chemiscope

Chemiscope is a tool for interactive exploration of databases of materials and molecules, correlating local and global structural representations with the properties of the systems. Chemiscope files can be viewed online, generated using a python library and used inside jupyter notebooks or sphinx documentations, which is how it’s used in the cookbook examples. You can check the documentation and the github repository.

Generalized Convex Hull construction for the polymorphs of ROY
This notebook analyzes the structures of 264 polymorphs of ROY, from Beran et Al, Chemical Science (2022), comparing the conventional density-energy convex hull with a Generalized Convex Hull (GCH) analysis (see Anelli et al., Phys. Rev. Materials (2018)). It uses features computed with rascaline and uses the directional convex hull function from scikit-matter to make the figure.
Generalized Convex Hull construction for the polymorphs of ROY
PCA/PCovR Visualization for the rattled GaAs training dataset
This example uses rascaline and metatensor to compute structural properties for the structures in a training for a ML model. These are then used with simple dimensionality reduction algorithms (implemented in sklearn and skmatter) to obtain a simplified description of the dataset, that is then visualized using chemiscope.
PCA/PCovR Visualization for the rattled GaAs training dataset
Path integral metadynamics
This example shows how to run a free-energy sampling calculation that combines path integral molecular dynamics to model nuclear quantum effects and metadynamics to accelerate sampling of the high-free-energy regions.
Path integral metadynamics
Path integral molecular dynamics
This example shows how to run a path integral molecular dynamics simulation using i-PI, analyze the output and visualize the trajectory in chemiscope. It uses LAMMPS as the driver to simulate the q-TIP4P/f water model.
Path integral molecular dynamics