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@aced-differentiate

Accelerated Computational Electrochemical-systems Discovery

This is the GitHub organization for the ARPA-E DIFFERENTIATE award with Carnegie Mellon University (lead), Julia Computing, Citrine Informatics, MIT.

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  1. EquivariantOperators.jl EquivariantOperators.jl Public

    Julia 19

  2. DeepUncertainty.jl DeepUncertainty.jl Public

    Uncertainty quantification for Deep Learning models in Julia.

    Julia 8

  3. auto_cat auto_cat Public

    Tools for automated structure generation of catalyst systems

    Python 4

  4. MHC_DOS MHC_DOS Public

    Generalized MHC kinetics for electrochemical interfaces.

    Jupyter Notebook 3 3

  5. GeometricFlux.jl GeometricFlux.jl Public

    Forked from FluxML/GeometricFlux.jl

    Geometric Deep Learning for Flux

    Julia 2

  6. dftparse dftparse Public

    Forked from CitrineInformatics/dftparse

    Simple parsers for DFT codes

    Python 2

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