Everything you need for quantum hardware engineering in the field. Curated by Onri Jay Benally, an Indigenous American Quantum Hardware Engineer.

Python package to aid materials design and informatics

The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

Comprehensive Linux Basics: A complete guide covering foundational Linux concepts, core tasks, and best practices.

A unified platform for fine-tuning atomistic foundation models in chemistry and materials science

Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c…

An open-source project dedicated to build foundational large language model for natural science, mainly in physics, chemistry and material science.

Online resource for a practical course in machine learning for materials research at Imperial College London (MATE70026)

Tutorials for using the pymatgen library

Code for automated fitting of machine learned interatomic potentials.

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

Active learning workflow with data and task parallelism through MPI

Things that you should (and should not) do in your Materials Informatics research.

Package to perform automatic bonding analysis with the program Lobster in the field of computational materials science and quantum chemistry

A public repository collecting links to state of the art QA and evaluation sets for various ML and LLM applications

Python-based GUI to collect Feedback of Chemist in Molecules

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials …

Application of Large Language Models (LLM) for computational materials science - visit jan-janssen.com/LangSim

This repo contains code and data of our contribution to the 2024 LLM Hackathon, materials' property prediction from textual descriptions of structures and their bonding properties.

Materials for ACerS Automated Experiment Course

A set of tools and structures for modelling perovskite polytypes

Code and Data for "Large Language Models for Inorganic Synthesis Prediction"

Python module for quantum chemistry

a curated list of resources for everyone interested in learning about digital chemistry