All software
CP2K
CP2K is a quantum chemistry and solid state physics software package running on graphics processing units and thousands of processing units. It is open-source and allows simulations, spectroscopy, vibrational analysis and energy minimization on a vast variety of theory levels.
- electronic structure
- GPU
- High performance computing
- + 5
- Fortran
- C
- Python
- + 12
MercuryDPM
MercuryDPM is an open-source C++ framework for discrete particle simulations of granular materials, powders, and other particulate systems. It was started in 2009 to support complex scientific and industrial particle simulations. MercuryDPM is developed by an international open-source community.
- Computational Granular Mechanics
- Discrete Element Method
- Discrete Particle Method
- + 3
ILTpy
ILTpy is a python library for performing regularized inversion of one-dimensional or multi-dimensional data without non-negativity constraint. Primary applications include magnetic resonance (NMR, EPR), and electrochemical impedance spectroscopy (distribution of relaxation times; DRT).
- Distribution of Relaxation times
- DRT
- EPR
- + 7
- Python
- HTML
PeCon.py
PeCon.py is a Python-Software, that enables the calculation of the ionic and electronic conductivities of Perovskite-type ceramic materials, i.e. the conductivities within oxygen-transport ceramic membranes.
- Energy
- MTET
- open source
- + 1
GOAC
Global Optimization of Atomistic Configurations by Coulomb
- Energy
- Modeling
- MTET
- + 1
- Fortran Free Form
- Python
JuMPER
JuMPER (Jülich open access Modelling Platform for Electrochemistry Research) is a collaborative platform designed for modelling and analyzing electrochemical processes. It supports open access research on electrochemical devices, including fuel cells, electrolyzers and batteries.
- Energy
- open source
- python
micromechanics-indentationGUI
Graphical User Interface (GUI) software for analyzing nanoindentation experimental data
- Data analysis
- Data Visualization
- Energy
- + 5
- Python
UTILE-Oxy
Automated workflow using deep learning for the analysis of videos containing oxygen bubbles in PEM electrolyzers: 1. preparing annotated dataset and training models to conduct semantic seg- mentation of bubbles and 2. automating the extraction of bubble properties for further distribution analysis.
- bubbles
- Data analysis
- Data Visualization
- + 7
- Python
- Jupyter Notebook