 45 publications

Construction of a Gaussian Process Regression Model of Formamide for Use in Molecular Simulations

Construction of a Gaussian Process Regression Model of Formamide for Use in Molecular Simulations

Application of quantum chemical topology force field FFLUX to condensed matter simulations: liquid water

Molecular Dynamics with Conformationally Dependent, Distributed Charges

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