Giter Site home page Giter Site logo

materialsvirtuallab / matgenb Goto Github PK

View Code? Open in Web Editor NEW
211.0 29.0 140.0 83.93 MB

Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.

License: BSD 3-Clause "New" or "Revised" License

Jupyter Notebook 99.99% Python 0.01%

matgenb's People

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

matgenb's Issues

Notebook for using adsorption.py

Add the tutorial for using adsorption.py from the supplementary material of:

Montoya, J. H., & Persson, K. A. (2017). A high-throughput framework for determining adsorption energies on solid surfaces. Npj Computational Materials, 3(1), 14. https://doi.org/10.1038/s41524-017-0017-z

to matgenb. Will take a pedantic approach to discussing the nuances of modelling adsorption.

Can developers update files?

Hi, I found that pymatgen has changed a lot change-log, which some modules can not be found in the lastest version. May I request developers update the notebook files for convenience?

Request: Notebook demonstrating pymatgen transformations capabillities

Requesting an example notebook of using the transformations framework in pymatgen to create structures with full provenance of how they were generated.

  • using various transformations
  • chaining transformations
  • the one to many concept
  • converting to a SNL
  • embedding provenance for original structure into SNL ( e.g. ICSD, MP, OQMD, etc. IDs and info)

Import Error when using "get_pourbaix_entries"

Using python version 3.7.1 I am trying to use the example for producing pourbaix diagrams.
The first errors I receive when importing the packages and calling "get_pourbaix_entries" are resolved upon recompiling.
ValueError: numpy.ufunc has the wrong size, try recompiling. Expected 192, got 216

I then get the following error upon recompiling the code below:
# Get all pourbaix entries corresponding to the Cu-O-H chemical system.
entries = mpr.get_pourbaix_entries(["Cu"])

ImportError: cannot import name 'LinearAssignment' from 'pymatgen.optimization.linear_assignment' (unknown location)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.