myyiqjy / Multi-Objective-Design-of-HEAsLinks
Accelerated design for high entropy alloys based on machine learning and multi-objective optimization
☆11Updated last year
Alternatives and similar repositories for Multi-Objective-Design-of-HEAs
Users that are interested in Multi-Objective-Design-of-HEAs are comparing it to the libraries listed below
Sorting:
- Python interface to the SISSO (Sure Independence Screening and Sparsifying Operator) method.☆62Updated last year
- AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction☆10Updated 2 years ago
- 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
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆41Updated 2 years ago
- Predict materials properties using only the composition information!☆111Updated 2 years ago
- Crystal Edge Graph Attention Neural Network☆23Updated last year
- Crystal graph convolutional neural networks for predicting material properties.☆35Updated 2 years ago
- Automatic generation of crystal structure descriptions.☆125Updated this week
- The functions of superalloyDigger toolkit include batch downloading documents in XML and TXT format from the Elsevier database, locating …☆62Updated 3 months ago
- This is the source code of CubicGAN generating cubic crystal structures using improved WGAN.☆10Updated 3 years ago
- ☆33Updated last year
- Crystal Graph Convolutional Neural Networks tutorial☆28Updated 2 years ago
- ☆107Updated 2 months ago
- MatDesign: a programming-free AI platform to predict and design materials☆75Updated 3 months ago
- ☆62Updated 4 years ago
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆283Updated last month
- This is the code for the paper 'Machine learning-enabled high-entropy alloy discovery'☆76Updated 2 years ago
- CrySPY is a crystal structure prediction tool written in Python.☆140Updated last week
- ☆26Updated last year
- Modules for cross validation, evaluation and plot of SISSO☆16Updated 5 years ago
- Python library for the construction of porous materials using topology and building blocks.☆76Updated 4 months ago
- GPTFF allowing anyone to directly download and run the AI model in an out-of-the-box manner☆64Updated 7 months ago
- DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules☆24Updated 9 months ago
- Repository for links to software packages and databases used in deep-learning applications for materials science☆148Updated 5 months ago
- ☆17Updated 3 years ago
- Composition-Conditioned Crystal GAN pytorch code☆43Updated 3 years ago
- Machine Learning Interatomic Potential Predictions☆93Updated last year
- Universal Transfer Learning in Porous Materials, including MOFs.☆111Updated last year
- MatDeepLearn, package for graph neural networks in materials chemistry☆197Updated 2 years ago
- Heat capacity predictor for porous materials☆12Updated last year