Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman-Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |<i>R</i><sup><i>n</i></sup> + <i>c</i>|<sup>-<i>m</i></sup>. Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-02-05
DOI
https://doi.org/10.1021/acs.jctc.4c01234
Citations
5
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
2.59

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article

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

Alexander Buccheri, J. Emiliano Deustua, Frederick R. Manby, Seyed Mohamad Moosavi et al.
5 citations
Journal of Chemical Theory and Computation
Machine Learning in Materials Science
2.59
article

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

Alexander Buccheri, J. Emiliano Deustua, Frederick R. Manby, Seyed Mohamad Moosavi, Peter J. Bygrave, Rui Li
article en
5 citations

Abstract

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman-Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |<i>R</i><sup><i>n</i></sup> + <i>c</i>|<sup>-<i>m</i></sup>. Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

Journal of Chemical Theory and ComputationVol. 21(4)
California Institute of Technology (US), University of Toronto (CA), University of Bristol (GB), Division of Chemistry (US), Max Planck Institute for the Structure and Dynamics of Matter (DE)
Max-Planck-Gesellschaft, Engineering and Physical Sciences Research Council, Basic Energy Sciences
Openalex Percentile: Top 12%
Machine Learning in Materials Science
2.59
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