Band structure simulation using Snider program

In summary, the conversation is about someone seeking help with using Gregory Snider's 1D Schrodinger/Poisson solver for simulations of a quantum well. They are having trouble modulating the density and band structure, and the program overestimates the density in the well. Suggestions are given for other solvers, such as Siesta and Quantum Espresso, which are commonly used in similar fields.
  • #1
drummerguy
3
0
Does anyone have any experience using Gregory Snider's 1D Schrodinger/Poisson solver? I'm trying to do some simulations of a quantum well my group is studying, and I'm not sure if I'm doing something wrong or if the code is buggy or if I'm just interpreting the results incorrectly. Here's the code I'm running:

surface
GaAs t=100.00 dy=10
AlGaAs t=1000.00 dy=10 x=0.16
algaas x=.16 t=10 Na=1.00000E+20 dy=10
AlGaAs t=800.00 dy=10 x=0.16
GaAs t=200.00 dy=10
AlGaAs t=20000.00 dy=10 x=0.16
GaAs t=10000.00 dy=10
substrate schottky v1

v1 10
fullyionized
schrodingerstart=10
schrodingerstop=32000.000000
temp=.3K
dy=10


The problem I'm having is that by changing the voltage v1 on the substrate I'm not able to modulate the density in the well at all (and the band structure doesn't change noticeably either). I've tried doing this with his included quantum well file and I am able to modulate the density and band structure significantly. Does this program just not work well for thick layers? (His quantum well example has much thinner layers). The program also overestimates the density in the well significantly (it says the density is of the order of 10^16 cm^-2 while our the density measured in the actual device was around 10^10 cm^-2). Anyone have any suggestions or know of any other solvers?
 
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  • #2
I'm sorry I don't have any direct experience of Gregory Snider's 1D Schrodinger/Poisson solver. However, I can suggest some other solvers that may be useful for your simulations. Some popular ones are the Siesta and Quantum Espresso packages. The Siesta package is a full-potential electronic structure code that uses linear-scaling techniques to reduce computational cost. The Quantum Espresso package is a suite of codes for performing electronic structure calculations and molecular dynamics simulations. Both of these packages are widely used in the quantum chemistry and condensed matter physics fields.
 

Related to Band structure simulation using Snider program

1. What is the Snider program used for?

The Snider program is a computer software used for simulating the band structure of materials. It is commonly used in the field of condensed matter physics and materials science.

2. How does the Snider program work?

The Snider program uses a combination of theoretical models and numerical calculations to simulate the electronic band structure of materials. It takes into account factors such as crystal structure, electronic interactions, and external fields to predict the behavior of electrons in a material.

3. What types of materials can be studied with the Snider program?

The Snider program can be used to study a wide range of materials, including metals, semiconductors, insulators, and even exotic materials such as topological insulators. It is also capable of simulating multi-layered materials and heterostructures.

4. What are the advantages of using the Snider program for band structure simulation?

The Snider program offers several advantages over other band structure simulation methods. It is user-friendly, efficient, and can handle complex systems. It also allows for the incorporation of external factors such as strain and electric fields, making it a versatile tool for studying the electronic properties of materials.

5. Are there any limitations to the Snider program?

Like any simulation program, the Snider program has its limitations. It relies on theoretical models, which may not fully capture the complexity of real materials. It also has a limited ability to accurately predict the behavior of materials under extreme conditions, such as high temperatures or pressures. Therefore, it is important to validate the results of the simulation with experimental data.

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