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Updated: Sep 17, 2025

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LOPOSTER: A Cascading Postprocessor for LOBSTER.

YiXu Wang1, Peter C Müller1, David Hemker1

  • 1Chair of Solid-State and Quantum Chemistry, Institute of Inorganic Chemistry, RWTH Aachen University, Aachen, Germany.

Journal of Computational Chemistry
|June 30, 2025
PubMed
Summary
This summary is machine-generated.

LOPOSTER is a new program that speeds up the analysis of complex chemical bonding data. It automates advanced calculations, making chemical bonding investigations more efficient and accessible.

Keywords:
LOBSTERcarbodiimidechemical bondingmagnetic orderingpostprocessing

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Solid-State Physics

Background:

  • Analyzing complex chemical bonding is crucial for understanding material properties.
  • Existing methods for postprocessing large datasets from codes like LOBSTER can be time-consuming and prone to errors.
  • Advanced bonding analyses, such as multicenter bonding and k-dependent COHP, require specialized tools.

Purpose of the Study:

  • To introduce LOPOSTER, a novel computer program for efficient postprocessing of LOBSTER code results.
  • To automate and streamline advanced chemical bonding analyses for large datasets.
  • To facilitate a deeper understanding of interactions and their correlation with material properties, exemplified by NiNCN.

Main Methods:

  • Development and application of the LOPOSTER program, available via GitHub.
  • Automated processing of multicenter bonding, molecular-orbital formation energy, and k-dependent COHP.
  • Analysis of chemical bonding in NiNCN, including real/reciprocal space and atomic/molecular orbital evaluations.

Main Results:

  • LOPOSTER significantly reduces postprocessing time for large datasets (>10,000 interactions).
  • The program enables automated, comprehensive analysis of advanced bonding features.
  • Versatile analysis of NiNCN interactions revealed correlations with magnetism and discussed N=C=N π bond characteristics.

Conclusions:

  • LOPOSTER enhances the efficiency and scope of routine chemical bonding investigations.
  • The tool minimizes user intervention and potential errors in complex data analysis.
  • LOPOSTER provides valuable insights into material properties through detailed bonding analysis, as demonstrated with NiNCN.