Back to Search
Start Over
Developing empirical potentials from ab initio simulations: The case of amorphous silica
- Source :
- Computational Materials Science, Computational Materials Science, Elsevier, 2016, 124, pp.323-334. ⟨10.1016/j.commatsci.2016.07.041⟩
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- We discuss two procedures to obtain empirical potentials from ab initio trajectories. The first method consists in adjusting the parameters of an empirical pair potential so that the radial distribution functions extracted from classical simulations using this potential match the ones extracted from the ab initio simulations. As a case study, we consider the example of amorphous silica, a material that is highly relevant in the field of glass science as well as in geology. With our approach we are able to obtain an empirical potential that gives a better description with respect to structural and thermodynamic properties than the potential proposed by van Beest, Kramer, and van Santen, and that has been very frequently used as a model for amorphous silica. The second method is the so-called “force matching” approach proposed by Ercolessi and Adams to obtain an empirical potential. We demonstrate that for the case of silica this method does not yield a reliable potential and discuss the likely origin for this failure.
- Subjects :
- Yield (engineering)
Materials science
General Computer Science
Field (physics)
Ab initio
General Physics and Astronomy
02 engineering and technology
01 natural sciences
Empirical potential
Force matching
Computational chemistry
0103 physical sciences
General Materials Science
[PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]
Statistical physics
010306 general physics
Silica
General Chemistry
Radial distribution
021001 nanoscience & nanotechnology
Structure of glass
Computational Mathematics
Mechanics of Materials
[PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci]
Amorphous silica
0210 nano-technology
Pair potential
Computer simulations
Subjects
Details
- ISSN :
- 09270256
- Volume :
- 124
- Database :
- OpenAIRE
- Journal :
- Computational Materials Science
- Accession number :
- edsair.doi.dedup.....85169630cae09cc94c389562371b1dd5