Computational study of structural and elastic properties of random AlGaInN alloys

Physics – Condensed Matter – Materials Science

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

In this work we present a detailed computational study of structural and elastic properties of cubic AlGaInN alloys in the framework of Keating valence force field model, for which we perform accurate parametrization based on state of the art DFT calculations. When analyzing structural properties, we focus on concentration dependence of lattice constant, as well as on the distribution of the nearest and the next nearest neighbour distances. Where possible, we compare our results with experiment and calculations performed within other computational schemes. We also present a detailed study of elastic constants for AlGaInN alloy over the whole concentration range. Moreover, we include there accurate quadratic parametrization for the dependence of the alloy elastic constants on the composition. Finally, we examine the sensitivity of obtained results to computational procedures commonly employed in the Keating model for studies of alloys.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Computational study of structural and elastic properties of random AlGaInN alloys does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Computational study of structural and elastic properties of random AlGaInN alloys, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Computational study of structural and elastic properties of random AlGaInN alloys will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-706577

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.