User applications driven by the community contribution framework MPContribs in the Materials Project

Huck, P.; Gunter, Dan; Cholia, Shreyas; Winston, Donald; N’Diaye, Alpha T.; Persson, Kristin A.

doi:10.1002/cpe.3698

Cited by 22 publications

(16 citation statements)

References 17 publications

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“…In this first stage, we aim to provide tools for efficient manual data inspection. For instance, a separate "staging" area for data contributions is already in place [26] and allows for human verification before release on the live web site. Further, our integration of the plotting tool Plotly quickly reveals incorrect data such as outliers.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, XMCD signals resulting from the XAS spectra can be overlaid with the corresponding theoretical phase diagrams calculated by MP, providing a unified view of experiment and theory. The workflow of this Unified Theoretical and Experimental xray Spectroscopy Application in addition to MPContribs' role in the Nanoporous Materials Explorer are discussed in [26]. Note that such dedicated analysis applications within MPContribsUsers also drive the feedback loop of derived data back into the core and contribution collections.…”

Section: Collaborative Extension: Mpcontribsusersmentioning

confidence: 99%

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A Community Contribution Framework for Sharing Materials Data with Materials Project

Huck

Jain

Gunter

et al. 2015

2015 IEEE 11th International Conference on E-Science

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Abstract-As scientific discovery becomes increasingly datadriven, software platforms are needed to efficiently organize and disseminate data from disparate sources. This is certainly the case in the field of materials science. For example, Materials Project has generated computational data on over 60,000 chemical compounds and has made that data available through a web portal and REST interface. However, such portals must seek to incorporate community submissions to expand the scope of scientific data sharing. In this paper, we describe MPContribs, a computing/software infrastructure to integrate and organize contributions of simulated or measured materials data from users. Our solution supports complex submissions and provides interfaces that allow contributors to share analyses and graphs. A RESTful API exposes mechanisms for book-keeping, retrieval and aggregation of submitted entries, as well as persistent URIs or DOIs that can be used to reference the data in publications. Our approach isolates contributed data from a host project's quality-controlled core data and yet enables analyses across the entire dataset, programmatically or through customized web apps. We expect the developed framework to enhance collaborative determination of material properties and to maximize the impact of each contributor's dataset. In the long-term, MPContribs seeks to make Materials Project an institutional, and thus community-wide, memory for computational and experimental materials science.

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Section: Discussionmentioning

confidence: 99%

Section: Collaborative Extension: Mpcontribsusersmentioning

confidence: 99%

A Community Contribution Framework for Sharing Materials Data with Materials Project

Huck

Jain

Gunter

et al. 2015

2015 IEEE 11th International Conference on E-Science

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show abstract

“…Automated database development is expected to be minimal and to follow the Materials Project's MPContribs framework. 17…”

Section: Summary and Future Outlookmentioning

confidence: 99%

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

Mayeshiba

Angsten

et al. 2017

Computational Materials Science

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The MAterials Simulation Toolkit (MAST) is a workflow manager and post-processing tool for ab initio defect and diffusion workflows. MAST codifies research knowledge and best--practices for such workflows, and allows for the generation and management of easily modified and reproducible workflows, where data is stored along with workflow information for data provenance tracking. MAST is available for download through the Python Package Index, or at https://pypi.python.org/pypi/MAST, with installation instructions and a detailed user's guide at http://pythonhosted.org/MAST. MAST code may be browsed at the GitHub repository at https://github.com/uw--cmg/MAST.

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“…Steps for further study and insights for design of other functional materials are discussed. Additionally, data from ab initio calculations are made freely available for further analyses via the Materials Project MPContribs Framework 27,28 at https://materialsproject.org/mpcontribs/ScreeningInorganicPV.…”

Section: Introductionmentioning

confidence: 99%

Candidate Inorganic Photovoltaic Materials from Electronic Structure-Based Optical Absorption and Charge Transport Proxies

2019

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Approximately 33,000 valence-precise, ordered, inorganic compounds tabulated in the Inorganic Crystal Structures Database have been screened for their potential as photovoltaic (PV) absorbers. This has been accomplished through the use of proxies for charge carrier mobilities and optical absorption properties from electronic structure calculations, in addition to constraints on thermodynamic stability. Preliminary screening of computed properties tabulated in the Materials Project database, with subsequent high(er)-fidelity electronic structure calculations of optical properties and band gap corrections indicate ≈200 known compounds on or near the convex hull which exhibit Spectroscopic Limited Maximum Efficiency (SLME) in excess of 25 % for a 500 nm thin film, in addition to possessing low effective masses for both electrons and holes. Among the predicted high-performers are nearly all the known commercial inorganic thin-film PV materials as well as several previously unexplored candidates. The new candidates are drawn from a diversity of chemical and structural families, including many chalcogenides and pnictides as well as anti-perovskites, skutterudites, and semiconducting intermetallics. Carrier effective masses, SLME, corrected band gaps, and other relevant information for ≈800 compounds are made available for further analyses via the Materials Project MPContribs Framework. Supporting Information Computed parameters for the ≈800 candidate phases, and further methodological details. Additionally, structured digital datasets of computed absorption spectra, densities of states, SLME, effective masses, and a list of all ≈33,000 phases which were screened are available at https://materialsproject.org/mpcontribs/ScreeningInorganicPV.

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User applications driven by the community contribution framework MPContribs in the Materials Project

Cited by 22 publications

References 17 publications

A Community Contribution Framework for Sharing Materials Data with Materials Project

A Community Contribution Framework for Sharing Materials Data with Materials Project

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

Candidate Inorganic Photovoltaic Materials from Electronic Structure-Based Optical Absorption and Charge Transport Proxies

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