引用本文:
【打印本页】   【HTML】   【下载PDF全文】   View/Add Comment  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 1103次   下载 672 本文二维码信息
码上扫一扫!
分享到: 微信 更多
Chemical Empiricism 2.0 at Age of Big Data: Large-scale Prediction of Reaction Pathways Based on Bond Dissociation Energies
Shi-lu Chen*
Author NameAffiliationE-mail
Shi-lu Chen* Key Laboratory of Cluster Science of Ministry of Education, School of Chemistry, Beijing Institute of Technology, Beijing 100081, China shlchen@bit.edu.cn 
Abstract:
A programmable algorithm using bond dissociation energies has been proposed for the prediction of reaction pathways. It has been successfully applied to a gas-phase reaction of F2+CH3Cl, with the accurate revelation of the most favorable product CF4 and its corresponding reaction pathway. This acts as an inspiring example of chemical empiricism 2.0, and may open the door for the large-scale prediction of reaction pathways at the age of big data.
Key words:  Big data, Bond dissociation energy, Reaction pathway, Prediction
FundProject:
大数据时代下的化学经验2.0:基于键能的大规模反应途径预测
陈世稆*
摘要:
报道了一个基于键能数据预测反应途径的可编程算法.运用该算法,成功预测了F2+CH3Cl气相反应的最优产物(CF4)和对应的反应途径.提供了一个启示性的化学经验2.0 的例子,并可能开启大数据时代下的大规模反应途径预测的大门.
关键词:  大数据,键能,反应途径,预测
DOI:10.1063/1674-0068/28/cjcp1505103
分类号: