zincware / ZnDraw
Display and Edit Molecules (https://zndraw.icp.uni-stuttgart.de)
☆41Updated this week
Alternatives and similar repositories for ZnDraw:
Users that are interested in ZnDraw are comparing it to the libraries listed below
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics☆56Updated this week
- Compute neighbor lists for atomistic systems☆53Updated 2 weeks ago
- Training and evaluating machine learning models for atomistic systems.☆31Updated this week
- python workflow toolkit☆39Updated 2 months ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆80Updated 2 weeks ago
- ☆21Updated last year
- ⚛ download and manipulate atomistic datasets☆44Updated 4 months ago
- A fully featured ASE calculator for xTB☆18Updated 6 months ago
- An ecosystem for digital reticular chemistry☆48Updated 7 months ago
- ☆19Updated last month
- ☆25Updated 6 months ago
- Computing representations for atomistic machine learning☆71Updated last week
- Quick Uncertainty and Entropy via STructural Similarity☆39Updated this week
- A post-processing engine for particle simulations☆40Updated last week
- ☆25Updated last year
- Particle-mesh based calculations of long-range interactions in PyTorch☆47Updated last week
- A high-performance software package for training and evaluating machine-learned XC functionals using the CIDER framework☆12Updated last week
- ☆11Updated this week
- ☆15Updated this week
- WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions☆32Updated last year
- Library for Crystal Symmetry in Rust☆49Updated this week
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆35Updated last week
- Chemical intuition for surface science in a package.☆26Updated 2 weeks ago
- Some tutorial-style examples for validating machine-learned interatomic potentials☆34Updated last year
- Tools for machine learnt interatomic potentials☆28Updated last week
- an interface to semi-empirical quantum chemistry methods implemented with pytorch☆50Updated this week
- Python package to interact with high-dimensional representations of the chemical elements☆42Updated this week
- A framework for performing active learning for training machine-learned interatomic potentials.☆34Updated last month
- Basis set optimization library for quantum chemistry☆34Updated last year
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆22Updated last week