AiiDA
Automated Interactive Infrastructure and Database for Computational Science

AiiDA is a flexible and scalable informatics' infrastructure to manage, preserve, and disseminate the simulations, data, and workflows of modern-day computational science. Able to store the full provenance of each object, and based on a tailored database built for efficient data mining of heterogeneous results, AiiDA gives the user the ability to interact seamlessly with any number of remote HPC resources and codes, thanks to its flexible plugin interface and workflow engine for the automation of complex sequences of simulations.

Journal ref: G. Pizzi, A. Cepellotti, R. Sabatini, N. Marzari, and B. Kozinsky, AiiDA: automated interactive infrastructure and database for computational science, Comp. Mat. Sci. 111, 218-230 (2016)

Open access link: arXiv:1504.0116

Posts

Nature Nanotechnology March cover features a high-throughput study on novel 2D materials performed using AiiDA

👤 🕔 March 6, 2018 Comments Off on Nature Nanotechnology March cover features a high-throughput study on novel 2D materials performed using AiiDA

The March 2018 issue of Nature Nanotechnology features a paper by N. Mounet and coworkers who have used AiiDA to identify  close to 2000 well-known inorganic compounds that may be exfoliated into novel 2D materials and compute, for a large subset of over 250 of them, their electronic, vibrational, magnetic and topological properties.

Copyright: Image: Giovanni Pizzi, EPFL, Switzerland.


The paper has been also highlighted in a few feature stories, including the homepage of the EPFL website and on the MARVEL website.

Full journal reference: Nicolas Mounet et al., Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds, Nature Nanotech. 13, 246–252 (2018) doi:10.1038/s41565-017-0035-5

Computed data is available in open access, including full AiiDA provenance, on the Materials Cloud website: Nicolas Mounet et al., Materials Cloud Archive (2017), doi: 10.24435/materialscloud:2017.0008/v1