Alternatives and similar repositories for SuperalloyDigger

Users that are interested in SuperalloyDigger are comparing it to the libraries listed below

• ruihwang / MOF-CGCNN
  We developed a novel method, MOF-CGCNN, to efficiently and accurately predict the methane the volumetric uptakes at 65 bar for MOFs. Two …
  ☆19Updated 3 years ago
• tobacco-mofs / tobacco_3.0
  ☆54Updated 4 years ago
• Sangwon91 / PORMAKE
  Python library for the construction of porous materials using topology and building blocks.
  ☆68Updated 3 weeks ago
• vxfung / MatDeepLearn_DOS
  MatDeepLearn for DOS prediction
  ☆24Updated 2 years ago
• simonverret / materials_data_api_scripts
  scripts to load all data from ICSD, Materials Project, and OQMD
  ☆61Updated 2 years ago
• SeyedMohamadMoosavi / tools-cp-porousmat
  Heat capacity predictor for porous materials
  ☆12Updated last year
• danieleongari / CURATED-COFs
  Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs
  ☆38Updated last year
• snurr-group / mofid
  A system for rapid identification and analysis of metal-organic frameworks
  ☆57Updated 6 months ago
• olivettigroup / table_extractor
  Extracts tables into json format from HTML/XML files
  ☆37Updated 5 years ago
• kaist-amsg / Synthesizability-PU-CGCNN
  ☆31Updated 3 years ago
• PV-Lab / FTCP
  FTCP code
  ☆34Updated last year
• Wang-Group / Machine-learning-for-Cu-CO2RR
  This is the Python code and original data of "Machine-Learning Guided Discovery and Optimization of Additives in Preparing Cu Catalyst fo…
  ☆7Updated 2 years ago
• lipelopesoliveira / pyCOFBuilder
  A package for Covalent Organic Frameworks structure assembly based on specific building block, topology and functional groups based on th…
  ☆54Updated last month
• Tsotsalas-Group / MOF_Literature_Extraction
  ☆30Updated 3 years ago
• aimat-lab / MOF_Synthesis_Prediction
  ☆36Updated 3 years ago
• tongzhugroup / mddatasetbuilder
  A script to build reference datasets for training neural network potentials from given LAMMPS trajectories.
  ☆40Updated this week
• michaeldalverson / CrysTens
  ☆26Updated 10 months ago
• hspark1212 / MOFTransformer
  Universal Transfer Learning in Porous Materials, including MOFs.
  ☆103Updated last year
• kmcos / kmcos
  Kinetic Monte Carlo of Systems (KMCOS): lattice based kinetic Monte Carlo with a python front-end and Fortran back-end.
  ☆22Updated this week
• atomly-materials-research-lab / GPTFF
  GPTFF allowing anyone to directly download and run the AI model in an out-of-the-box manner
  ☆55Updated 3 months ago
• Yeonghun1675 / L2M3
  Large Language Models Material Miner
  ☆32Updated 4 months ago
• CMMRLab / LUNAR
  ☆40Updated last week
• usccolumbia / AlphaCrystal
  AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction
  ☆11Updated last year
• ulissigroup / vasp-interactive
  ☆67Updated 2 years ago
• Matgenix / pysisso
  Python interface to the SISSO (Sure Independence Screening and Sparsifying Operator) method.
  ☆54Updated last year
• core-cof / CoRE-COF-Database
  ☆54Updated last year
• hyllios / CGAT
  Crystal graph attention neural networks for materials prediction
  ☆27Updated last year
• CompRhys / roost
  Representation Learning from Stoichiometry
  ☆59Updated 2 years ago
• SarkisovGitHub / PoreBlazer
  PoreBlazer (v4.0) source code, examples, and geometric properties of porous materials calculated for the subset of 12,000 structures from…
  ☆53Updated last year
• cyye001 / Con-CDVAE
  This is a conditionally generative model for crystal structures based on a modified version of CDVAE.
  ☆31Updated 2 weeks ago