A new potential energy surface of the OH2+ system and state-to-state quantum dynamics studies of the O+ + H2 reaction

2018 ◽  
Vol 20 (2) ◽  
pp. 1039-1050 ◽  
Author(s):  
Wentao Li ◽  
Jiuchuang Yuan ◽  
Meiling Yuan ◽  
Yong Zhang ◽  
Minghai Yao ◽  
...  
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Configuration Interaction ◽  
Quantum Dynamics ◽  
Energy Surface ◽  
Basis Sets ◽  
Interaction Method ◽  
Configuration Interaction Method ◽  
Network Method

A new global potential energy surface of the O+ + H2 system was constructed with neural network method, using about 63000 ab initio points, which were calculated by employing the multi-reference configuration interaction method with aug-cc-pVTZ and aug-cc-pVQZ basis sets.

A neural network potential energy surface for the NaH2 system and dynamics studies on the H(2S) + NaH(X1Σ+) → Na(2S) + H2(X1Σg+) reaction

2017 ◽  
Vol 19 (30) ◽  
pp. 19873-19880 ◽  
Author(s):  
Shufen Wang ◽  
Jiuchuang Yuan ◽  
Huixing Li ◽  
Maodu Chen
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Neural Network Method ◽  
The Neural Network ◽  
Network Method ◽  
High Level

A new potential energy surface of the NaH2 system is obtained using the neural network method based on high-level energies.

A new potential energy surface for the ground electronic state of the LiH2 system, and dynamics studies on the H(2S) + LiH(X1Σ+) → Li(2S) + H2(X1Σg+) reaction

2015 ◽  
Vol 17 (17) ◽  
pp. 11732-11739 ◽  
Author(s):  
Jiuchuang Yuan ◽  
Di He ◽  
Maodu Chen
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Electronic State ◽  
Energy Surface ◽  
Ground Electronic State ◽  
Neural Network Method ◽  
Network Method ◽  
High Level

A new potential energy surface of the LiH2 system is obtained using a neural network method based on high-level energies.

Quasi-classical trajectory studies on the full-dimensional accurate potential energy surface for the OH + H2O = H2O + OH reaction

2017 ◽  
Vol 19 (27) ◽  
pp. 17718-17725 ◽  
Author(s):  
Mengna Bai ◽  
Dandan Lu ◽  
Jun Li
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Classical Trajectory ◽  
Invariant Polynomial ◽  
Neural Network Method ◽  
Polynomial Neural Network ◽  
Network Method

The first accurate PES for the OH + H2O reaction is developed by using the permutation invariant polynomial-neural network method to fit ∼48 000 CCSD(T)-F12a/AVTZ calculated points.

scholarly journals A global potential energy surface and dynamics study of the Au+ + H2 → H + Au+H reaction

RSC Advances ◽  
2017 ◽  
Vol 7 (57) ◽  
pp. 35648-35654
Author(s):  
Shufen Wang ◽  
Di He ◽  
Wentao Li ◽  
Maodu Chen
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Ground State ◽  
Energy Surface ◽  
Invariant Polynomials ◽  
Neural Network Method ◽  
Network Method

A global potential energy surface (PES) of the ground state of the Au+H2 system was constructed using a neural network method with permutation invariant polynomials.

scholarly journals A new potential energy surface for the ground state of the LiH2+system and dynamic studies on LiH+(X2Σ+) + H(2S) → Li+(1S) + H2(X1Σ+g)

RSC Advances ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. 7008-7014 ◽  
Author(s):  
Man Dong ◽  
Wentao Li ◽  
Di He ◽  
Maodu Chen
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Ground State ◽  
Energy Surface ◽  
Neural Network Method ◽  
Dynamic Studies ◽  
The Neural Network ◽  
Network Method

An accurate potential energy surface for the ground state of the LiH2+system is constructed with the neural network method.

A new global potential energy surface of the SH2+(X4A′′) system and quantum calculations for the S+ + H2(v = 0–3, j = 0) reaction

2021 ◽  
Author(s):  
Ziliang Zhu ◽  
Aijie Zhang ◽  
Di He ◽  
Wentao Li
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Ground State ◽  
Energy Surface ◽  
Invariant Polynomial ◽  
Quantum Calculations ◽  
Neural Network Method ◽  
Polynomial Neural Network ◽  
Network Method

A new global potential energy surface (PES) for the ground state of the SH2+(X4A′′) system is constructed using a permutation invariant polynomial neural network method.

scholarly journals Full-Dimensional Ab Initio Potential Energy Surface and Vibrational Energy Levels of Li2H

Molecules ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 26
Author(s):  
Michiko Ahn Furudate ◽  
Denis Hagebaum-Reignier ◽  
Gwang-Hi Jeung
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Ab Initio ◽  
Configuration Interaction ◽  
Energy Surface ◽  
Vibrational Energy ◽  
Energy Levels ◽  
Vibrational States ◽  
Configuration Interaction Method ◽  
Vibrational Energy Levels

We built a full-dimensional analytical potential energy surface of the ground electronic state of Li2H from ca. 20,000 ab initio multi-reference configuration interaction calculations, including core–valence correlation effects. The surface is flexible enough to accurately describe the three dissociation channels: Li (2s 2S) + LiH (1Σ+), Li2 (1Σg+) + H (1s 2S) and 2Li (2s 2S) + H (1s 2S). Using a local fit of this surface, we calculated pure (J = 0) vibrational states of Li2H up to the barrier to linearity (ca. 3400 cm−1 above the global minimum) using a vibrational self-consistent field/virtual state configuration interaction method. We found 18 vibrational states below this barrier, with a maximum of 6 quanta in the bending mode, which indicates that Li2H could be spectroscopically observable. Moreover, we show that some of these vibrational states are highly correlated already ca. 1000 cm−1 below the height of the barrier. We hope these calculations can help the assignment of experimental spectra. In addition, the first low-lying excited states of each B1, B2 and A2 symmetry of Li2H were characterized.

Mode specificity for the dissociative chemisorption of H2O on Cu(111): a quantum dynamics study on an accurately fitted potential energy surface

2016 ◽  
Vol 18 (12) ◽  
pp. 8537-8544 ◽  
Author(s):  
Tianhui Liu ◽  
Zhaojun Zhang ◽  
Bina Fu ◽  
Xueming Yang ◽  
Dong H. Zhang
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Quantum Dynamics ◽  
Energy Surface ◽  
Dissociative Chemisorption ◽  
Mode Specificity

The mode-specific dynamics for the dissociative chemisorption of H2O on Cu(111) is first investigated by seven-dimensional quantum dynamics calculations, based on an accurately fitted potential energy surface (PES) recently developed by neural network fitting to DFT energy points.

A neural network potential energy surface for the F + H2O ↔ HF + OH reaction and quantum dynamics study of isotopic effect

2021 ◽  
Author(s):  
Xiaoren Zhang ◽  
Jun Chen ◽  
Xin Xu ◽  
Shu Liu ◽  
Dong H. Zhang
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Ab Initio ◽  
Quantum Dynamics ◽  
Energy Surface ◽  
Isotopic Effect ◽  
The Neural Networks

A global potential energy surface for the F + H2O ↔ HF + OH reaction has been constructed using the neural networks method based on ~24,000 ab initio energies calculated...

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