{"title":"COMPAS-3:近缩多苯烃数据集","authors":"Alexandra Wahab and Renana Gershoni-Poranne","doi":"10.1039/D4CP01027B","DOIUrl":null,"url":null,"abstract":"<p >We introduce the third installment of the COMPAS Project – a COMputational database of Polycyclic Aromatic Systems, focused on <em>peri</em>-condensed polybenzenoid hydrocarbons. In this installment, we develop two datasets containing the optimized ground-state structures and a selection of molecular properties of ∼39k and ∼9k <em>peri</em>-condensed polybenzenoid hydrocarbons (at the GFN2-xTB and CAM-B3LYP-D3BJ/cc-pvdz//CAM-B3LYP-D3BJ/def2-SVP levels, respectively). The manuscript details the enumeration and data generation processes and describes the information available within the datasets. An in-depth comparison between the two types of computation is performed, and it is found that the geometrical disagreement is maximal for slightly-distorted molecules. In addition, a data-driven analysis of the structure–property trends of <em>peri</em>-condensed PBHs is performed, highlighting the effect of the size of <em>peri</em>-condensed islands and linearly annulated rings on the HOMO–LUMO gap. The insights described herein are important for rational design of novel functional aromatic molecules for use in, <em>e.g.</em>, organic electronics. The generated datasets provide a basis for additional data-driven machine- and deep-learning studies in chemistry.</p>","PeriodicalId":99,"journal":{"name":"Physical Chemistry Chemical Physics","volume":" 21","pages":" 15344-15357"},"PeriodicalIF":2.9000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/cp/d4cp01027b?page=search","citationCount":"0","resultStr":"{\"title\":\"COMPAS-3: a dataset of peri-condensed polybenzenoid hydrocarbons†\",\"authors\":\"Alexandra Wahab and Renana Gershoni-Poranne\",\"doi\":\"10.1039/D4CP01027B\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >We introduce the third installment of the COMPAS Project – a COMputational database of Polycyclic Aromatic Systems, focused on <em>peri</em>-condensed polybenzenoid hydrocarbons. In this installment, we develop two datasets containing the optimized ground-state structures and a selection of molecular properties of ∼39k and ∼9k <em>peri</em>-condensed polybenzenoid hydrocarbons (at the GFN2-xTB and CAM-B3LYP-D3BJ/cc-pvdz//CAM-B3LYP-D3BJ/def2-SVP levels, respectively). The manuscript details the enumeration and data generation processes and describes the information available within the datasets. An in-depth comparison between the two types of computation is performed, and it is found that the geometrical disagreement is maximal for slightly-distorted molecules. In addition, a data-driven analysis of the structure–property trends of <em>peri</em>-condensed PBHs is performed, highlighting the effect of the size of <em>peri</em>-condensed islands and linearly annulated rings on the HOMO–LUMO gap. The insights described herein are important for rational design of novel functional aromatic molecules for use in, <em>e.g.</em>, organic electronics. The generated datasets provide a basis for additional data-driven machine- and deep-learning studies in chemistry.</p>\",\"PeriodicalId\":99,\"journal\":{\"name\":\"Physical Chemistry Chemical Physics\",\"volume\":\" 21\",\"pages\":\" 15344-15357\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.rsc.org/en/content/articlepdf/2024/cp/d4cp01027b?page=search\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical Chemistry Chemical Physics\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2024/cp/d4cp01027b\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Chemistry Chemical Physics","FirstCategoryId":"92","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/cp/d4cp01027b","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
COMPAS-3: a dataset of peri-condensed polybenzenoid hydrocarbons†
We introduce the third installment of the COMPAS Project – a COMputational database of Polycyclic Aromatic Systems, focused on peri-condensed polybenzenoid hydrocarbons. In this installment, we develop two datasets containing the optimized ground-state structures and a selection of molecular properties of ∼39k and ∼9k peri-condensed polybenzenoid hydrocarbons (at the GFN2-xTB and CAM-B3LYP-D3BJ/cc-pvdz//CAM-B3LYP-D3BJ/def2-SVP levels, respectively). The manuscript details the enumeration and data generation processes and describes the information available within the datasets. An in-depth comparison between the two types of computation is performed, and it is found that the geometrical disagreement is maximal for slightly-distorted molecules. In addition, a data-driven analysis of the structure–property trends of peri-condensed PBHs is performed, highlighting the effect of the size of peri-condensed islands and linearly annulated rings on the HOMO–LUMO gap. The insights described herein are important for rational design of novel functional aromatic molecules for use in, e.g., organic electronics. The generated datasets provide a basis for additional data-driven machine- and deep-learning studies in chemistry.
期刊介绍:
Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions.
The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.