Open Science @ THEOS


Marco Borelli (EPFL)
Andrea Cepellotti (EPFL)
Fernando Gargiulo (EPFL)
Dominik Gresch (ETHZ)
Rico A. Häuselmann (EPFL)
Sebastiaan P. Huber (EPFL)
Leonid Kahle (EPFL)
Boris Kozinsky (Bosch & Harvard University)
Snehal Kumbhar (EPFL)
Antimo Marrazzo (EPFL)
Nicola Marzari (EPFL)
Andrius Merkys (Vilnius University)
Nicolas Mounet (EPFL)
Elsa Passaro (EPFL)
Giovanni Pizzi (EPFL)
Gianluca Prandini (EPFL)
Thomas Schulthess (CSCS)
Ole Schütt (Empa)
Berend Smit (EPFL)
Leopold Talirz (EPFL)
Iurii Timrov (EPFL)
Martin Uhrin (EPFL)
Joost VandeVondele (CSCS)
Aliaksandr Yakutovich (EPFL)
Spyros Zoupanos (EPFL)


The objective of the Open Science platform is to develop robust "turn key" solutions for predicting materials properties. Such effort automatically makes it possible to offer core capabilities open to the community at large – fellow computational scientists, experimental groups, national laboratories, companies.

The two core components of Open Science are AiiDA, which is used as the “operating system”, and Materials Cloud which is the dissemination portal and cloud simulation platform, organized around the 5 sections of Learn, Work, Discover, Explore and Archive.

Moreover, we also work on the development of open-source simulation codes for materials, as well as on the generation of curated datasets (like the curated SSSP pseudopotential library) that are essential for the implementation of automated “turn-key” materials simulation workflows.

  • AiiDA ( In recent years, there has been a great increase in the performance and capabilities of computers. Materials science has greatly benefited from this computational boom, which is continuously boosting research, the discovery of new materials and the development of simulation codes. The "materials by design" approach has become very powerful, but requires running large numbers of simulations and building databases of computed properties. A key challenge is the need to automatically prepare, execute and monitor workflows of calculations, and then retrieve and store the results in a format that is easy to browse and query. The AiiDA open-source platform provides researchers with a tool that fulfills those requirements, by implementing the four “ADES” pillars of Automation, Data, Environment and Sharing. AiiDA is continuously being developed and has matured into an ecosystem with multiple backend options for increased performance and flexibility, a powerful graph querying tool for easy result analysis, a redesigned plugin system to simplify external user contributions, new more powerful and easy to write workflows, and a continuous integration system to ensure the stability of the platform.
  • Materials Cloud ( Materials Cloud, a new web platform developed to help computational materials scientists share their work and promote open science, can also offer advantages to industrial partners. With five sections — Learn, Work, Discover, Explore and Archive — the platform allows the seamless sharing of resources such as learning materials, interactive tools, virtual hardware, curated and raw data as well as the actual calculations underlying published results. While academic researchers are using it to render their scientific data complete, fully downloadable, easy to browse and ready to reuse, industrial partners are starting to use Materials Cloud to, for instance, keep track of, reproduce and visualize workflows. Materials Cloud leverages the power of AiiDA for workflow management, provenance tracking, and interaction with HPC resources, and uses various technologies such as JupyterHub and Docker to enable the creation of interactive discovery and research tools.
  • Open-source simulation software: We work on the development, dissemination, and training in open-source simulation tools: some of us work on the development of open-source electronic structure codes, as co-developers of the Quantum ESPRESSO effort (; see also; and authors and members of the Wannier90 developers group (; just in 2017, ~2000 papers were published worldwide using Quantum-ESPRESSO, and ~430 papers using Wannier90 (Google Scholar).
  • SSSP (A curated library of pseudopotentials on Materials Cloud): We developed a protocol to test publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state (delta-test) and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure of elemental crystals. Adopting these criteria we obtained two curated pseudopotential libraries (named SSSP or Standard Solid-State Pseudopotential libraries) for 85 elements of the periodic table, that are tailored for high-throughput materials screening and high-precision materials modelling. All the calculations needed for this work (more than 50'000 DFT and DFPT calculations) were performed in an automated fashion through the AiiDA infrastructure for computational science, with the goal of ensuring full reproducibility of the obtained results. The complete SSSP testing protocol is implemented as an AiiDA workflow, called SsspWorkflow, that can run all the convergence tests and the delta-factor verification tests. AiiDA also allows straightforward dissemination of these results through the Materials Cloud web platform.