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@materialsvirtuallab

Materials Virtual Lab

The Materials Virtual Lab is dedicated to the application of first principles calculations and informatics to accelerate materials design.

The Materials Virtual Lab at the University of California San Diego‘s Department of NanoEngineering is a materials AI group focused on the cross-disciplinary application of materials science, computer science and machine learning to accelerate materials design. We develop cutting-edge software frameworks for automation of calculations, sophisticated data infrastructure for large materials data, and state-of-the-art machine learning models with high predictive accuracy.

Vision

Our vision is to be a world-class computational materials group pioneering the application of informatics techniques in materials study and design.

Mission

  • We develop techniques that effectively integrate materials, computer and information science.
  • We apply cutting-edge computational techniques to gain novel and useful insights into materials design.
  • We build robust open software and data infrastructure for materials analysis.

Values

Integrity

  • We practice integrity in all forms.
  • We are honest and fair to fellow group members and collaborators.
  • We have a zero-tolerance policy towards plagiarism and falsification of results.

Excellence

  • We strive for excellence in everything that we do.
  • We stand by the quality of our science.
  • We aim to develop scientists with great analytical, technical and communication skills.

Teamwork

  • We believe great teamwork is the key to great science.
  • We share and discuss ideas freely.
  • We strive to build great collaborations, both within and outside of the group.
  • We contribute actively to the materials science community.

Pinned

  1. maml maml Public

    Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

    Jupyter Notebook 330 72

  2. matgl matgl Public

    Graph deep learning library for materials

    Python 210 49

  3. pymatgen-analysis-diffusion pymatgen-analysis-diffusion Public

    This add-on to pymatgen provides tools for analyzing diffusion in materials.

    Python 74 51

  4. monty monty Public

    This repository implements supplementary useful functions for Python that are not part of the standard library. Examples include useful utilities like transparent support for zipped files etc.

    Python 65 46

  5. nano281 nano281 Public

    Data Science for Materials Science

    Jupyter Notebook 55 27

  6. nano266 nano266 Public

    Repository for UCSD NANO 266 Quantum Mechanical Modelling of Materials

    Python 19 21

Repositories

Showing 10 of 33 repositories
  • flamyngo Public

    Flask frontend for MongoDB

    Python 15 BSD-3-Clause 7 0 0 Updated Apr 25, 2024
  • monty Public

    This repository implements supplementary useful functions for Python that are not part of the standard library. Examples include useful utilities like transparent support for zipped files etc.

    Python 65 MIT 46 6 4 Updated Apr 25, 2024
  • maml Public

    Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

    Jupyter Notebook 330 BSD-3-Clause 72 6 8 Updated Apr 25, 2024
  • pymatgen-analysis-diffusion Public

    This add-on to pymatgen provides tools for analyzing diffusion in materials.

    Python 74 BSD-3-Clause 51 6 4 Updated Apr 22, 2024
  • matgl Public

    Graph deep learning library for materials

    Python 210 BSD-3-Clause 49 5 3 Updated Apr 18, 2024
  • matcalc Public

    A python library for calculating materials properties from the PES

    Python 41 BSD-3-Clause 10 0 0 Updated Apr 12, 2024
  • matgenie Public

    Web interface to pymatgen

    Python 4 1 0 2 Updated Apr 8, 2024
  • nano266 Public

    Repository for UCSD NANO 266 Quantum Mechanical Modelling of Materials

    Python 19 BSD-3-Clause 21 0 0 Updated Mar 14, 2024
  • nano281 Public

    Data Science for Materials Science

    Jupyter Notebook 55 BSD-3-Clause 27 0 1 Updated Feb 21, 2024
  • Jupyter Notebook 0 BSD-3-Clause 1 0 1 Updated Feb 21, 2024

People

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