(Q46007547)

18 December 2017

title

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

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18 December 2017

author

Satish T S Bukkapatnam

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ORCID Public Data File 2021

author name string

M Malshe

1

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18 December 2017

R Narulkar

2

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18 December 2017

L M Raff

3

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18 December 2017

M Hagan

4

1 reference

18 December 2017

S Bukkapatnam

5

1 reference

18 December 2017

P M Agrawal

6

1 reference

18 December 2017

R Komanduri

7

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18 December 2017

language of work or name

English

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publication date

1 May 2009

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18 December 2017

Journal of Chemical Physics

published in

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18 December 2017

volume

130

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18 December 2017

issue

18

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18 December 2017

page(s)

184102

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18 December 2017

Diatomic Molecules According to the Wave Mechanics. II. Vibrational Levels

cites work

1 reference

On the Determination of Molecular Fields. II. From the Equation of State of a Gas

21 January 2018

1 reference

Embedded-atom method: Derivation and application to impurities, surfaces, and other defects in metals

21 January 2018

1 reference

Empirical potential for hydrocarbons for use in simulating the chemical vapor deposition of diamond films

21 January 2018

1 reference

Modeling solid-state chemistry: Interatomic potentials for multicomponent systems

21 January 2018

1 reference

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

21 January 2018

1 reference

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

21 January 2018

1 reference

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.

21 January 2018

1 reference

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

21 January 2018

1 reference

Constructing multidimensional molecular potential energy surfaces from ab initio data

21 January 2018

1 reference

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

21 January 2018

1 reference

Ab initio potential energy and dipole moment surfaces for H5O2 +.

21 January 2018

1 reference

Full-dimensional quantum calculations of ground-state tunneling splitting of malonaldehyde using an accurate ab initio potential energy surface

21 January 2018

1 reference

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

21 January 2018

1 reference

Efficient chemical kinetic modeling through neural network maps.

21 January 2018

1 reference

High-dimensional model representations generated from low order terms--lp-RS-HDMR.

21 January 2018

1 reference

Multicut-HDMR with an application to an ionospheric model.

21 January 2018

1 reference

Random sampling-high dimensional model representation (RS-HDMR) and orthogonality of its different order component functions

21 January 2018

1 reference

Using neural networks to represent potential surfaces as sums of products.

21 January 2018

1 reference

Multilayer feedforward networks are universal approximators

21 January 2018

1 reference

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

21 January 2018

1 reference

21 January 2018

Identifiers

DOI

10.1063/1.3124802

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18 December 2017

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18 December 2017