Fragmentation methods: a route to accurate calculations on large systems.

By M. Gordon, D. Fedorov, Spencer R Pruitt, Lyudmila V. Slipchenko. Chemical Reviews, 2012

1,011 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Condensed Matter Physics

View Paper: https://www.semanticscholar.org/paper/0959586ad3d592d5178fdf21fc481b297c09f76c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

In Condensed Matter Physics

Citations in the corpus

Solving the scalability issue in quantum-based refinement: Q|R#1. (2017, methodology): “Fragmentation methods can provide an efficient route to effectively model large and complex molecular systems (Kitaura et al., 1999; He et al., 2014; Gordon et al., 2012; Fedorov & Kitaura, 2007).”
GAMESS as a free quantum-mechanical platform for drug research. (2012, methodology): “A number of ab initio [19, 20] and fragment-based [21, 22] linearly scaling methods have been proposed, which”
Explicitly correlated local coupled‐cluster methods using pair natural orbitals (2018, methodology): “For a further discussion of fragmentation methods, we refer to a recent book(186) and other reviews.(152,187) In the current article, we review the explicitly correlated pair natural orbital local coupled-cluster method [PNO-LCCSD(T)F12], which has recently been developed in our laboratory.”
Subsystem density‐functional theory (2014, neutral): “The subsystem-DFT energy expression is thus E[{ψi I }] = ∑ I Ts[{ψi I }] + Vnuc[ρ] + J [ρ] + Exc[ρ] + Tnads [{ρI}] + Vnn. (24) Minimization of this energy expression with respect to the Kohn–Sham-like orbitals {ψiK } of subsystem K, under the constraint that these subsystem orbitals are orthonormal ”
Transferable Multilevel Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multitask Learning (2020, background): “Lmain targets = ∑ ∑ |PiDeepMoleNet − PiDFT| all i 8 properties in Set2Set P Nmolecules + ρ ∑ ∑ |PiDeepMoleNet − PiDFT| all i 4 properties in Atom−wise NN P Nmolecules (10), where the first term is set for the readout 8 properties, including dipole, polarizability, HOMO, LUMO, HOMO-LUMO gap, <R2>, ZP”