A Variational Linear-Scaling Framework to Build Practical, Efficient Next-Generation Orbital-Based Quantum Force Fields

Journal of Chemical Theory and Computation vol. 9  p. 1417-1427  DOI: 10.1021/ct3010134
PMID/PMCID: PMC3694615 Published: 2013-03-12 

Timothy J. Giese [ ] , Haoyuan Chen, Thakshila Dissanayake, George M. Giambas╠žu, Hugh Heldenbrand, Ming Huang, Erich R. Kuechler, Tai-Sung Lee [ ] , Maria T. Panteva, Brian K. Radak, Darrin M. York [ ]

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We introduce a new hybrid molecular orbital/density-functional modified divide-and-conquer (mDC) approach that allows the linear-scaling calculation of very large quantum systems. The method provides a powerful framework from which linear-scaling force fields for molecular simulations can be developed. The method is variational in the energy and has simple, analytic gradients and essentially no break-even point with respect to the corresponding full electronic structure calculation. Furthermore, the new approach allows intermolecular forces to be properly balanced such that nonbonded interactions can be treated, in some cases, to much higher accuracy than the full calculation. The approach is illustrated using the second-order self-consistent charge density-functional tight-binding model (DFTB2). Using this model as a base Hamiltonian, the new mDC approach is applied to a series of water systems, where results show that geometries and interaction energies between water molecules are greatly improved relative to full DFTB2. In order to achieve substantial improvement in the accuracy of intermolecular binding energies and hydrogen bonded cluster geometries, it was necessary to extend the DFTB2 model to higher-order atom-centered multipoles for the second-order self-consistent intermolecular electrostatic term. Using generalized, linear-scaling electrostatic methods, timings demonstrate that the method is able to calculate a water system of 3000 atoms in less than half of a second, and systems of up to 1 million atoms in only a few minutes using a conventional desktop workstation.