{"title":"MO-NanoDatabase:一个由大量金属氧化物纳米化合物、它们的全局性质和三维结构组成的金属氧化物纳米结构化合物数据集","authors":"Francesc Serratosa, Natàlia Segura-Alabart","doi":"10.1016/j.dib.2025.111476","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents the first important recompilation of metal-oxide nanocompounds, which is composed of three main parts: the first one includes several global properties of the nanocompounds whereas the second one includes their 3D structure, represented by the well-known XYZ format. Finally, the third part includes the structural nano QSAR named NanoFingerprint of these 3D structures. Modelling size-realistic metal-oxide nanomaterials to analyse some of their properties, such as chemical activity, solubility, or electronic structure, is a current challenge in computational and theoretical chemistry. Several nano QSAR models have been published based on global properties of these compounds, but few QSAR models also leverage their 3D structure. A general database of nanocompounds is crucial for the validation of current and future models.</div><div>The global properties have been extracted from datasets published as the supporting material of papers that present new models for property prediction of metal-oxide nanocompounds [2–7]. The data has been curated, imposed the same units, formatted and given the same name per property since we realised the low generalisation on units, formats and nomenclature. Note the input parameters of the QSAR models and also the properties to be predicted have been put together as global properties in our database. Moreover, the 3D crystallographic structure has been computed through simulation computer applications of all the compounds since these structures could not be found in most of the cases.</div><div>Since it is the first time that all this knowledge is compiled in a unique database, the purpose of MO-NanoDatabase is to be a reference database for prediction (chemical activity, solubility or electronic structure) of metal-oxide nanocompounds for current and future nano QSART models. Although many nanocompounds have been included, new versions of the database are not discarded if they bring substantial quantity of new nanocompounds presented in future papers.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111476"},"PeriodicalIF":1.0000,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MO-NanoDatabase: A metal-oxide nanostructured compound dataset composed of a huge number of metal-oxide nanocompounds, their global properties and 3D-structure\",\"authors\":\"Francesc Serratosa, Natàlia Segura-Alabart\",\"doi\":\"10.1016/j.dib.2025.111476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper presents the first important recompilation of metal-oxide nanocompounds, which is composed of three main parts: the first one includes several global properties of the nanocompounds whereas the second one includes their 3D structure, represented by the well-known XYZ format. Finally, the third part includes the structural nano QSAR named NanoFingerprint of these 3D structures. Modelling size-realistic metal-oxide nanomaterials to analyse some of their properties, such as chemical activity, solubility, or electronic structure, is a current challenge in computational and theoretical chemistry. Several nano QSAR models have been published based on global properties of these compounds, but few QSAR models also leverage their 3D structure. A general database of nanocompounds is crucial for the validation of current and future models.</div><div>The global properties have been extracted from datasets published as the supporting material of papers that present new models for property prediction of metal-oxide nanocompounds [2–7]. The data has been curated, imposed the same units, formatted and given the same name per property since we realised the low generalisation on units, formats and nomenclature. Note the input parameters of the QSAR models and also the properties to be predicted have been put together as global properties in our database. Moreover, the 3D crystallographic structure has been computed through simulation computer applications of all the compounds since these structures could not be found in most of the cases.</div><div>Since it is the first time that all this knowledge is compiled in a unique database, the purpose of MO-NanoDatabase is to be a reference database for prediction (chemical activity, solubility or electronic structure) of metal-oxide nanocompounds for current and future nano QSART models. Although many nanocompounds have been included, new versions of the database are not discarded if they bring substantial quantity of new nanocompounds presented in future papers.</div></div>\",\"PeriodicalId\":10973,\"journal\":{\"name\":\"Data in Brief\",\"volume\":\"60 \",\"pages\":\"Article 111476\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2025-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data in Brief\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352340925002082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340925002082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
MO-NanoDatabase: A metal-oxide nanostructured compound dataset composed of a huge number of metal-oxide nanocompounds, their global properties and 3D-structure
This paper presents the first important recompilation of metal-oxide nanocompounds, which is composed of three main parts: the first one includes several global properties of the nanocompounds whereas the second one includes their 3D structure, represented by the well-known XYZ format. Finally, the third part includes the structural nano QSAR named NanoFingerprint of these 3D structures. Modelling size-realistic metal-oxide nanomaterials to analyse some of their properties, such as chemical activity, solubility, or electronic structure, is a current challenge in computational and theoretical chemistry. Several nano QSAR models have been published based on global properties of these compounds, but few QSAR models also leverage their 3D structure. A general database of nanocompounds is crucial for the validation of current and future models.
The global properties have been extracted from datasets published as the supporting material of papers that present new models for property prediction of metal-oxide nanocompounds [2–7]. The data has been curated, imposed the same units, formatted and given the same name per property since we realised the low generalisation on units, formats and nomenclature. Note the input parameters of the QSAR models and also the properties to be predicted have been put together as global properties in our database. Moreover, the 3D crystallographic structure has been computed through simulation computer applications of all the compounds since these structures could not be found in most of the cases.
Since it is the first time that all this knowledge is compiled in a unique database, the purpose of MO-NanoDatabase is to be a reference database for prediction (chemical activity, solubility or electronic structure) of metal-oxide nanocompounds for current and future nano QSART models. Although many nanocompounds have been included, new versions of the database are not discarded if they bring substantial quantity of new nanocompounds presented in future papers.
期刊介绍:
Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.