Scientific Python package for solving Slater Koster tight-binding topological hamiltonian

Julia implementation of algorithm for counting primitive rings in an atomistic structure. Useful for materials simulations

The Otago Research Genetic Algorithm for Nanoclusters, Including Structural Methods and Similarity (Organisms) program is a genetic algorithm designed to globally optimise nanoclusters (also known as clusters or nanoparticles)

Python class to interface with QUESTAAL Quantum codes which is a suite of electronic structure programs.

This module includes functions that can be used to simulate mechanochemical phenomena. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001436

Fork of ASE https://gitlab.com/ase/ase with added support for performing Koopmans functional calculations with Quantum ESPRESSO

This repository contains wrapper scripts for running transition state and IRC (Intrinsic Reaction Coordinate) calculations using Sella and IRC ASE optimizers for the Sella package.

This repository contains scripts to test the performance of different path optimization appraches to compute transition states and the minimum energy paths.

Density functional theory (DFT)-based Genetic algorithm (GA) code for structural optimization of supported nanoparticle model in a queueing system

ASE-based code to globally optimize the atomic configuration of a bulk bimetallic material.

Interfacing Fortnet with the Atomic Simulation Environment

This repository contains examples of genetic algorithm optimisations using the Organisms program that can be run on Jupyter. This can be run either on your computer or live on the web through Binder

GUI tool to run NEB calculation using ASE and Gaussian16 or XTB binary.