Examples Gallery#
This gallery contains examples demonstrating the capabilities of ALCHEMI Toolkit-Ops. Each example is a fully executable Python script that showcases different features of the library, from basic neighbor list construction to advanced dispersion corrections.
All examples are designed to run on both CPU and GPU, automatically detecting available hardware. The code can be downloaded as Python scripts or Jupyter notebooks.
Interactions#
Examples demonstrating GPU-accelerated computation of atomic interactions, including DFT-D3 dispersion corrections with environment-dependent C6 coefficients.
These examples show how to:
Compute dispersion energies and forces for molecules
Process batches of crystal structures
Integrate with PyTorch for differentiable workflows
Electrostatics#
Examples demonstrating GPU-accelerated computation of long-range electrostatic interactions in periodic systems using Coulomb, Ewald summation, and Particle Mesh Ewald (PME).
These examples show how to:
Compute direct Coulomb interactions (damped and undamped)
Use Ewald summation for periodic systems with automatic parameter estimation
Apply Particle Mesh Ewald (PME) for O(N log N) scaling
Work with neighbor list and neighbor matrix formats
Perform batch evaluation for multiple systems
Leverage autograd for computing forces and gradients
Particle Mesh Ewald (PME) for Long-Range Electrostatics
Neighbor Lists#
Examples demonstrating efficient O(N) neighbor list construction using GPU-accelerated cell list algorithms.
These examples show how to:
Build neighbor lists for single and batched systems
Use dense or sparse COO output formats
Detect when neighbor lists need rebuilding
Optimize performance with
torch.compileIntegrate with molecular dynamics workflows
