Details

Autor(en) / Beteiligte

• Youn, Yong
• Lee, Miso
• Hong, Changho
• Kim, Doyeon
• Kim, Sangtae
• Jung, Jisu
• Yim, Kanghoon
• Han, Seungwu

Titel

AMP2: A fully automated program for ab initio calculations of crystalline materials

Ist Teil von

• Computer physics communications, 2020-11, Vol.256, p.107450, Article 107450

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Ab initio calculations based on the density functional theory (DFT) become a vital tool in material science for understanding and predicting material properties. However, DFT calculations involve several parameters and procedures that call for deep understanding on underlying theories and preceding knowledge on certain properties of target materials. Such technicalities cost a significant amount of human time and expose practitioners to mistakes. Here, we introduce a fully automated package for DFT calculations, automated ab initio modeling of materials property package (AMP2), which aims to produce key DFT properties of crystalline materials with essentially no user intervention except for initial structural information. This is achieved through algorithms that automatically determine various technical parameters and make self-decisions during computational workflow. As results, AMP2 is material-agnostic and provides a highly accurate band structure, band gap, effective mass, density of states and dielectric constant for the given material. Notably, the package finds the antiferromagnetic ground state by applying a genetic algorithm to effective Ising models. AMP2 also addresses band-gap underestimation in semilocal functionals with help of a hybrid functional, thereby producing a more accurate band gap, even if the material turns out to be metallic within the semilocal functional. We believe that the present package will significantly expand usage of DFT calculations by making them more accessible. Program Title: AMP2 CPC Library link to program files: http://dx.doi.org/10.17632/5rdw9jv5vp.1 Licensing provisions: GPLv3 Programming language: Python Nature of problem: Conducting abinitio calculation under a fully automated protocol to obtain crystalline properties Solution method: Construct workflow to estimate material properties using the density functional theory. Ising model and genetic algorithm are used for identifying magnetic spin ordering.