Determination of Total Energy Tight Binding Parameters from First Principles Calculations Using Adaptive Simulated Annealing

2001 ◽  
Vol 700 ◽  
Author(s):  
Anders G. Froseth ◽  
Peter Derlet ◽  
Ragnvald Hoier
Keyword(s):  
Simulated Annealing ◽  
Total Energy ◽  
First Principles ◽  
Linear Optimization ◽  
Tight Binding ◽  
Accurate Method ◽  
Optimization Method ◽  
Binding Parameters ◽  
Non Linear

AbstractEmpirical Total Energy Tight Binding (TETB) has proven to be a fast and accurate method for calculating materials properties for various system, including bulk, surface and amorphous structures. The determination of the tight binding parameters from first-principles results is a multivariate, non-linear optimization problem with multiple local minima. Simulated annealing is an optimization method which is flexible and “guaranteed” to find a global minimum, opposed to classical methods like non-linear least squares algorithms. As an example results are presented for a nonorthogonal s,p parameterization for Silicon based on the NRL tight binding formalism.

Automatic Determination of Tight-Binding Parameters in Bulk Systems

2013 ◽  
Vol 1523 ◽  
Author(s):  
Yasuaki Ohtani ◽  
Takeo Fujiwara ◽  
Shinya Nishino ◽  
Takashi Suzuki ◽  
Susumu Yamamoto ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
First Principles ◽  
Tight Binding ◽  
Crystalline Solid ◽  
Binding Parameters ◽  
Automatic Determination ◽  
Dynamics Calculation ◽  
Good Set ◽  
Good Agreement

ABSTRACTWe have studied a procedure to determine Tight-Binding (TB) parameters automatically, by which the band structure of the crystalline solid can be reproduced so as to be good agreement with that of first-principles molecular dynamics calculation. According to this procedure, we determine TB parameter sets for silicon and diamond accurately, and a fairly good set for their compound SiC.

scholarly journals Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization

2017 ◽  
Vol 1 (2) ◽  
pp. 82 ◽  
Author(s):  
Tirana Noor Fatyanosa ◽  
Andreas Nugroho Sihananto ◽  
Gusti Ahmad Fanshuri Alfarisy ◽  
M Shochibul Burhan ◽  
Wayan Firdaus Mahmudy
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Problems ◽  
Linear Optimization ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Function Optimization ◽  
Non Linear ◽  
Speed Up ◽  
Linear Problems

The optimization problems on real-world usually have non-linear characteristics. Solving non-linear problems is time-consuming, thus heuristic approaches usually are being used to speed up the solution’s searching. Among of the heuristic-based algorithms, Genetic Algorithm (GA) and Simulated Annealing (SA) are two among most popular. The GA is powerful to get a nearly optimal solution on the broad searching area while SA is useful to looking for a solution in the narrow searching area. This study is comparing performance between GA, SA, and three types of Hybrid GA-SA to solve some non-linear optimization cases. The study shows that Hybrid GA-SA can enhance GA and SA to provide a better result

Semi-Empirical Tight-Binding Parameters for Total Energy Calculation in Zinc

1997 ◽  
Vol 491 ◽  
Author(s):  
A. Bere ◽  
A. Hairie ◽  
G. Nouet ◽  
E. Paumier
Keyword(s):  
Total Energy ◽  
Interatomic Potential ◽  
Tight Binding ◽  
Energy Calculation ◽  
Extended Defects ◽  
Binding Parameters ◽  
Total Energy Calculation ◽  
Tight Binding Method ◽  
The Stability ◽  
Semi Empirical

ABSTRACTThe semi-empirical tight-binding method is used to build up an interatomic potential in zinc. Using relaxed structures, the parameters are fitted to the lattice parameters, the elastic constants and the vacancy formation energy. The total energy calculation predicts the stability of the h.c.p. structure. The potential is used to calculate the energy of some extended defects: the basal stacking fault and two twin boundaries.

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