PyAR Documentation

PyAR is a chemistry-focused structure-search package. It helps generate, optimise, select, and inspect plausible molecular structures before committing to higher-level electronic-structure calculations.

PyAR is most useful when you want to:

explore low-energy cluster geometries for a set of fragments
search for products or close-contact reaction candidates between two reactants
place solvent molecules or ligands around a central structure
scan a bond distance between two fragments as a simple reaction-coordinate probe

For most chemistry users, start with the task that matches your problem:

First Successful Run for a complete first calculation
Aggregation and Cluster Search for clusters, aggregates, and noncovalent complexes
Reaction Search for AFIR-style product and close-contact searches
Solvation and Growth Around a Core for microsolvation, ligand addition, and growth around a core
Bond Scan for a simple distance-coordinate probe

Cite this work

If you use PyAR in a project, start with Selected Publications and cite the paper that best matches your chemistry problem. The sections below show the most common mappings.

Why chemists use PyAR

PyAR is useful when you want an automated way to generate and screen plausible structures before committing to higher-level electronic-structure work. In practice that means:

getting candidate low-energy geometries for clusters and complexes
finding plausible reaction products or prebiotic intermediates
exploring ligand addition or catalyst formation without hand-building every guess structure
testing solvation and coordination growth around a central core
following a simple bond coordinate when you want a quick structural probe

If you are a student or researcher, start with Quickstart, then move to one of the chemistry task pages above. If you want examples of published uses, see Selected Publications.

Which paper matches my problem?

Chemistry problem	Command/task	Example publications
Noncovalent cluster growth and aggregation	`aggregate`	[Nandi2017], [Khatun2019], [Sherpa2026]
Prebiotic reaction discovery and bond rearrangement	`react`	[Nandi2018], [Panda2024]
Microsolvation or ligand addition around a central core	`solvate`	Use the same build-up logic for solvent shells, coordination complexes, and organometallic assembly
Catalyst formation and sequential ligand addition	`react`	[Roy2022]
Chemical-space exploration of noncovalent clusters	`aggregate`	[Giri2025]

Start here

Tools and references

Backend guides

Developer and API details

These pages are useful when you are modifying PyAR or trying to understand its internal design:

How to cite PyAR

There is no single citation that covers every PyAR use case. In general:

cite the paper that best matches what you used
if you used more than one task, cite the relevant papers
use Selected Publications as the short list of chemistry-facing examples

For a general citation, the two original papers that introduced the main build up and reaction-search ideas are [Nandi2017] and [Khatun2019].

Note

If your work used AFIR-style reaction search, cluster growth, solvation, or another specific application, also cite the corresponding paper from Selected Publications.

The fastest way to verify a local install is:

pyar-cli --help

Tools and reference

Developer documentation