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Aestimo 1.0

Freedownload8 rating:
License:
GPL v3
Added:
Nov 30, -1
Submit date:
Feb 15, 2015
Publisher:
Dr. S. Bora Lisesivdin
File size:
Downloads:
181
 

Aestimo 1.0

by Dr. S. Bora Lisesivdin

Aestimo is an open source and completely free command-line software implemented in Python and created from the ground up to act as an one-dimensional (1D) self-consistent Schrödinger-Poisson solver that can be used for semiconductor heterostructures.

Supports a wide range of alloys and materials

The software was successfully used as a usable co-tool in a scientific and/or educational work environment. It supports a wide range of alloys and materials, among which we can mentiion GaAs, InAs, AlAs, InP, GaP, AlP, AlGaAs, InGaP, AlInP, and InGaAs.

Includes band structure for gamma electrons

Key features include band structure for gamma electrons, as well as for heavy, light and split-off holes, 3x3 k.p method for holes and effective-mass method for electrons, carrier concentrations for heavy, light and split-off holes, as well as for gamma electrons.

In addition, the software comes with an electric field distribution, electron wavefunctions, non-parabolicity, external electric field, strain for valence band calculations, and many other attractive features for your to discover.

Getting started with Aestimo

The software is a bit complicated to use, as it must be used from a console environment, such as a terminal emulator software. Therefore, you must first download the latest release, save the archive on a location of your choice (preferably your Home directory), and uncompress it.

Open a Terminal app, go to the location where you’ve extracted the archive file (e.g. cd /home/softpedia/aestimo_1_0), and run the ‘python aestimo.py --help’ command to view the program’s usage message.

Several samples are provided in the source package

Basically, there’s a single command-line option for the Aestimo software, -i INPUTFILE (usage: aestimo.py --inputfile=INPUTFILE), allowing you to chose the input file to override the default one in config.py. Several samples are provided in the source package, so you can get a taste of what Aestimo can do.

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