material-science
There are 5 repositories under material-science topic.
- Language:Fortran 1016
rouyang2017 / SISSO
A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.
Language:Fortran 340- Language:Jupyter Notebook 255
boschresearch / pylife
a general library for fatigue and reliability
Language:Python 169dftfeDevelopers / dftfe
DFT-FE: Real-space DFT calculations using Finite Elements
Language:C++ 151scikit-learn-contrib / scikit-matter
A collection of scikit-learn compatible utilities that implement methods born out of the materials science and chemistry communities
Language:Python 88- mdapy
mushroomfire / mdapy
A simple and fast python library to handle the data generated from molecular dynamics simulations
Language:Python 85 - Language:Fortran 65
- Language:Python 64
- Language:Python 61
- Fierro
lanl / Fierro
Fierro is a C++ code designed to aid the research and development of numerical methods, testing of user-specified models, and creating multi-scale models related to quasi-static solid mechanics and compressible material dynamics using low- and high-order meshes.
Language:C++ 57 - Language:Python 39
pylada / pylada-light
A physics computational framework for python and ipython
Language:Python 38- Language:Python 33
- Language:Python 29
mcsorkun / V2DB
V2DB (Virtual 2D Materials Database): the code for generating and predicting the novel 2D materials by virtual screening.
Language:Python 22mdavezac / Crystals.jl
Atomic crystal structures for Julia
Language:Julia 20alesgenova / pbcpy
Python package providing some useful tools when dealing with molecules and materials under periodic boundary conditions and uniform grids. This is a mirror of https://gitlab.com/ales.genova/pbcpy
Language:Python 19Neelfrost / microstructure-mas
Microstructure Modeling and Simulation. Generate microstructures using site-saturation condition, and simulate grain growth using Monte Carlo Potts Model.
Language:Python 18Gressling / examples
Examples for the book 'Data Science in Chemistry', ISBN: 978-3-11-062939-2, Published: 23 Nov 2020
Language:Jupyter Notebook 16nlesc-nano / swan
Statistical models to predict new materials
Language:Python 14romankempt / hetbuilder
Builds 2D heterostructures via coincidence lattice theory.
Language:Python 14BlueQuartzSoftware / simplnx
The backend algorithms and framework associated with DREAM3DNX, a data analysis program for materials science data analytics
Language:C++ 12- cp-pawLanguage:Fortran 11
cakshat / MatSci-LLM-Agents
Agentic framework combining the power of LLMs with domain-specific tools for materials science, enabling property extraction, simulations, and crystal structure generation to accelerate innovative material design and analysis.
Language:Jupyter Notebook 10materials-commons / materialscommons.org
The Materials Commons website
Language:JavaScript 10ealcobaca / mlglass
We share in this repository some codes and data used during our research about glass property prediction and the design of new glasses.
Language:Jupyter Notebook 9mlacs-developers / mlacs
A python library for machine-Learning assisted canonical sampling
Language:Python 9odarbelaeze / vegas-lattice-rs
Lattice generator library and tool in rust.
Language:Rust 9OpenChemistry / materialsdatabank
An information portal for 3D atomic electron tomography data
Language:JavaScript 8MehrdadJalali-AI / LLM-ELN
Integrating LLMs with ELNs to transform materials science research at KIT, enhancing data management and accelerating scientific innovation.
Language:Jupyter Notebook 7idaholab / PANDA
This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training.
Language:Jupyter Notebook 6KIST-CSRC / DenseSSD
Machine vision for vial positioning detection toward the safe automation of material synthesis
Language:Python 6marcosdelcueto / MachineLearning_AcceptorDonor
Code allows the use of different machine learning methods to predict efficiency of organic photovoltaics using different descriptors
Language:Python 6MolarVerse / PQAnalysis
PQAnalysis is a API/CLI python package for the analysis of MD simulations
Language:Python 6vijaypurohit / wien2k
This provides the files needed and detailed process (instructions) to install the wien2k 14.2 in Linux.
Language:Shell 6
