MGEdata / SuperalloyDigger
The functions of superalloyDigger toolkit include batch downloading documents in XML and TXT format from the Elsevier database, locating target sentences from the full text and automatically extracting triple information in the form of <material name, property specifier, value>.
☆55Updated this week
Alternatives and similar repositories for SuperalloyDigger:
Users that are interested in SuperalloyDigger are comparing it to the libraries listed below
- We developed a novel method, MOF-CGCNN, to efficiently and accurately predict the methane the volumetric uptakes at 65 bar for MOFs. Two …☆18Updated 3 years ago
- MatDeepLearn for DOS prediction☆24Updated 2 years ago
- Extracts tables into json format from HTML/XML files☆35Updated 4 years ago
- ☆53Updated 4 years ago
- Python library for the construction of porous materials using topology and building blocks.☆66Updated 4 months ago
- FTCP code☆34Updated last year
- 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
- ☆30Updated 3 years ago
- A system for rapid identification and analysis of metal-organic frameworks☆53Updated 5 months ago
- A package for Covalent Organic Frameworks structure assembly based on specific building block, topology and functional groups based on th…☆53Updated last week
- Examples demonstrating how to reproduce the results in the paper.☆57Updated 6 months ago
- Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs☆37Updated last year
- Heat capacity predictor for porous materials☆12Updated 10 months ago
- The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.☆143Updated 2 months ago
- PoreBlazer (v4.0) source code, examples, and geometric properties of porous materials calculated for the subset of 12,000 structures from…☆52Updated last year
- Crystal Edge Graph Attention Neural Network☆21Updated 10 months ago
- AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction☆10Updated last year
- Universal Transfer Learning in Porous Materials, including MOFs.☆96Updated 10 months ago
- ☆54Updated last year
- ☆67Updated 2 years ago
- ☆30Updated 3 years ago
- BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…☆81Updated 4 months ago
- Tool for the canonicalization of Polymer SMILES (P🙂) strings☆23Updated 8 months ago
- Codes for text-mined solid-state reactions dataset☆75Updated last year
- updated constant potential plugin for LAMMPS☆39Updated 2 years ago
- A toolkit featured artificial intelligence × ab initio for computational chemistry research.☆67Updated last week
- ☆43Updated 2 years ago
- Python library for generation of MOFs, COFs, Zeolites...☆29Updated 3 years ago
- ☆91Updated 4 months ago
- Machine-Learning-Based Interatomic Potentials for Catalysis: an Universal Catalytic Large Atomic Model☆32Updated 3 months ago