This school will focus on the field of theoretical condensed matter electronic transport exploiting the non-equilibrium Green’s function approach. In particular, recent advances in transport theory  will be presented in the form of lectures and hands-on sessions on hot topics in the field. The teachers will present novel methods used for materials research modelling. The participants will learn the advanced features of SIESTA, such as the calculations of non-equilibrium properties using the TranSIESTA/TBtrans approach and the python framework SISL . For example the school lectures will cover a recent novel scheme introducing truly single-junction transport calculations  and the new implementations to include in the transport calculations different corrections to the Hamiltonian accounting for electron-phonon coupling , spin orbit coupling and electronic correlation. Moreover the users will learn how to extract a tight-binding Hamiltonian from a DFT Hamiltonian allowing them to deal with very large systems [5,6].
We have invited a list of speakers who will present their work in a variety of fields in which the covered tools have been used. Each topic will be addressed through hands-on in which the users can experience how to use these features.
Up to one month before the school, the students are invited to post specific questions on a GitHub repository
were also all the training material will be hosted. Selected questions will be addressed in detail during the last day of the school.
- Advanced usage of SIESTA, TranSIESTA/TBtrans and sisl:
Participants will learn how to use the advanced features implemented in the aforementioned code and python framework. In particular students will be taught how to perform efficient DFT+NEGF calculations, pre-processing, post-processing analysis and data visualization.
First principles simulations are now crucial in many areas of materials science. However, this has not yet reached the field of electrochemistry, where the complexity of the electrochemical environment and the presence of the external electrode potential are difficulties that have precluded direct application of the usual first-principles methods like DFT. We will explain how some of these problems, like the presence of the electrostatic potential, can be tackled using TranSIESTA.
- Topological Insulators
Topological insulators (TI) are a phase of matter characterized by a bulk energy gap and conducting surface (or edge) states symmetry-protected against small perturbations. Quantum transport simulations are crucial to compute and validate the topological properties of materials. We will show how SIESTA can be used to predict the essential features of topological materials, leveraging on the recent Spin-Orbit Coupling implementation and SISL.
- Inelastic transport:
The modelling of inelastic effects due to the electron-phonon coupling in nano-scale devices is of great technological importance as it impacts both the transport properties and Joule heating. It is especially challenging to include the effects in large-scale atomistic first principles device simulations. We will discuss how this can be addressed using various approximations.
- Correlated systems
Electron correlations in magnetic systems are necessary to understand e.g. the Kondo effect in nanostructures. It is of vital importance for predicting spin structures and for future spintronics. System simulations with the Hubbard-U model provides a simple and, yet, often sufficient method in understanding how electron correlations affect magnetism in nanostructures.
- Single contacts by removal of periodic images
Understanding transport properties under non-equilibrium is of vital importance to the development of next-generation electronics. A basic principle of conducting such simulations is by using Bloch’s theorem which has the disadvantage of adding a periodic image of the junction. We will present how users can overcome this limitation and simulate truly single junctions.
- Modelling of extremely large scale systems with DFT precision
Recent increase in compute power is rapidly decreasing the gap between experimental and theoretical works. This allows theoreticians to study one-to-one samples matching an exact experiment. However, there is still some way to go in terms of scalability and precision. Here we present a method to extract the important part of a Hamiltonian in an energy window allowing simulations of transport properties of even larger systems by retaining the band-structure without using any wannierization techniques.