Recipes grouped by software used¶
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¶
Constant-temperature MD and thermostats

Path integral molecular dynamics

Path integral metadynamics

Quantum heat capacity of water

Multiple time stepping and ring-polymer contraction

Atomistic Water Model for Molecular Dynamics

The PET-MAD universal potential

MD using direct-force predictions with PET-MAD

Long-stride trajectories with a universal FlashMD model

ML collective variables in PLUMED with metatomic

chemiscope¶
Generalized Convex Hull construction for the polymorphs of ROY

PCA/PCovR Visualization of a training dataset for a potential

Path integral metadynamics

Path integral molecular dynamics

Constant-temperature MD and thermostats

Multiple time stepping and ring-polymer contraction

Atomistic Water Model for Molecular Dynamics

Equivariant linear model for polarizability

Equivariant model for tensorial properties based on scalar features

The PET-MAD universal potential

Long-stride trajectories with a universal FlashMD model

ML collective variables in PLUMED with metatomic

featomic¶
PCA/PCovR Visualization of a training dataset for a potential

Local Prediction Rigidity analysis

A ML model for the electron density of states

Long-distance Equivariants: a tutorial

Generalized Convex Hull construction for the polymorphs of ROY

Sample and Feature Selection with FPS and CUR

Periodic Hamiltonian learning

Rotating equivariants

Equivariant linear model for polarizability

Equivariant model for tensorial properties based on scalar features

scikit-matter¶
Sample and Feature Selection with FPS and CUR

Generalized Convex Hull construction for the polymorphs of ROY

Local Prediction Rigidity analysis

PCA/PCovR Visualization of a training dataset for a potential

cp2k¶
Batch run of CP2K calculations

Periodic Hamiltonian learning

LAMMPS¶
Constant-temperature MD and thermostats

Path integral molecular dynamics

Quantum heat capacity of water

Atomistic Water Model for Molecular Dynamics

The PET-MAD universal potential

ML collective variables in PLUMED with metatomic

metatensor¶
Atomistic Water Model for Molecular Dynamics

Equivariant linear model for polarizability

Equivariant model for tensorial properties based on scalar features

The PET-MAD universal potential

MD using direct-force predictions with PET-MAD

Long-stride trajectories with a universal FlashMD model

Computing NMR shielding tensors using ShiftML

Hamiltonian Learning for Molecules with Indirect Targets

ML collective variables in PLUMED with metatomic

PLUMED¶
Path integral metadynamics

ML collective variables in PLUMED with metatomic

torch-pme¶
Atomistic Water Model for Molecular Dynamics

Learning Capabilities with torchpme
