Daresbury Laboratory, UK, 13-17 May 2019
Daresbury: Leon Petit, Jerome Jackson, Martin Lüders
King’s College London: Mark van Schilfgaarde, Dimitar Pashov
The third Questaal school concentrated on qsGW and DMFT using the code’s new interface to the TRIQS library. A series of tutorials enabled the 31 participants (mostly post-doctoral researchers and lecturers) to setup and run calculations starting from density functional theory and working up to GW, qsGW, LDA + Bethe Salpeter (BSE), or the inclusion of ladder diagrams in W: qsGW^BSE, and DMFT. The participants were encouraged to experiment with a diverse range of materials, including itinerant magnets, f-electron systems, simple semiconductors and strongly correlated insulators.
In addition to the new TRIQS DMFT capability, the school also showcased recent developments in extending the GW self-energy by including phonon contributions and the first results of the new “Jigsaw Puzzle Orbital” basis, which is a full-potential analogue of the LMTO screening transformation which is short ranged and compact while still very precise. Continue reading 3rd Daresbury QUESTAAL School
Workshop on Crystal Structure Prediction: Exploring the Mendeleev Table as a Palette to Design New Materials
ICTP, Trieste, 14-18 January 2019
Thanks to enormous progress in computing power and in algorithm development, we are now closer to being able to predict the crystal structure of any material from the simple knowledge of its composition. This is the first necessary step for predicting in silico the property of a material, and planning modifications that could improve these properties. A critical discussion of the algorithms developed in the last years for the “in silico” prediction of crystal structures was the main theme of a workshop that took place at the Abdus Salam International Centre for Theoretical Physics (ICTP), in Trieste, Italy, from 14 to 18 January 2019. The event, titled “Workshop on Crystal Structure Prediction: Exploring the Mendeleev Table as a Palette to Design New Materials”, focused in particular on approaches based on molecular modeling and was an opportunity to celebrate 2019 as the International Year of the Periodic Table, since crystal structure prediction is rooted in a deep knowledge of the properties of the atoms, and, in turn, numerous discoveries made with the help of crystal structure prediction, reveal new (often completely unexpected) sides of the behavior of the atoms. The Workshop was directed by the A. Laio, G. Desiraju, A. Oganov, and S. Scandolo. It was divided in two parts: the first three days were dedicated to an in-depth and critical discussion of the methods, with talks given by world experts in the field. The last two days were devoted to “hands-on” computer labs were the younger participants were given the opportunity to learn how to use the most advanced codes for crystal structure prediction, including the “Universal Structure Predictor: Evolutionary Xtallography” (USPEX) and the “Ab initio Random Structure Searching” (AIRSS). Continue reading Report on Workshop on Crystal Structure Prediction: Exploring the Mendeleev Table as a Palette to Design New Materials
EPFL (Lausanne, Switzerland), May 21-24, 2019
Today, many open questions in computational science call for more than individual computations using a single code. As the demand for integration and throughput increases, the skill of writing robust and reproducible workflows is becoming ever more important. In this context, the move towards open science raises the level of scrutiny and demands that workflows be recorded in a way that can be inspected and reused by scientific peers.
This hands-on tutorial introduced young researchers to writing reproducible computational workflows using the open-source AiiDA framework for workflow management and provenance tracking (http://www.aiida.net), complemented by invited talks from experts in the field that highlight the power and the challenges involved with leveraging complex workflows in computational materials science.
Continue reading Writing reproducible workflows for computational materials science