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A Protocol for Computer-Based Protein Structure and Function Prediction
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TopoFF: MOF structure prediction using specifically optimized blueprints.

Julian Keupp1, Rochus Schmid

  • 1Computational Materials Chemistry Group, Lehrstuhl für Anorganische Chemie 2, Ruhr-Universität Bochum, Bochum, Germany. rochus.schmid@rub.de.

Faraday Discussions
|July 21, 2018
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Summary
This summary is machine-generated.

We introduce the topoFF method to optimize crystal structure prediction for metal-organic frameworks (MOFs). This approach refines topological blueprints, accelerating the search for stable MOF structures.

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Area of Science:

  • Materials Science
  • Crystallography
  • Computational Chemistry

Background:

  • Accurate structure prediction is crucial for designing novel crystalline framework materials like MOFs.
  • Existing methods like the Reversed Topological Approach (RTA) use topological blueprints but require optimization of building block (BB) insertion.
  • Minimizing average angle deviation (AAD) is key for optimal BB placement within the blueprint.

Purpose of the Study:

  • To enhance the Reversed Topological Approach (RTA) for MOF structure prediction.
  • To introduce a fast, parameter-free method (topoFF) for optimizing topological blueprints.
  • To enable quantitative ranking of different crystal topologies.

Main Methods:

  • Developed the topoFF method for pre-optimizing the maximum symmetry embedding of a topology.
  • Implemented topoFF to minimize the overall mean AAD for a given set of BBs.
  • Optimized vertex positions and cell parameters of the blueprint to fit BB structural requirements.

Main Results:

  • The topoFF method significantly speeds up the search for energetically favorable MOF structures.
  • topoFF allows for a quantitative and intuitive ranking of various crystal topologies.
  • Demonstrated the application of topoFF within the RTA framework using instructive examples.

Conclusions:

  • The topoFF method is an effective extension of RTA for MOF structure prediction.
  • This approach accelerates the discovery of stable and energetically favorable crystalline frameworks.
  • topoFF offers a valuable tool for materials design and topological analysis.