LOPOSTER:龙虾的级联后处理器

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
YiXu Wang, Peter C. Müller, David Hemker, Richard Dronskowski
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引用次数: 0

摘要

介绍了通过GitHub提供的计算机程序LOPOSTER,它能够对LOBSTER代码结果进行后处理。LOPOSTER被设计为特别有效地分析具有超过10,000个交互的大型数据集,并大大减少了后处理时间。LOPOSTER率先实现了高级键合分析结果的自动化处理,包括多中心键合、分子轨道形成能和k依赖的COHP,扩大了常规化学键合研究的范围。此外,LOPOSTER通过在一次执行中提供全面的结果来简化后处理工作流程,最大限度地减少用户干预和潜在错误。最后给出了一个用LOPOSTER可视化软件对NiNCN进行化学键分析的例子。LOPOSTER提供了对NiNCN中相互作用的多功能分析,能够在实空间或互反空间中进行评估,并基于原子或分子轨道,以满足不同的分析偏好。并探讨了这些相互作用与NiNCN磁性之间的各种相关性。本文从多个角度讨论了N=C=N π键的富电子特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

LOPOSTER: A Cascading Postprocessor for LOBSTER

LOPOSTER: A Cascading Postprocessor for LOBSTER

The computer program LOPOSTER, available via GitHub, is introduced, capable of postprocessing the LOBSTER code results. LOPOSTER is designed to be particularly effective for analyzing large datasets with over 10,000 interactions and enormously reducing postprocessing time. LOPOSTER pioneers the automated processing of advanced bonding analysis results, including multicenter bonding, molecular-orbital formation energy, and k-dependent COHP, expanding the scope of routine chemical-bonding investigations. In addition, LOPOSTER streamlines the postprocessing workflow by providing comprehensive results in a single execution, minimizing user intervention and potential errors. An example of chemical-bonding analysis on NiNCN is provided, with visualization by LOPOSTER. LOPOSTER offers versatile analysis of interactions in NiNCN, enabling evaluations in real or reciprocal space, and based on atomic or molecular orbitals, catering to different analytic preferences. Various correlations between those interactions and magnetism in NiNCN are also explored. The electron-rich features of an N=C=N π bond have been discussed from various perspectives.

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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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