LAMMPS is a classical molecular dynamics code with a focus on materials modeling.

Questions related to the GULP materials science software. GULP is a lattice dynamics package for the fitting of force fields and calculation of materials properties.

Discuss the Materials Project, its website, data and infrastructure. The Materials Project is funded by the US Department of Energy, Basic Energy Sciences and additional partners.

Questions related to the OVITO application software and the corresponding Python package. OVITO is a data visualization and analysis solution for particle-based simulations.

The Open Databases Integration for Materials Design (OPTIMADE) consortium aims to make materials databases interoperational by developing a common REST API.

The Atomic Simulation Environment (ASE) is a set of tools and Python
modules for setting up, manipulating, running, visualizing and
analyzing atomistic simulations. The code is freely available under
the GNU LGPL license. ASE provides interfaces to different codes
through Calculators which are used together with the central Atoms
object and the many available algorithms in ASE.

Questions related to the matminer, automatminer, matbench and figrecipes materials data mining packages.

Questions related to the pymatgen materials analysis code. Bug reports should go directly to the GitHub Issues page.

Discussion and questions related to the Open Knowledgebase of Interatomic Models (OpenKIM) including the online framework at openkim.org, contributing and using OpenKIM content (interatomic potentials, property calculations (tests), data, visualizers), the KIM API, and related topics. OpenKIM is funded by the US National Science Foundation.

Questions related to the amset electronic transport software. Bug reports should go directly to the GitHub Issues page.

Questions related to the Atomate materials science software. Bug reports should go directly to the GitHub Issues page.

The NOMAD Laboratory is a community-effort web-based platform for the FAIR sharing and utilization of materials-science data. It offers cutting-edge tools for collecting, storing, presenting, and analyzing these data.

The Materials Research Data Alliance (MaRDA) is a community-led network focused on connecting and integrating materials research data infrastructure. MaRDA Working Groups (WGs) are intended to accelerate progress in specific ways.

DL_POLY is a general purpose classical molecular dynamics (MD) simulation software developed at Daresbury Laboratory.

The MPDS (project Pauling File) is a commercial provider of the curated materials data of 3 types (crystal structures, phase diagrams, and properties), manually extracted from ~400k scientific publications in materials science (1891—now), cross-checked, and interlinked.

Questions related to the FireWorks high-throughput computing software and rocketsled, an optimization package for FireWorks. Bug reports should go directly to the GitHub Issues page.

General discussion of any topics related to materials science. Ask questions or share new or interesting research, including your own!

Atomly.net is a materials database based on high-throughput first-principles.

Custodian is a simple, robust and flexible just-in-time (JIT) job management framework written in Python. Using custodian, you can create wrappers that perform error checking, job management and error recovery for high-throughput applications.

pyiron is an integrated development environment (IDE) for computational materials science. It enables scientists to upscale their workflows from rapid prototyping to high performance computing.

Questions about the Matscholar website, Matscholar API, and mat2vec for data mining the scientific literature of materials with natural language processing (NLP).

hiPhive — High-order force constants for the masses

IFermi is a Python library for the generation, analysis and, visualisation of Fermi surfaces and slices.

exciting is an all-electron, full-potential computer package for first-principles calculations, based on (linearized) augmented planewave + local orbital (L)APW+lo methods. This family of basis sets is known as the most precise numerical scheme to solve the Kohn-Sham equations of density-functional theory (DFT), reaching up to micro-Hartree precision.

JARVIS infrastructure provides computational tools and databases to automate materials design using density functional theory, machine learning and classical force-field methods.