Please cite L. Talirz et al., Sci Data 7, 299 (2020), if you use Materials Cloud in your research.
Materials Cloud is built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.
In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).
The Materials Cloud allows you to share your scientific results to make them:
Materials Cloud is powered by AiiDA, an open-source Python infrastructure to manage and persist the ever-growing amount and complexity of workflows and data in computational science.
The vision for the project nucleated in 2010, with the FET MARVEL Flagship Proposal, and took shape in 2013, with the SNSF MARVEL NCCR, and in 2015, with the H2020 MaX Centre of Excellence.
Today, Materials Cloud is supported by a consortium of partners, including a Go-FAIR implementation network, is a recommended repository of the Swiss National Science Foundation, European Commission through Open Research Europe and of Nature Scientific Data, and remains open to further partnerships.
Materials Cloud supports Open Science and FAIR sharing of research data in the field of Materials Science.
Research data can be made open, findable and accessible by publishing it on Materials Cloud Archive, an open repository for research data that are relevant to computational materials science. Submissions receive persistent DOIs and a guaranteed lifetime of at least 10 years from submission.
In order to support researchers using Materials Cloud in preparing grant proposals, we also provide templates for data management plans (DMPs).
In addition, the entire workflows of calculations, when performed using AiiDA, can also be disseminated in their entirety using the Explore and Discover sections of the Materials Cloud, providing a beyond-FAIR comprehensive release of the simulations with their full provenance, and making entire simulation workflows fully reproducible.
Finally, AiiDA workflows can be run seamlessly in AiiDAlab, a web platform where users can access their personal AiiDA environment in the cloud, and manage workflows through tailored and lightweight web applications, directly in the browser.
Results based on records published on Materials Cloud Archive before Oct 10, 2024
*Structures counted with an automated script, no check for duplicates has been
performed