Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
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Updated
Jul 13, 2024 - Jupyter Notebook
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
An evaluation framework for machine learning models simulating high-throughput materials discovery.
Representation Learning from Stoichiometry
The Wren sits on its Roost in the Aviary.
Generate random alloys and compute various properties
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
Vote on whether you think predicted crystal structures could be synthesised
Predict materials properties using only the composition information!
Data-driven risk-conscious thermoelectric materials discovery
Examples of using the Novel Materials Discovery (NOMAD) database, especially downloading all chemical formulas.
Quantum-inspired Cluster Expansion: formulating chemical space search as QUBOs and Ising models
Isomorphic TypeScript / JavaScript client to aggregate all the official Optimade providers
Evolutionary algorithm for development of glassy alloy materials
Using Bayesian optimization via Ax platform + SAASBO model to simultaneously optimize 23 hyperparameters in 100 iterations (set a new Matbench benchmark).
Tool to search vast areas of chemical space for magnesium dissolution modulators.
closed loop materials discovery using error correction learning
MSc research project on application of Quality-Diversity algorithms for crystal structure prediction
Capstone project for my Master's degree. In it, I developed some machine learning models to predict the heat of formation for materials containing 1–3 components.
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