scholarly journals Structural exploration of AuxM− (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm

RSC Advances ◽  
2019 ◽  
Vol 9 (13) ◽  
pp. 7432-7439 ◽  
Author(s):  
Ping Huang ◽  
Yan Jiang ◽  
Tianquan Liang ◽  
Enhui Wu ◽  
Jun Li ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface

We used a revised genetic algorithm (GA) to explore the potential energy surface (PES) of AuxM− (x = 9–12; M = Si, Ge, Sn) clusters.

scholarly journals Exploring the potential energy surface of small lead clusters using the gradient embedded genetic algorithm and an adequate treatment of relativistic effects

RSC Advances ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 145-152 ◽  
Author(s):  
Walter A. Rabanal-León ◽  
William Tiznado ◽  
Edison Osorio ◽  
Franklin Ferraro
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Crucial Role ◽  
Energy Surface ◽  
Relativistic Effects ◽  
Spin Orbit ◽  
Adequate Treatment ◽  
Structural Assignment

Theoretical inclusion of relativistic effects (scalar and spin–orbit) play a crucial role to assure an adequate structural assignment on lead clusters.

Conformational space analysis of neutral and protonated glycine using a genetic algorithm for multi-modal search

2014 ◽  
Vol 13 (08) ◽  
pp. 1450067 ◽  
Author(s):  
B. El Merbouh ◽  
M. Bourjila ◽  
R. Tijar ◽  
R. Drissi El Bouzaidi ◽  
A. El Gridani ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Protonated Form ◽  
Conformational Space ◽  
Empirical Methods ◽  
Space Analysis ◽  
Semi Empirical

The genetic algorithm based on the Multi-Niche Crowding (MNC) method is used with the semi-empirical methods AM1 and PM3 in order to scan the potential energy surface (PES) of neutral and protonated glycine. The algorithm is implemented as a package of programs interfaced with MOPAC and piloted by scripts. Both methods AM1 and PM3 located six minima on the PES of neutral glycine and seven on the protonated glycine one, of which three are those of the N -protonated form and four of the O -protonated one.

Fitting potential energy surface of reactive systems via genetic algorithm

2006 ◽  
Vol 106 (13) ◽  
pp. 2650-2657 ◽  
Author(s):  
Wiliam Ferreira Da Cunha ◽  
Luiz Fernando Roncaratti ◽  
Ricardo Gargano ◽  
Geraldo Magela E Silva
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Reactive Systems

Quantum Monte Carlo and genetic algorithm study of the potential energy surface of the H +5 molecule

2008 ◽  
Vol 108 (13) ◽  
pp. 2318-2325 ◽  
Author(s):  
Geraldo M. e Silva ◽  
Ricardo Gargano ◽  
Washington B. da Silva ◽  
Luiz F. Roncaratti ◽  
Paulo H. Acioli
Keyword(s):  
Genetic Algorithm ◽  
Monte Carlo ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Quantum Monte Carlo ◽  
Energy Surface

Quantum reactive study of a potential energy surface obtained via genetic algorithm

2008 ◽  
Vol 108 (13) ◽  
pp. 2306-2311 ◽  
Author(s):  
Lucas R. Salviano ◽  
Geraldo M. E Silva ◽  
João B. L. Martins ◽  
Ricardo Gargano
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface

scholarly journals Thermodynamically accessible titanium clusters TiN, N = 2–32

2018 ◽  
Vol 20 (20) ◽  
pp. 13962-13973 ◽  
Author(s):  
Tomas Lazauskas ◽  
Alexey A. Sokol ◽  
John Buckeridge ◽  
C. Richard A. Catlow ◽  
Susanne G. E. T. Escher ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Interatomic Potential ◽  
Tight Binding ◽  
Algorithm Search

We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2–32) clusters.

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