Hostname: page-component-848d4c4894-89wxm Total loading time: 0 Render date: 2024-07-07T13:24:51.231Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  17 March 2011

Anders G. Froseth
Affiliation:
Department of Physics, NTNU, Trondheim, Norway
Peter Derlet
Affiliation:
Present address: Paul Scherrer Institute, Nano-Crystalline Materials Group, Villigen, Switzerland
Ragnvald Hoier
Affiliation:
Department of Physics, NTNU, Trondheim, Norway
Get access

Abstract

Empirical 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.

Type
Research Article
Copyright
Copyright © Materials Research Society 2002

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Cohen, R. E., Mehl, M. J., and Papaconstantopoulos, D. A., Phys. Rev B 50, 14694, 1994 Google Scholar
2. Papaconstantopoulos, D. A., Mehl, M. J., and Pederson, M. R., “Tight-Binding Hamiltonians for Carbon and Silicon, Tight Binding Approach to Computational Materials Science, ed. Turchi, P.E.A, Gonis, A., and Colombo, L., MRS Proceedings 491 (Materials Research Society, Warrendale, PA, 1998)Google Scholar
3. Scheffler, Gross M., Mehl, M. J., and Papaconstantopoulos, D. A., Phys. Rev. Lett. 82, 12091212 (1999)Google Scholar
4. Slater, J. C. and Koster, G. F., Phys. Rev. 94, 1498, 1954 Google Scholar
5. Ingber, A. L., J. Control and Cybernetics, 25, 3354 (1996)Google Scholar
6. Ingber, L., “Adaptive Simulated Annealing (ASA)”, Global Optimization C-code (Caltech Alumni Association, Pasadena, CA, 1993) URL http://www.ingber,com/#ASA-CODEGoogle Scholar
7. , Corona et. al, ACM Transactions on Mathematical Software 13, 262280 (1987)Google Scholar
8. Harrison, W. A., “Electronic Structure and the Properties of Solids” (W. H. Freeman and Company, 1980)Google Scholar
9. Anderson, H. L. ed., A Physicist's Desk Reference, the Second Edition of Physics Vade Mecum (American Institute of Physics, New York, 1989)Google Scholar