Use of simulations to predict material properties, a publication on npf Computational Materials, with the collaboration of the Theory and Simulation Research Unit at ICMAB, published on npj Computational Materials.
Using electronic-structure simulations based on density-functional theory to predict material properties has become routine, thanks at least in part to an ever-widening choice of increasingly robust simulation packages. This wide selection of codes and methods allows for cross-verification, useful in ascertaining accuracy and reliability. But the wide range of methods, algorithms and paradigms available make it difficult for non-experts to select or efficiently use any one for a given task.
In the paper “Common workflows for computing material properties using different quantum engines,” published in npj Computational Materials, a team of researchers in the MaX CoE, including ICMAB Researchers Emanuele Bosoni, Vladimir Dikan and Alberto García, from the Theory and Simulation Research Unit, showed how the development of common interfaces for workflows that automatically compute material properties can address these challenges and demonstrate the approach with an implementation involving 11 different simulation codes.
Also thanks to the use of the AiiDA workflow engine, they guarantee reproducibility of the simulations, simplify interoperability and cross-verification, and open up the use of quantum engines to a wider range of researchers.
Read the full press release published by Carey Sargent at the NCCR Marvel at EPFL, which highlights the article "Common workflows for computing material properties using different quantum engines". Th publication tackles the complications of choosing, using, and mastering different simulation softwares that have, at the moment, no unified interface for the different codes used.
Common workflow for the geometrical optimization of a structure or a molecule. The common interface allows non-experts to run the relaxation with any of the 11 quantum codes involved in the project after choosing few simple and general inputs. At the same time, the interface retain full flexibility for code experts in changing all the simulation parameters.
Common workflows for computing material properties using different quantum engines
Sebastiaan P. Huber, Emanuele Bosoni, Marnik Bercx, Jens Bröder, Augustin Degomme, Vladimir Dikan, Kristjan Eimre, Espen Flage-Larsen, Alberto Garcia, Luigi Genovese, Dominik Gresch, Conrad Johnston, Guido Petretto, Samuel Poncé, Gian-Marco Rignanese, Christopher J. Sewell, Berend Smit, Vasily Tseplyaev, Martin Uhrin, Daniel Wortmann, Aliaksandr V. Yakutovich, Austin Zadoks, Pezhman Zarabadi-Poor, Bonan Zhu, Nicola Marzari & Giovanni Pizzi
npj Comput Mater 2020, 7, 136, 10.1038/s41524-021-00594-6
The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification.
We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.