A flexible implementation of frozen‐density embedding for use in multilevel simulations

Jacob, Christoph R.; Neugebauer, Johannes; Visscher, Lucas

doi:10.1002/jcc.20861

Cited by 162 publications

(215 citation statements)

References 52 publications

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“…[20] While achieving this goal is (at least on paper) relatively straightforward when atom-centered basis sets are employed, the fact that QE includes periodic boundary conditions and employs an originless plane-wave (PW) basis set, presents us with a challenge. If all of the N S subsystems are represented on the same supersystem simulation cell and share the same kinetic energy cutoff in the PW expansion, the code would thus need to solve N S coupled KS-like problems in the large (supersystem) basis set.…”

Section: Subsystem-specific Basis Setsmentioning

confidence: 99%

“…On the FDE side, the Amsterdam Density Functional (ADF) code [19] holds perhaps the most celebrated implementation. [20][21][22][23][24][25] Another notable implementation [26,27] resides in the CP2K code. [28] CASTEP [29] also has an implementation of FDE [30] which was employed in simulations involving two subsystems, one of which was treated at the correlated wavefunction level.…”

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confidence: 99%

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eQE: An open‐source density functional embedding theory code for the condensed phase

Genova

Ceresoli

Krishtal

et al. 2017

Int J of Quantum Chemistry

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In this work, we present the main features and algorithmic details of a novel implementation of the frozen density embedding (FDE) formulation of subsystem density functional theory (DFT) that is specifically designed to enable ab initio molecular dynamics (AIMD) simulations of largescale condensed-phase systems containing 1000s of atoms. This code (available at http://eqe. rutgers.edu) has been given the moniker of embedded Quantum ESPRESSO (eQE) as it is a generalization of the open-source Quantum ESPRESSO (QE) suite of programs. The strengths of eQE reside in a hierarchical parallelization scheme that allows for an efficient and fully self-consistent treatment of the electronic structure (via the addition of an additional DIIS extrapolation layer) while simultaneously exploiting the inherent symmetries and periodicities in the system (via sampling of subsystem-specific first Brillouin zones and utilization of subsystem-specific basis sets).While bulk liquids and molecular crystals are two classes of systems that exemplify the utility of the FDE approach (as these systems can be partitioned into weakly interacting subunits), we show that eQE has significantly extended this regime of applicability by outperforming standard semilocal Kohn-Sham DFT (KS-DFT) for large-scale heterogeneous catalysts with quite different layerspecific electronic structure and intrinsic periodicities. eQE features very favorable strong parallel scaling for a model system of bulk liquid water composed of 256 water molecules, which allows for a significant decrease in the overall time to solution when compared to KS-DFT. We show that eQE achieves speedups greater than one order of magnitude (>103) when performing AIMD simulations of such large-scale condensed-phase systems as: (1) | I N T R O D U C T I O NThe Kohn-Sham (KS) formulation of density functional theory (DFT) [1] is currently the most widely employed electronic structure method in the fields of chemistry, physics, and materials science. This is largely due to the fact that KS-DFT employing semilocal exchange-correlation (xc) functionals produces models of remarkable accuracy and predictive capability [2] with a relatively low associated computational cost (that in general Int J Quantum Chem. 2017;117:e25401.

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Section: Subsystem-specific Basis Setsmentioning

confidence: 99%

mentioning

confidence: 99%

eQE: An open‐source density functional embedding theory code for the condensed phase

Genova

Ceresoli

Krishtal

et al. 2017

Int J of Quantum Chemistry

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“…Frozen-density embedding and subsystem-DFT jobs are handled by the class adffragmentsjob. Such jobs require a list of fragments (i.e., molecule objects and possibly the results objects of previous calculations) and for each of these fragments, it can then be chosen whether it is active, frozen, or a frozen fragment that is iteratively updated in freeze-and-thaw cycles (see also the description of the flexible FDE implementation in the Adf package 44 ). In the case considered here, two fragments (one active and one that is updated in freeze-and-thaw cycles) are used.…”

Section: Running Calculations For Large Test Sets Of Moleculesmentioning

confidence: 99%

PyADF — A scripting framework for multiscale quantum chemistry

Jacob

Beyhan²,

Bulo³

et al. 2011

J Comput Chem

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100

106

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Abstract:Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed PyAdf, a scripting framework for quantum chemistry. PyAdf handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of PyAdf and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications.

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“…26,27 While the FDE ansatz has been mostly applied in the embedding regime (one small active system surrounded by a large frozen environment), one may also formulate this model as a special case of a more general subsystem DFT approach. 28,29 One then writes the total density as a sum of subsystem densities…”

Section: Introductionmentioning

confidence: 99%

Molecular properties via a subsystem density functional theory formulation: A common framework for electronic embedding

Höfener¹,

Gomes

Visscher³

2012

The Journal of Chemical Physics

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108

125

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In this article, we present a consistent derivation of a density functional theory (DFT) based embedding method which encompasses wave-function theory-in-DFT (WFT-in-DFT) and the DFT-based subsystem formulation of response theory (DFT-in-DFT) by Neugebauer [J. Neugebauer, J. Chem. Phys. 131, 084104 (2009)] as special cases. This formulation, which is based on the time-averaged quasi-energy formalism, makes use of the variation Lagrangian techniques to allow the use of nonvariational (in particular: coupled cluster) wave-function-based methods. We show how, in the timeindependent limit, we naturally obtain expressions for the ground-state DFT-in-DFT and WFT-in-DFT embedding via a local potential. We furthermore provide working equations for the special case in which coupled cluster theory is used to obtain the density and excitation energies of the active subsystem. A sample application is given to demonstrate the method.

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A flexible implementation of frozen‐density embedding for use in multilevel simulations

Cited by 162 publications

References 52 publications

eQE: An open‐source density functional embedding theory code for the condensed phase

eQE: An open‐source density functional embedding theory code for the condensed phase

PyADF — A scripting framework for multiscale quantum chemistry

Molecular properties via a subsystem density functional theory formulation: A common framework for electronic embedding

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