MOFChecker: a package for validating and correcting metal-organic framework (MOF) structures.

Area of Science:

• Materials Science
• Computational Chemistry
• Nanotechnology

Background:

• Metal-organic frameworks (MOFs) are advanced porous materials with diverse applications.
• Large-scale computational screening of MOFs is crucial for discovering new materials.
• Existing MOF databases suffer from structural inaccuracies due to experimental limitations.

Purpose of the Study:

• To introduce MOFChecker, a computational tool for validating and correcting MOF structural data.
• To improve the quality and reliability of MOF databases for computational screening.
• To facilitate accurate density functional theory (DFT) optimizations and high-throughput studies of MOFs.

Main Methods:

• MOFChecker employs algorithms for duplicate structure detection.
• It performs geometric and charge error checking on MOF structures.
• Systematic atomic adjustments are used for structure correction, including adding missing components.

Main Results:

• Evaluation revealed significant errors in established MOF databases, with 38% of structures in CoRE2014 containing errors.
• MOFChecker successfully identifies and corrects issues like incorrect hydrogen positions, atomic overlaps, and missing elements.
• The tool enables systematic correction of duplicated structures and addition of missing atoms, linkers, and counterions.

Conclusions:

• MOFChecker is essential for ensuring the accuracy of MOF structural data.
• Improved data quality through MOFChecker enhances the reliability of computational screening and DFT studies.
• This work significantly advances the usability of MOF databases for materials discovery and practical applications.