Pseudospectral generalized valence-bond calculations: Application to methylene, ethylene, and silylene

Langlois, Jean Marc; Muller, Richard P.; Coley, Terry R.; Goddard, William A.; Ringnalda, Murco N.; Won, Youjip; Friesner, Richard A.

doi:10.1063/1.458184

Cited by 76 publications

(39 citation statements)

References 15 publications

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“…Using eqn. (44) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 out Λ in terms of these three basic quantities, we obtain…”

Section: Computing ∂λ ∂∆Pqmentioning

confidence: 96%

Coupled Cluster Valence Bond Method: Efficient Computer Implementation and Application to Multiple Bond Dissociations and Strong Correlations in the Acenes

Small

Lawler

Head‐Gordon

2014

J. Chem. Theory Comput.

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We describe an efficient implementation of the coupled cluster valence bond (CCVB) model. CCVB captures a certain essential part of the description of molecules with strong correlations (SC), which allows it to achieve correct energy profiles when covalent bonds are broken, while maintaining proper spin symmetry and size extensivity. To illustrate treatment of SC in bond breaking, we examine the symmetric dissociation of the sulfur allotropes S6 and S8 into triplet S atoms. To show applicability to larger systems and to explore whether CCVB can capture aspects of SC that arise in extended π systems, we report results for a series of acenes up to 12 fused benzene rings, with active spaces of up to 228 correlated electrons. The lowest-energy CCVB solutions found for two of the largest acenes show signatures consistent with multi-electron SC and partial delocalization.

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Section: Computing ∂λ ∂∆Pqmentioning

confidence: 96%

Coupled Cluster Valence Bond Method: Efficient Computer Implementation and Application to Multiple Bond Dissociations and Strong Correlations in the Acenes

Small

Lawler

Head‐Gordon

2014

J. Chem. Theory Comput.

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“…The parallel pseudo spectral algorithm has been described in our previous study, and we shall only present the basic idea without detailed elaboration. In PS algorithm, the Coulomb matrix ( J ) elements and the exchange matrix ( K ) elements are calculated via,

J_{i j} = \underset{g}{false\sum} Q_{i} false(r_{g} false) \underset{μ ν}{false\sum} ρ_{ν μ} A_{μ ν} (|, r_{g}) R_{j} false(r_{g} false)

K_{i j} = \underset{g}{false\sum} Q_{i} false(r_{g} false) \underset{μ ν}{false\sum} ρ_{ν μ} A_{μ j} (|, r_{g}) R_{ν} false(r_{g} false)

where

ρ_{ν μ}

is an element of the density matrix,

R_{j} true(r_{g} true)

is the atomic basis function j evaluated at a grid point

r_{g}

A_{μ ν} (|, r_{g})

is a three‐center, one‐electron integral representing the field at

r_{g}

due to the product of two atomic basis functions indexed by

μ

and

ν

, and

Q_{i} true(r_{g} true)

is the least squares fitting operator given by,

…”

Section: Parallel Implementationmentioning

confidence: 99%

Efficient simulation of large materials clusters using the jaguar quantum chemistry program: Parallelization and wavefunction initialization

Zhang

Weisman

Saitta

et al. 2015

Int J of Quantum Chemistry

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An outline of the improvements to the pseudospectral electronic structure program Jaguar is presented, showing efficient and robust performance of hybrid‐DFT calculations for large systems with thousands of basis functions, focusing on materials applications. The improvements include re‐engineered parallelization, the design of a fragment‐based initial guess generation method, and the validation of small eigenvalue cutoff values. An OpenMP/MPI hybrid parallelization has been implemented for the pseudospectral algorithm, which extends Jaguar's scalability to up to 256 cores in tests of TiO2 clusters with 1295‐4961 basis functions. In the largest test case, the code delivers 84.4× speedup for 128 cores in total calculation time. In addition, a fragment‐based initial guess method has been constructed for large systems containing many transition metals, where the conventional (atomic) approach often fails. Overall, Jaguar is now capable of efficiently and robustly performing hybrid‐DFT geometrical optimizations for large systems with more than 600 atoms in reasonable runtimes. © 2015 Wiley Periodicals, Inc.

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“…Excitation energies predicted for the lowest triplet state and the two lowest excited singlet states 1 B 1 and 2 1 A 1 were within a kcal mol 1 of the predictions of the full CI calculation when triple excitations were included, but only for the 2 1 A 1 state was there marked improvement over the inclusion of only single and double excitations. SiH 2 and SiF 2 were among several species used as 'guinea pigs' for new pseudospectral algorithms for electronic structure calculations 231,232 . Absolute energies agreed to within 0.25 kcal mol 1 with those from conventional basis sets, and relative energies were within 0.1 kcal mol 1 , with enhanced computation speeds.…”

Section: Benchmark Calculations On Silylenesmentioning

confidence: 99%

Silylenes

Gaspar¹,

West²

2009

Patai's Chemistry of Functional Groups

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Introduction Generation of Silylenes Reactions of Silylenes Theoretical Calculations Spectroscopic Characterization of Silylenes Kinetics of Silylene Reactions Silylene–Transition Metal Complexes Special Topics Speculations on the Future of Silylene Chemistry

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Pseudospectral generalized valence-bond calculations: Application to methylene, ethylene, and silylene

Cited by 76 publications

References 15 publications

Coupled Cluster Valence Bond Method: Efficient Computer Implementation and Application to Multiple Bond Dissociations and Strong Correlations in the Acenes

Coupled Cluster Valence Bond Method: Efficient Computer Implementation and Application to Multiple Bond Dissociations and Strong Correlations in the Acenes

Efficient simulation of large materials clusters using the jaguar quantum chemistry program: Parallelization and wavefunction initialization

Silylenes

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