GTsR

GTsR is a graph neural network based tool for solvent identification, solvent removal, and activation-stability prediction in metal-organic frameworks (MOFs).

Pretrained Models

Installation

git clone https://github.com/coollkr/GTsR.git
cd GTsR
conda env create -f environment.yml
conda activate gtsr
pip install -e .

or

conda install -c conda-forge zeopp-lsmo
pip install gtsr

Usage

• Remove solvent

from gtsr import GTsRunner

runner = GTsRunner(checkpoint="free")
result = runner.clean(
    cif="input.cif",
    output="prediction",
    threshold=0.5,
)

You can also use:

runner = GTsRunner(checkpoint="all")
runner = GTsRunner(checkpoint="path/to/ckpt.pth", device="cpu")

runner.clean() returns a dictionary with the following fields:

• Predict activation stability

from gtsr import GTsRunner

runner = GTsRunner(checkpoint="stability")
score = runner.stability(cif="cleaned_framework.cif")

if score == 1:
    print("The cleaned structure is stable.")
else:
    print("The cleaned structure is not stable.")

Web Interface

Streamlit demo

Citation

Update the following entry when the associated publication becomes available:

@article{gtsr-xyl-group,
  title   = {GTSR: A GNN Based Tool for Solvent Removal from MOF with Stability Check},
  author  = {Liang, Kairui and Zhao, Guobin and Li, Xiao-Yan},
  year    = {2026}
}

License

This project is released under the MIT License. See LICENSE for details.