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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

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Published on: July 25, 2013

First principles prediction of amorphous phases using evolutionary algorithms.

Suhas Nahas¹, Anshu Gaur¹, Somnath Bhowmick¹

¹Department of Material Science and Engineering, Indian Institute of Technology, Kanpur 208016, India.

The Journal of Chemical Physics

|July 11, 2016

Summary

An evolutionary method effectively simulates amorphous solid structures, matching results from traditional ab initio molecular dynamics (MD) for amorphous silicon and indium gallium zinc oxide.

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Area of Science:

Materials Science
Computational Chemistry
Condensed Matter Physics

Background:

Current methods for analyzing amorphous solids, such as ab initio molecular dynamics (MD) melt-quench, are deterministic.
These deterministic approaches have been successful in studying amorphous materials.

Purpose of the Study:

To evaluate the efficacy of an evolutionary method for the structural analysis of amorphous solids.
To demonstrate a stochastic approach, inspired by Darwinian evolution, as an alternative simulation technique.
To re-investigate amorphous silicon and indium gallium zinc oxide using this evolutionary method.

Main Methods:

Employing an evolutionary algorithm combined with density functional theory (DFT) for electronic, ionic, and cell relaxation.
Simulating the structures of amorphous silicon and indium gallium zinc oxide.

Main Results:

The evolutionary method successfully simulated amorphous structures.
Characteristic structural parameters, including average bond length and bond angle, were calculated.
Results closely aligned (within ~2%) with established ab initio MD calculations and experimental data.

Conclusions:

The evolutionary method is a viable and effective approach for the structural analysis of amorphous solids.
This stochastic method provides an alternative to deterministic techniques like ab initio MD.
The findings validate the evolutionary approach for studying complex amorphous materials.