Graphene-Based Nanomaterials - www.introductiontographene.org https://introductiontographene.org Fri, 05 Jun 2015 13:19:00 +0000 en-US hourly 1 https://wordpress.org/?v=4.1.42 Before new year’s break https://introductiontographene.org/before-2014-new-years-break/ https://introductiontographene.org/before-2014-new-years-break/#comments Sun, 21 Dec 2014 20:13:37 +0000 http://www.introductiontographene.org/?p=450 This has been a hectic year full of great discoveries and developments in the field of graphene and other 2D materials. But now we wanted to propose our readers to take a breath and make a ludic stop.

Following Symmetry Magazine we are proposing to turn into the art of cutting paper snowflakes. These are not, however, ordinary snowflakes, they feature Paul Dirac and six Dirac cones!

Dirac-snowflakes-introductiontographene.org

You will need scissors (a cutter may also help) and to print the pdf attached to this post.

Download the pdf file with the instructions and get started.

Thanks for keeping with us throughout the year. We wish you a great 2015!

The authors.

]]> https://introductiontographene.org/before-2014-new-years-break/feed/ 0 Stephan’s recursion methods https://introductiontographene.org/stephans-recursion-methods/ https://introductiontographene.org/stephans-recursion-methods/#comments Sun, 08 Jun 2014 19:23:14 +0000 http://www.introductiontographene.org/?p=354 One of the most efficient methods available for computing the Density of States (DoS) and the transport properties, specially in samples containing a large number of atoms, is the recursion method explained in Appendix D of “Introduction to Graphene-based Nanomaterials”. Here we provide (by courtesy of Stephan Roche) a numerical code written in fortran and implementing this method for graphene and carbon nanotubes.

To get your link to download the code with Stephan’s recursion methods please send an email containing a proof of ownership of your book (invoice, photo with your book, or equivalent) to introductiontographene at gmail.com

]]> https://introductiontographene.org/stephans-recursion-methods/feed/ 0 Recursive Green’s functions and self-energies https://introductiontographene.org/recursive-greens-functions-and-self-energies/ https://introductiontographene.org/recursive-greens-functions-and-self-energies/#comments Sun, 08 Jun 2014 19:11:14 +0000 http://www.introductiontographene.org/?p=347 Here we provide a simple fortran 90 code that implements the recursive Green’s functions techniques for calculating the self-energy of a semi-infinite lead as described in Appendix C of “Introduction to Graphene-Based Nanomaterials”. To call this routine you must provide an array with matrices containing the hoppings between the layers as well as the diagonal block matrices of the Hamiltonian.

This should serve to give you an idea of a possible implementation. Of course, this can also be done in Python for example (if you are interested just drop a line to Luis Foa Torres).

selfenergy.f90 (click to download)

]]> https://introductiontographene.org/recursive-greens-functions-and-self-energies/feed/ 0 ABINIT input files for graphene nanoribbons https://introductiontographene.org/abinit-input-files/ https://introductiontographene.org/abinit-input-files/#comments Sun, 08 Jun 2014 18:41:05 +0000 http://www.introductiontographene.org/?p=341 ABINIT input files for armchair and zigzag graphene nanoribbons (by courtesy of Jean-Christophe Charlier). These inputs allow to calculate the structural and electronic properties of these GNRs (including spin-polarization in the zigzag case due to the potential magnetization at the edges). The PAW pseudopotentiels for carbon and hydrogen are also included.

agnr.in
zgnr.in
1h-gga-uspp.paw
6c-gga-uspp.paw

 

]]> https://introductiontographene.org/abinit-input-files/feed/ 0 Python packages for graphene-based materials and beyond https://introductiontographene.org/python-packages-for-graphene-based-materials-and-beyond/ https://introductiontographene.org/python-packages-for-graphene-based-materials-and-beyond/#comments Sat, 07 Jun 2014 23:00:09 +0000 http://www.introductiontographene.org/?p=377 Python is one of the most versatile languages for coding. It allows fast coding of complex algorithms and the community working with Python is growing at a fast pace.

Here we recommend two packages written for python:

  • PythTB: Python Tight-Binding is a package developed at Rutgers University by the group of David Vanderbilt. It allows to compute the electronic structure and topological properties of nanomaterials (1d, 2d or 3d) in an elegant way.
  • Kwant: The kwant package was released in late 2013 and offers a very nice platform for computing the transport properties of nanodevices. Kwant harnesses the power of MUMPS for solving sparse systems of equations. We encourage you to contribute to this initiative for the benefit of the whole community.

We will post a few examples of different calculations carried with both packages. If you have any suggestions please feel free to write me a few lines!

Independently of that, we suggest you to make your own experience by coding from scratch any of the methods described in the book. You can take advantage of the hints in the forthcoming posts.

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