Since the rise of nanotechnology increasing efforts have been made to develop material-design strategies directly from the first principles of matter. In particular, the properties of any materials, even the ones that have not been synthesized yet, can be predicted by solving the equations of quantum mechanics. In this talk, I will show how this highly non-trivial task can be pursued using two well known algorithm such as the Fourier transform and the conjugate gradient, in combination with powerful computer clusters. I will also present how this computational techniques can be beneficial to the development of more efficient thermoelectric materials.
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I am computational physicist and PhD candidate at King's College London. My main efforts are currently devoted to development of an HPC software framework to study thermoelectric phenomena in real materials from first-principles. I am also also active in scientific dissemination organizing the Pint of Science festival. Data science, and finance are among my side interests.