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The Atomistic Cookbook
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The Atomistic Cookbook
  • Recipes grouped by topic
    • Statistical sampling and dynamics
    • Analysis and post-processing
    • Machine learning models
    • Nuclear quantum effects
  • Recipes grouped by software used
    • i-PI
    • chemiscope
    • featomic
    • scikit-matter
    • cp2k
    • LAMMPS
    • metatensor
    • PLUMED
    • torch-pme
  • List of all recipes
    • A ML model for the electron density of states
    • Atomistic Water Model for Molecular Dynamics
    • Batch run of CP2K calculations
    • Constant-temperature MD and thermostats
    • Equivariant linear model for polarizability
    • Equivariant model for tensorial properties based on scalar features
    • Generalized Convex Hull construction for the polymorphs of ROY
    • Learning Capabilities with torchpme
    • Local Prediction Rigidity analysis
    • Long-distance Equivariants: a tutorial
    • MD using direct-force predictions with PET-MAD
    • Multiple time stepping and ring-polymer contraction
    • PCA/PCovR Visualization of a training dataset for a potential
    • Path integral metadynamics
    • Path integral molecular dynamics
    • Periodic Hamiltonian learning
    • Quantum heat capacity of water
    • Rotating equivariants
    • Sample and Feature Selection with FPS and CUR
    • The PET-MAD universal potential
  • Downloading and running the recipes
  • Contributing a recipe
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Recipes grouped by software usedΒΆ

Cookbook recipes often combine multiple modeling tools. Here you can find them organized based on the software they use. They may give you ideas on how to use them in your own atomistic cooking.

  • i-PI
  • chemiscope
  • featomic
  • scikit-matter
  • cp2k
  • LAMMPS
  • metatensor
  • PLUMED
  • torch-pme
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i-PI
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Nuclear quantum effects
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