omsdetector_forked 2024.11.13

Forked omsdetector to make it compliant with current python versions and dependencies

A Python program to analyze collections of Metal Organic Frameworks (MOFs) for open metal sites.

Author: Emmanuel Haldoupis [e-mail]

March 12th 2018

Description

Given a set of CIF files this program can read the files, analyze the structures and detect all the unique open metal sites present in each structure.

The first step is to create a collection containing all the desired CIF files. We can do this by pointing to a folder containing the CIF files.

from omsdetector-forked import MofCollection
mof_coll = MofCollection.from_folder(collection_folder="path to cif folder",
                                     analysis_folder="path to analysis folder")

Where collection_folder is the folder where the CIF files are located and analysis_folder is the folder where the results will be saved.

The analysis is run using the following command on the mof_coll object:

mof_coll.analyse_mofs()

Specifying a value for num_batches instructs the analysis to run in parallel in the specified number of batches, each as a separate process.

Once the results have finished they can be summarized using the following methods:

mof_coll.summarize_results()
mof_coll.summarize_tfactors()

The summarize_results() method generates a table that summarizes the number of open metal sites found for each metal type. The summarize_tfactors() method generates histograms (and stores them) for the distribution of the t-factors, which indicate the degree of deviation from a closed coordination sphere for tetra, penta, and hexa-coordinated coordination spheres.

Finaly, a collection can be filtered to create a sub-collection using the following filters:

• "density": [min, max] (range of values)
• "oms_density": [min, max] (range of values)
• "uc_volume": [min, max] (range of values)
• "metal_species": ["Cu", "Zn", ...] (list of metal species)
• "non_metal_species": ["C", "N", ...] (list of non metal species)
• "cif_okay": True (boolean value)
• "has_oms": True (boolean value)
• "mof_name": [mof_name1, mof_name2] (string values)

For example:

co_oms = mof_coll.filter_collection(using_filter={"metal_species":["Co"], "has_oms":True})

See the example jupyter notebook for more details.

Requirments

• python >=3.9
• pymatgen >=2023.2.28
• pandas 1.3.5
• numpy 1.21.6
• matplotlib 2.1.1

Reference

Chung, Yongchul; Haldoupis, Emmanuel; Bucior, Benjamin; Haranczyk, Maciej ; Zhang, Hongda; Vogiatzis, Konstantinos; Milisavljevic, Marija; Ling, Sanliang; Camp, Jeffrey; Slater, Ben; Siepmann, J.; Sholl, David; Snurr, Randall Computation-Ready, Experimental Metal-Organic Framework Database 2018: Additional Structures, Open Metal Sites, and Crystal Reconstruction (submited to Chemistry of Materials)