materials-discovery

🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.

Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

An evaluation framework for machine learning models simulating high-throughput materials discovery.

LLM-powered agents for scientific research automation

Generate random alloys and compute various properties

Representation Learning from Stoichiometry

A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.

Predict materials properties using only the composition information!

Vote on whether you think predicted crystal structures could be synthesised

Data-driven risk-conscious thermoelectric materials discovery

Quantum-inspired Cluster Expansion: formulating chemical space search as QUBOs and Ising models

Additive Manufacturing Mapping of Compositional Spaces with Thermodynamic, Analytical, and Artificial Intelligence Models

Examples of using the Novel Materials Discovery (NOMAD) database, especially downloading all chemical formulas.

Thermodynamics and phase stability of multicomponent alloys using conventional and enhanced sampling techniques applied to the Bragg–Williams Hamiltonian

Eight one-line laws that judge whether an inorganic crystal structure is physicochemically plausible and name the mechanism that fails when it is not. Discovered by autonomous agents that proposed, tested and refuted two million candidates, and cheap enough to screen a generator's output before any DFT.

Isomorphic TypeScript / JavaScript client to aggregate all the official Optimade providers

Using Bayesian optimization via Ax platform + SAASBO model to simultaneously optimize 23 hyperparameters in 100 iterations (set a new Matbench benchmark).

closed loop materials discovery using error correction learning

Evolutionary algorithm for development of glassy alloy materials

Optimize and deploy ALCHEMI models on NVIDIA NIM model serving platform