Keywords
Institutes
AFLOW-pi
Duke University

With AFLOWπ we introduce a minimalist framework for high-throughput first principles calculations that it easy to install and operate. The key components involve robust data generation, real time feedback and error control, curation and archival of the data, and post-processing tools for analysis and visualization. AFLOWπ simplifies the process of …

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  • United States
  • Datasets
  • Year 2020
  • minimalist framework for high-throughput first principles calculations
AFLOW Superalloys search
Duke University

Compound-forming ternary combinations

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  • United States
  • Datasets
  • Year 2020
  • superalloys
AFLOW-CHULL
Duke University

AFLOW-CHULL

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  • United States
  • Datasets
  • Year 2020
  • hull
AFLOW-online tools structure comparison
Duke University

AFLOW.org HOMECONSORTIUMPUBLICATIONSFORUMSRCSEARCH AFLOW Online Submit Reset Input Input StructuresInput PARTCAR EXAMPLE POSCAR -122.124500 0.000 1.000 1.000 1.000 0.000 1.000 1.000 1.000 0.000 1 7 Direct(8) 0.000 0.000 0.000 Cu 0.500 0.000 0.000 Pt 0.000 0.500 0.000 Pt 0.000 0.000 0.500 Pt 0.000 0.500 0.500 Pt 0.500 0.000 0.500 Pt 0.500 …

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  • United States
  • Datasets
  • Year 2020
  • x-ray diffractionK-pointscoordinationstructure comparison
AFLOW-CHULL
Duke University

AFLOW-CHULL

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  • United States
  • Datasets
  • Year 2020
  • hull
AFLOW prototype encyclopedia
Duke University

The AFLOW standard encyclopedia of crystallographic prototypes provides a complete description of each structure, including formulas for the primitive vectors, basis vectors, and AFLOW commands to generate the standardized cells. Electronic structure geometry files are available to download in both CIF and POSCAR formats. Number of prototypes in the encyclopedia: …

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  • United States
  • Datasets
  • Year 2020
  • crystallographic prototypes
AFLOW ML machine learning predictor
Duke University

Property Labeled Material Fragments (PLMF) Predicts the electronic and thermomechanical properties of a crystal. Molar Fragment Descriptor (MFD) Predicts the vibrational free energies (Fvib) and entropies (Svib) of a crystal. AFLOW Superconductor (ASC) Classifies a material as a superconductor and predicts the critical temperature (TC).

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  • United States
  • Datasets
  • Year 2020
  • electronic and thermomechanicalvibrational free energiesentropiessuperconductorcritical temperature
AFLOW Thermal property search
Duke University

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data-driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first-principles calculations and provides tools for data verification and dissemination for a broad …

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  • United States
  • Datasets
  • Year 2020
  • thermal conductivity
AFLOW Elastic property search
Duke University

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data-driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first-principles calculations and provides tools for data verification and dissemination for a broad …

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  • United States
  • Datasets
  • Year 2020
  • elasticity
AFLOW MendelIB search
Duke University

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data-driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first-principles calculations and provides tools for data verification and dissemination for a broad …

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  • United States
  • Datasets
  • Year 2020
  • Lithium-ion battery materials