(Q43910787)

English

Molecular dissociation of hydrogen peroxide (HOOH) on a neural network ab initio potential surface with a new configuration sampling method involving gradient fitting

scientific article published in July 2009

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scholarly article

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Europe PubMed Central

28 November 2017

Molecular dissociation of hydrogen peroxide (HOOH) on a neural network ab initio potential surface with a new configuration sampling method involving gradient fitting (English)

1 reference

Europe PubMed Central

28 November 2017

author name string

Hung M Le

1

1 reference

Europe PubMed Central

28 November 2017

Sau Huynh

2

1 reference

Europe PubMed Central

28 November 2017

Lionel M Raff

3

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Europe PubMed Central

28 November 2017

language of work or name

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publication date

1 July 2009

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28 November 2017

Journal of Chemical Physics

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28 November 2017

131

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28 November 2017

1

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Europe PubMed Central

28 November 2017

014107

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Europe PubMed Central

28 November 2017

Gaussian basis sets for use in correlated molecular calculations. I. The atoms boron through neon and hydrogen

1 reference

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Density-functional thermochemistry. III. The role of exact exchange

1 reference

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Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density

1 reference

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21 January 2018

Interpolating moving least-squares methods for fitting potential energy surfaces: computing high-density potential energy surface data from low-density ab initio data points

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Interpolating moving least-squares methods for fitting potential energy surfaces: a strategy for efficient automatic data point placement in high dimensions

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Theoretical investigation of the dissociation dynamics of vibrationally excited vinyl bromide on an ab initio potential-energy surface obtained using modified novelty sampling and feed-forward neural networks

1 reference

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21 January 2018

Theoretical investigation of the dissociation dynamics of vibrationally excited vinyl bromide on an ab initio potential-energy surface obtained using modified novelty sampling and feedforward neural networks. II. Numerical application of the method

1 reference

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21 January 2018

Development of generalized potential-energy surfaces using many-body expansions, neural networks, and moiety energy approximations.

1 reference

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21 January 2018

Using neural networks, optimized coordinates, and high-dimensional model representations to obtain a vinyl bromide potential surface

1 reference

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21 January 2018

Cis-->trans, trans-->cis isomerizations and N-O bond dissociation of nitrous acid (HONO) on an ab initio potential surface obtained by novelty sampling and feed-forward neural network fitting.

1 reference

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21 January 2018

Molecular dynamics investigations of the dissociation of SiO2 on an ab initio potential energy surface obtained using neural network methods.

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21 January 2018

Ab initio molecular dynamics of hydrogen dissociation on metal surfaces using neural networks and novelty sampling.

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21 January 2018

Prediction of molecular-dynamics simulation results using feedforward neural networks: reaction of a C2 dimer with an activated diamond (100) surface.

1 reference

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21 January 2018

Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks

1 reference

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21 January 2018

MP2 energy evaluation by direct methods

1 reference

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21 January 2018

Multilayer feedforward networks are universal approximators

1 reference

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21 January 2018

Support-vector networks

1 reference

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21 January 2018

Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks

1 reference

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21 January 2018

Note on an Approximation Treatment for Many-Electron Systems

1 reference

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21 January 2018

Identifiers

10.1063/1.3159748

1 reference

Europe PubMed Central

28 November 2017

1 reference

Europe PubMed Central

28 November 2017

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