Abstract: 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.

Info: Common workflows for computing material properties using different quantum engines, S.P. Huber, E. Bosoni, M. Bercx, J. Bröder, A. Degomme, V. Dikan, K. Eimre, E. Flage-Larsen, A. Garcia, L. Genovese, D. Gresch, C. Johnston, G. Petretto, S. Poncé, G. Rignanese, C. J. Sewell, B. Smit, V. Tseplyaev, M. Uhrin, D. Wortmann, A. V. Yakutovich, A. Zadoks, P. Zarabadi-Poor, B. Zhu, N. Marzari & G. Pizzi, npj Computational Materials volume 7, Article number: 136 (2021) | DOI: 10.1038/s41524-021-00594-6 | Open Access

Discover our INTERSECT publications, and register to our newsletter to stay up-to-date with our progress!

The BigDFT project started in 2005 with the aim of testing the advantages of using a Daubechies wavelet basis set for Kohn–Sham DFT with pseudopotentials. This project led to the creation of the BigDFT code, which employs a computational approach with optimal features of flexibility, performance, and precision of the results. BigDFT is an electronic structure pseudopotential code that employs Daubechies wavelets as a computational basis, designed for usage on massively parallel architectures.

The BigDFT package has been used in production for eight years, mainly in the domain of structure prediction calculations. Among the various actions, the entire code package has been restructured and redesigned such as to be distributed as a collection of independent pieces of software, packaged in separated modules, some of which have already been used and linked in third party software, with MaX flagship codes Quantum ESPRESSO and SIESTA among them.

The MaX webinar will show how the localized description of the KS problem, emerging from the features of the basis set, is helpful in providing a simplified description of large-scale electronic structure calculations. During the presentation, the webinar will highlight how the MaX consortium enabled the possibility of the implementation of advanced functionalities in the context of pre-exascale computing. One of the contributions, by A. Degomme, will also focus on “Software approach of BigDFT: from modularization to containers. AiiDA workflows with PyBigDFT“.

The target of the webinar is composed by Computational Physicists, Quantum chemists, Material Scientists. Anyone interested in the a uncommon usage of DFT calculations. Info and registration at http://www.max-centre.eu/webinar/flexibilities-wavelets-electronic-structure-calculations-large-systems.

Abstract: A review of the present status, recent enhancements, and applicability of the SIESTA program is presented. Since its debut in the mid-1990s, SIESTA’s flexibility, efficiency, and free distribution have given advanced materials simulation capabilities to many groups worldwide. The core methodological scheme of SIESTA combines finite-support pseudo-atomic orbitals as basis sets, norm-conserving pseudopotentials, and a realspace grid for the representation of charge density and potentials and the computation of their associated matrix elements. Here, we describe the more recent implementations on top of that core scheme, which include full spin–orbit interaction, non-repeated and multiple-contact ballistic electron transport, density functional theory (DFT)+U and hybrid functionals, time-dependent DFT, novel reduced-scaling solvers, density-functional perturbation theory, efficient van der Waals non-local density functionals, and enhanced molecular-dynamics options. In addition, a substantial effort has been made in enhancing interoperability and interfacing with other codes and utilities, such as WANNIER90 and the second-principles modeling it can be used for, an AiiDA plugin for workflow automatization, interface to Lua for steering SIESTA runs, and various post-processing utilities. SIESTA has also been engaged in the Electronic Structure Library effort from its inception, which has allowed the sharing of various low-level libraries, as well as data standards and support for them, particularly the PSeudopotential Markup Language definition and library for transferable pseudopotentials, and the interface to the ELectronic Structure Infrastructure library of solvers. Code sharing is made easier by the new open-source licensing model of the program. This review also presents examples of application of the capabilities of the code, as well as a view of on-going and future developments.

SIESTA is a first-principles materials simulation program based on density-functional theory (DFT), and is is both a method and its computer program implementation, to perform efficient electronic structure calculations and ab initio molecular dynamics simulations of molecules and solids. As you may already know, our Interoperable Material-to-Device simulation platform (IM2D) will integrate Quantum ESPRESSO and SIESTA, some of the most used open-source materials modelling codes, with models and modelling software for emerging devices (GinestraTM) via the SimPhony infrastructure for semantic interoperability and ontologies, powered by the AiiDA workflow engine, and its data-on-demand capabilities and apps interface.

Info & Download: https://doi.org/10.1063/5.0005077