five

DFT data used in training MolE8 chemical ML models

收藏
DataCite Commons2024-11-29 更新2025-04-17 收录
下载链接:
https://rdmc.nottingham.ac.uk/handle/internal/9356
下载链接
链接失效反馈
官方服务:
资源简介:
=============================================================== Data for paper "MolE8: Finding DFT Potential Energy Surface Minima Values from Force-Field Optimised Organic Molecules with New Machine Learning Representations" Sanha Lee, Kristaps Ermanis* and Jonathan M. Goodman* Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW and School of Chemistry, University of Nottingham, University Park Nottingham, Nottingham, NG7 2RD =============================================================== This dataset contains Gaussian DFT optimization and frequency calculation output files for all of the molecules used in the training of the MolE8 representations and machine learning methods. The dataset is divided in 7 parts to keep the archive file sizes manageable. Each folder contains data for around 8000 molecules. The data includes the geometry optimization *a.out files, frequency calculation *f.out files and *sdf files of the optimized structures for wider compatibility with visualization software. Part 1 contains structure files up to 009999A1* Part 2 contains structure files up to 019999A1* Part 3 contains structure files up to 021988A1* Part 4 contains structure files up to 39997A1* Part 5 contains structure files up to 49999A1* Part 6 contains structure files up to 59999A1* Part 6 contains structure files up to 69125A1* All structures in these folders have been optimized and frequencies calculated at B3LYP/6-31g(2df,p) level in gas phase. All of the files can be opened in any text editor. Gaussian output structures can be viewed and the frequency modes visualised in GausView, Avogadro, jmol and in most other molecular viewers/editors. *.sdf files can be viewed in essentially all 3D molecular editors and viewers.
提供机构:
The University of Nottingham
创建时间:
2021-11-09
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作