The MAterials Simulation Toolkit (MAST) for atomistic modeling of defects and diffusion

Mayeshiba, Tam; Wu, Haonan; Angsten, Thomas; Kaczmarowski, Amy; Song, Zhewen; Jenness, Glen R.; Xie, Wei

doi:10.1016/j.commatsci.2016.09.018

Cited by 38 publications

(17 citation statements)

References 33 publications

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“…All DFT calculations were performed using the Vienna Ab initio Simulation Package (VASP) . To efficiently manage the large number of calculations in this study, the MAST software package was used . The wavefunctions were modeled using a planewave basis set.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, we have used high‐throughput DFT methods enabled by the Materials Simulation Toolkit (MAST) to simulate and screen a total of 1845 different halide perovskite compositions in search of nontoxic, stable, and high‐efficiency solar cell materials. Additional information on the different composition spaces that we explored is provided in Section S1 of the Supporting Information, and a complete list of all materials is provided in the spreadsheet as part of the Supporting Information and available on Figshare (see link in the section summarizing the Supporting Information).…”

Section: Introductionmentioning

confidence: 99%

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Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High‐Efficiency Solar Cells

Jacobs

Luo

Morgan

2019

Adv Funct Materials

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Two critical limitations of organic-inorganic lead halide perovskite materials for solar cells are their poor stability in humid environments and inclusion of toxic lead. In this study, high-throughput density functional theory (DFT) methods are used to computationally model and screen 1845 halide perovskites in search of new materials without these limitations that are promising for solar cell applications. This study focuses on finding materials that are comprised of nontoxic elements, stable in a humid operating environment, and have an optimal bandgap for one of single junction, tandem Si-perovskite, or quantum dot-based solar cells. Single junction materials are also screened on predicted single junction photovoltaic (PV) efficiencies exceeding 22.7%, which is the current highest reported PV efficiency for halide perovskites. Generally, these methods qualitatively reproduce the properties of known promising nontoxic halide perovskites that are either experimentally evaluated or predicted from theory. From a set of 1845 materials, 15 materials pass all screening criteria for single junction cell applications, 13 of which are not previously investigated, such as (CH 3 NH 3 ) 0.75 Cs 0.25 SnI 3 , ((NH 2 ) 2 CH) Ag 0.5 Sb 0.5 Br 3 , CsMn 0.875 Fe 0.125 I 3 , ((CH 3 ) 2 NH 2 )Ag 0.5 Bi 0.5 I 3 , and ((NH 2 ) 2 CH) 0.5 Rb 0.5 SnI 3 . These materials, together with others predicted in this study, may be promising candidate materials for stable, highly efficient, and nontoxic perovskite-based solar cells.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High‐Efficiency Solar Cells

Jacobs

Luo

Morgan

2019

Adv Funct Materials

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“…The convergence tests for these values can be found in previous work [5]. The high-throughput workflow software MAterials Simulation Toolkit (MAST) [35] developed at University of Wisconsin-Madison based on the pymatgen toolset [36] was utilized to automate the workflows of all the calculations.…”

Section: Computational Detailsmentioning

confidence: 99%

First-principles investigation on diffusion mechanism of alloying elements in dilute Zr alloys

Zou

et al. 2018

Acta Materialia

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Impurity diffusion in Zr is potentially important for many applications of Zr alloys, and in particular for their use of nuclear reactor cladding. However, significant uncertainty presently exists about which elements are vacancy vs. interstitial diffusers, which can inhibit understanding and prediction of their behavior under different temperature, irradiation, and alloying conditions. Therefore, first-principles calculations based on density functional theory (DFT) have been employed to predict the temperature-dependent dilute impurity diffusion coefficients for 14 substitutional alloying elements in hexagonal closed packed (HCP) Zr. Vacancy-mediated diffusion was modeled with the eight-frequency model. Interstitial contributions to diffusion are estimated from interstitial formation and select migration energies. Formation energies for each impurity in nine high-symmetry interstitial sites were determined, including significant effects of thermal expansion. The dominant diffusion mechanism of each solute in HCP Zr was identified in terms of the calculated vacancy-mediated activation energy, lower and upper bounds of interstitial activation energy, and the formation entropy, suggesting a rough relation with the metallic radii of solutes. It is predicted that Cr, Cu, V, Zn, Mo, W, Au, Ag, Al, Nb, Ta and Ti all diffuse predominantly by an interstitial mechanism, while Hf, Zr, and Sn are likely to be

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“…With the advent of materials informatics toolkits and software enabling the development of high‐throughput (HT) screening workflows, HT periodic density functional theory (DFT) has been used to construct databases of electronic, energetic, and structural properties for hundreds of thousands of inorganic materials from first‐principles calculations . Metal–organic frameworks (MOFs), a novel class of highly porous crystalline materials, are well‐suited for computational screening studies due to the modular nature of their inorganic nodes and organic linkers .…”

Section: Introductionmentioning

confidence: 99%

Identifying promising metal–organic frameworks for heterogeneous catalysis via high‐throughput periodic density functional theory

2019

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Metal–organic frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chemical composition and topology. Due to their tunable nature, high‐throughput computational screening is a particularly appealing method to reduce the time‐to‐discovery of MOFs with desirable physical and chemical properties. In this work, a fully automated, high‐throughput periodic density functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof‐of‐concept, we use the high‐throughput workflow to screen MOFs containing open metal sites (OMSs) from the Computation‐Ready, Experimental MOF database for the oxidative C—H bond activation of methane. The results from the screening process suggest that, despite the strong C—H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc.

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The MAterials Simulation Toolkit (MAST) for atomistic modeling of defects and diffusion

Cited by 38 publications

References 33 publications

Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High‐Efficiency Solar Cells

Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High‐Efficiency Solar Cells

First-principles investigation on diffusion mechanism of alloying elements in dilute Zr alloys

Identifying promising metal–organic frameworks for heterogeneous catalysis via high‐throughput periodic density functional theory

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