WebMTA: a web-interface for ab initio geometry optimization of large molecules using molecular tailoring approach.

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Quantum Chemistry

Background:

• Geometry optimization is crucial for understanding molecular properties.
• Traditional methods struggle with large molecules due to computational cost.
• Linear scaling methods are needed to address these limitations.

Purpose of the Study:

• To present a web-interface for geometry optimization of large molecules.
• To provide access to the cardinality guided molecular tailoring approach (CG-MTA).
• To enable fragmentation scheme generation for extended molecules.

Main Methods:

• Developed a web interface using HTML and Python.
• Implemented the cardinality guided molecular tailoring approach (CG-MTA), a fragmentation-based linear scaling method.
• Utilized an in-house Linux cluster with @Home-based parallelization for job execution.

Main Results:

• The interface supports geometry optimization for large molecules (80-200 first-row atoms).
• Calculations can be performed at Hartree-Fock and density functional theory levels.
• Users can define fragmentation parameters like maximum fragment size and minimum cut radius.

Conclusions:

• The developed web interface provides accessible computational chemistry tools for large molecules.
• CG-MTA offers a linear scaling solution for ab initio calculations.
• This approach facilitates the study of complex molecular systems through fragmentation.