{"title":"The topological way-A new methodology to construct symmetric sets of valence-bond structures.","authors":"Sourav Roy, Avital Shurki","doi":"10.1063/5.0269493","DOIUrl":null,"url":null,"abstract":"<p><p>Classical valence bond (VB) theory has advanced significantly in recent years, evolving into a quantitative tool comparable to molecular orbital-based methods. A key advantage of VB is its high interpretability through Lewis-like resonance structures. However, traditional VB theory faces challenges with symmetric systems, as it often fails to generate symmetric sets of structures, leading to a loss of wavefunction interpretability. In this work, we extend the chemical insight approach and present a method for constructing symmetric VB sets. Rather than relying on conventional symmetry techniques, our method is predominantly based on topological information. It utilizes molecular geometry and connectivity and integrates scoring criteria for atoms, bonds, and structures. This approach enables the classification of VB structures into symmetry-adapted subsets guided by chemical intuition and topological features. We have successfully applied this method to a variety of molecular systems, demonstrating its ability to generate symmetric VB sets even in cases where traditional Rumer rules fail. These advancements contribute meaningfully to the interpretability of VB wavefunctions, marking a significant step forward in the development of VB theory.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"162 22","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Physics","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1063/5.0269493","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Classical valence bond (VB) theory has advanced significantly in recent years, evolving into a quantitative tool comparable to molecular orbital-based methods. A key advantage of VB is its high interpretability through Lewis-like resonance structures. However, traditional VB theory faces challenges with symmetric systems, as it often fails to generate symmetric sets of structures, leading to a loss of wavefunction interpretability. In this work, we extend the chemical insight approach and present a method for constructing symmetric VB sets. Rather than relying on conventional symmetry techniques, our method is predominantly based on topological information. It utilizes molecular geometry and connectivity and integrates scoring criteria for atoms, bonds, and structures. This approach enables the classification of VB structures into symmetry-adapted subsets guided by chemical intuition and topological features. We have successfully applied this method to a variety of molecular systems, demonstrating its ability to generate symmetric VB sets even in cases where traditional Rumer rules fail. These advancements contribute meaningfully to the interpretability of VB wavefunctions, marking a significant step forward in the development of VB theory.
期刊介绍:
The Journal of Chemical Physics publishes quantitative and rigorous science of long-lasting value in methods and applications of chemical physics. The Journal also publishes brief Communications of significant new findings, Perspectives on the latest advances in the field, and Special Topic issues. The Journal focuses on innovative research in experimental and theoretical areas of chemical physics, including spectroscopy, dynamics, kinetics, statistical mechanics, and quantum mechanics. In addition, topical areas such as polymers, soft matter, materials, surfaces/interfaces, and systems of biological relevance are of increasing importance.
Topical coverage includes:
Theoretical Methods and Algorithms
Advanced Experimental Techniques
Atoms, Molecules, and Clusters
Liquids, Glasses, and Crystals
Surfaces, Interfaces, and Materials
Polymers and Soft Matter
Biological Molecules and Networks.