COF-Landscaper¶

GitHub: https://github.com/GregorLauter/COF-Landscaper

COF-Landscaper is a Python package for building and analyzing two-dimensional covalent organic frameworks (COFs).

It provides tools to construct single-layer COF structures from node and linker building blocks, generate interlayer-distance and interlayer-slipping structure matrices, run machine-learning interatomic potential workflows, analyze stacking minima, and compare simulated and experimental PXRD patterns.

Installation¶

COF-Landscaper requires Python 3.12.

Install COF-Landscaper from PyPI:

pip install cof-landscaper

Install PORMAKE, which is required for COF construction:

pip install "pormake @ git+https://github.com/Sangwon91/PORMAKE.git"

To copy the example workflows into the current directory, run:

cof-landscaper-copy-examples

Developer Setup¶

Install just.

Install uv.

Clone the repository and enter the source directory:

git clone https://github.com/GregorLauter/COF-Landscaper.git
cd COF-Landscaper

Set up the development environment:

just setup

Run code checks:

just check

Overview¶

COF-Landscaper is designed around a complete computational workflow for screening 2D COF stacking configurations.

COF Construction¶

COF-Landscaper builds single-layer COF structures from user-provided node and linker fragments in .xyz format. The currently supported topology keys are hcb, sql, hcb_ab, and kgm.

The hcb, sql, and kgm topologies require one node and one linker. The hcb_ab topology requires two nodes and no linker.

ILD/ILS Matrix Generation¶

The package generates structure matrices by scanning interlayer distance (ILD) and interlayer slipping (ILS). Both serrated and inclined stacking variants can be generated. The default slip endpoint corresponds to the AB/default stacking shift and can be printed from the workflow settings.

MLIP Workflow¶

The MLIP workflow can be run locally using MACE-based single-point and optimization steps.

PXRD Analysis¶

COF-Landscaper can simulate PXRD patterns, extract peaks, and compare simulated PXRD data with experimental PXRD data.

Example Workflows¶

Example files can be copied after installation with:

cof-landscaper-copy-examples

The copied examples include an executable Python workflow with a separate cof-landscaper.params.json configuration file, as well as notebook workflows with different levels of explanation.

The notebook examples include:

cof-landscaper_configurable.ipynb: full notebook with Markdown explanations for all configurable options.
cof-landscaper.ipynb: default workflow notebook with explanations for the default settings.
cof-landscaper_minimal.ipynb: minimal code-only workflow for running the notebook without extended explanations.

What Next?¶

New users should start by installing COF-Landscaper, copying the example files, and running one of the notebooks or the Python workflow in examples/python/.

For API-level details, see the module documentation.