Fork of ASE https://gitlab.com/ase/ase with added support for performing Koopmans functional calculations with Quantum ESPRESSO
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Updated
Jun 18, 2024 - Python
Fork of ASE https://gitlab.com/ase/ase with added support for performing Koopmans functional calculations with Quantum ESPRESSO
This repository contains scripts to test the performance of different path optimization appraches to compute transition states and the minimum energy paths.
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.
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)
Julia implementation of algorithm for counting primitive rings in an atomistic structure. Useful for materials simulations
Density functional theory (DFT)-based Genetic algorithm (GA) code for structural optimization of supported nanoparticle model in a queueing system
Scientific Python package for solving Slater Koster tight-binding topological hamiltonian
Interfacing Fortnet with the Atomic Simulation Environment
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
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
ASE-based code to globally optimize the atomic configuration of a bulk bimetallic material.
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