/tools

DFT-D4 is a software tool that provides a generally applicable atomic-charge dependent London dispersion correction for quantum chemistry calculations. It allows users to perform dispersion-related calculations and access results through various APIs, making it useful for molecular property predictions and simulations.

geomeTRIC is a geometry optimization code that facilitates the optimization of molecular structures using various quantum chemistry and molecular mechanics software. It supports multiple external quantum chemistry packages and provides a command line interface for executing optimizations.

QCEngine is a tool designed for executing quantum chemistry calculations and standardizing input/output formats through QCSchema. It allows users to compute molecular properties and perform energy calculations using various quantum chemistry methods.

SO3LR is a pretrained machine-learned force field for molecular simulations that integrates neural network-based interactions with universal pairwise force fields. It supports various molecular dynamics simulations and geometry optimizations, making it a valuable tool for computational chemistry applications.

QUICK is an open-source software package designed for ab initio quantum chemistry calculations, utilizing GPU acceleration for efficient electronic structure calculations. It supports various methods including Hartree-Fock and density functional theory, and is capable of performing geometry optimizations and QM/MM simulations.

The SPICE dataset is a collection of quantum mechanical data aimed at training potential functions for simulating drug-like small molecules interacting with proteins. It includes a wide range of chemical space and conformations, making it a valuable resource for molecular machine learning applications.

The Basis Set Exchange repository is a library that contains a curated database of quantum chemistry basis sets. It allows users to obtain and manipulate basis set data, which is crucial for performing accurate quantum chemistry calculations.

tblite is a light-weight framework designed for tight-binding quantum chemistry calculations. It allows users to perform single-point energy calculations and provides a high-level interface for manipulating parametrization data, making it useful for molecular property predictions.

Neural-Network-Models-for-Chemistry is a repository that provides a variety of neural network models aimed at advancing computational chemistry. It includes methods for quantum chemistry, force fields, and molecular simulations, facilitating the prediction of molecular properties and behaviors.

QCElemental is a Python library that offers data structures for quantum chemistry, including a periodic table and physical constants. It also includes functionalities for parsing molecules, making it useful for various molecular chemistry applications.

The Molecular Design Toolkit is a Python library that facilitates molecular modeling by integrating simulation, visualization, and analysis tools. It allows users to work with various molecular types and perform tasks such as geometry optimization and 3D visualization in Jupyter notebooks.

MOPAC is a molecular orbital package that allows for quantum mechanical calculations of molecules and materials. It is designed for high-throughput calculations and is useful in both educational and research settings for predicting molecular properties.

sGDML is a reference implementation of the Symmetric Gradient Domain Machine Learning model, aimed at constructing accurate molecular force fields. It facilitates atomistic simulations and predictions of molecular properties, making it a valuable tool in computational chemistry.

Fermi.jl is a quantum chemistry program written in Julia that implements various post Hartree-Fock methods for energy computations and molecular property predictions. It is designed for high-performance calculations in computational quantum chemistry.

QCFractal is a distributed compute and database platform that facilitates the execution and management of large-scale quantum chemistry calculations. It allows computational chemists to store, retrieve, and analyze extensive datasets generated from quantum chemistry computations.

IOData is a Python library that facilitates the input and output of quantum chemistry file formats, enabling users to generate input files for various computational chemistry applications. It serves as a valuable tool for researchers working in molecular simulations and related fields.

PyQuante2 is an open-source suite for developing quantum chemistry methods, allowing scientists to construct their own quantum chemistry programs. It includes various integral methods and wave function calculations, making it relevant for molecular property predictions and simulations.

p4vasp is a visualization tool for VASP (Vienna Ab initio Simulation Package) outputs, facilitating the analysis of quantum mechanical and molecular dynamics simulations. It provides a graphical interface and command-line utilities for users to interact with simulation data effectively.

Psiflow is a scalable molecular simulation engine designed for chemistry and materials science applications. It facilitates complex molecular simulations using quantum mechanical calculations and supports a variety of sampling algorithms, allowing users to define and execute intricate workflows efficiently.

Tangelo is an open-source Python package that facilitates end-to-end chemistry workflows on quantum computers. It supports the design of quantum experiments and integrates with various quantum chemistry packages, making it suitable for molecular simulations and drug discovery applications.

MLatom is a Python package designed for atomistic simulations that integrates machine learning with quantum chemical methods. It supports various functionalities including molecular dynamics, geometry optimization, and the prediction of molecular properties using advanced AI models.

Pysisyphus is a Python suite designed for exploring potential energy surfaces in both ground and excited states. It provides methods for searching stationary points and calculating minimum energy paths, making it a valuable tool for molecular simulations and quantum chemistry workflows.

This repository provides a collection of interactive Jupyter notebooks focused on quantum mechanics and computational materials science. It includes tutorials on molecular dynamics and other related concepts, making it a useful educational tool for understanding molecular behavior and simulations.

MolGym is a tool that utilizes reinforcement learning to design molecules in three-dimensional space, guided by principles of quantum mechanics. It allows users to train agents to build molecular structures by placing atoms on a canvas, facilitating the generation and optimization of new molecular designs.