Curated list of known efforts in materials informatics, i.e. in modern materials science
-
Updated
Mar 24, 2026
Curated list of known efforts in materials informatics, i.e. in modern materials science
Reproduction of CGCNN for predicting material properties
mechanoChemML library
Utilities for ab initio modeling suite CRYSTAL, developed in Turin University
Code implementation of PolyCL
A "sky-scanner" Optimade browser-only GUI
A suite of scripts and modules that perform menial, tedious and repetitive tasks and operations on VASP files that were hurriedly and haphazardly put together by some intern.
Tools for handling Wannier models with a spin operator, calculating the Wannier model quality and spin-texture plotting.
The optical properties of 2D materials with the VASP code
Basin-Hopping Monte Carlo (BHMC) algorithm coupled with density functional theory (Quantum espresso) package for unbiased global optimization of clusters and nanoparticles
Build layered VASP inputs and analyze electron localization and bonding in layered materials.
End-to-end Machine Learning pipeline for developing Moment Tensor Potentials (MTP) for Tungsten and GaAs using mlip-3, Quantum Espresso and LAMMPS
Agent-native provenance, safety gates, and handoff for computational research with MCP, VASP, CP2K, LAMMPS, and HPC.
Automate input setup for CALYPSO structure searches, including configurable two-dimensional searches.
Cost-bounded quantum-mechanical discovery, ASE supercell modeling, and Ferritic Nitrocarburizing (FNC) kinetic solver for anti-fretting bearing steel (NITRO_BRG_ALLOY_000). Features VASP DFT elastic relaxation, Chromium-trapping diffusion kinetics, and thermo-mechanical stress/EHL permutation testing. Developed with Google Gemini co-pilot support.
Local FastAPI workbench for preparing, reviewing, and launching VASP materials-science workflows.
Dataset of sodium-ion battery cathode candidate materials generated from Materials Project structures with estimated electrochemical properties (capacity, voltage, and energy density) for machine learning–based inverse design and screening.
Generative inverse design of Li–P–S solid-electrolyte candidates: MatterGen → self-consistent MLIP stability screen (S.U.N.) → conductivity ranking. Concept validation.
Computational engine mapping sub-atomic vector states to macro-scale material properties for inorganic alloy screening and bio-organic hydrogel synthesis.
Data-driven analysis of steel microstructure and hardness using Python and computational metallurgy concepts.
To associate your repository with the computational-materials topic, visit your repo's landing page and select "manage topics."