Polarizabilities and London dispersion forces are important to many chemical processes. Force fields for classical atomistic simulations can be constructed using atominmaterial polarizabilities and C n ( n = 6, 8, 9, 10…) dispersion coefficients. This article addresses the key question of how to efficiently assign these parameters to constituent atoms in a material so that properties of the whole material are better reproduced. We develop a new set of scaling laws and computational algorithms (called MCLF) to do this in an accurate and computationally efficient manner across diverse material types. We introduce a conduction limit upper bound and m scaling to describe the different behaviors of surface and buried atoms. We validate MCLF by comparing results to highlevel benchmarks for isolated neutral and charged atoms, diverse diatomic molecules, various polyatomic molecules ( e.g. , polyacenes, fullerenes, and small organic and inorganic molecules), and dense solids (including metallic, covalent, and ionic). We also present results for the HIV reverse transcriptase enzyme complexed with an inhibitor molecule. MCLF provides the nondirectionally screened polarizabilities required to construct force fields, the directionallyscreened static polarizability tensor components and eigenvalues, and environmentally screened C 6 coefficients. Overall, MCLF has improved accuracy compared to the TSSCSmore »
New scaling relations to compute atominmaterial polarizabilities and dispersion coefficients: part 2. Linearscaling computational algorithms and parallelization
We present two algorithms to compute systemspecific polarizabilities and dispersion coefficients such that required memory and computational time scale linearly with increasing number of atoms in the unit cell for large systems. The first algorithm computes the atominmaterial (AIM) static polarizability tensors, forcefield polarizabilities, and C 6 , C 8 , C 9 , C 10 dispersion coefficients using the MCLF method. The second algorithm computes the AIM polarizability tensors and C 6 coefficients using the TSSCS method. Linearscaling computational cost is achieved using a dipole interaction cutoff length function combined with iterative methods that avoid large dense matrix multiplies and large matrix inversions. For MCLF, Richardson extrapolation of the screening increments is used. For TSSCS, a failproof conjugate residual (FCR) algorithm is introduced that solves any linear equation system having Hermitian coefficients matrix. These algorithms have mathematically provable stable convergence that resists roundoff errors. We parallelized these methods to provide rapid computation on multicore computers. Excellent parallelization efficiencies were obtained, and adding parallel processors does not significantly increase memory requirements. This enables systemspecific polarizabilities and dispersion coefficients to be readily computed for materials containing millions of atoms in the unit cell. The largest example studied herein is an ice more »
 Award ID(s):
 1555376
 Publication Date:
 NSFPAR ID:
 10122310
 Journal Name:
 RSC Advances
 Volume:
 9
 Issue:
 57
 Page Range or eLocationID:
 33310 to 33336
 ISSN:
 20462069
 Sponsoring Org:
 National Science Foundation
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