2篇
您的检索式：作者名="Maria Frysali"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Chemically intuited,large-scale screening of MOFs by machine learning techniques显示文摘A novel computational methodology for large-scale screening of MOFs is applied to gas storage with the use of machine learning technologies.This approach is a promising trade-off between the accuracy of ab initio methods and the speed of classical approaches,strategically combined with chemical intuition.The results demonstrate that the chemical properties of MOFs are indeed predictable(stochastically,not deterministically)using machine learning methods and automated analysis protocols,with the accuracy of predictions increasing with sample size.Our initial results indicate that this methodology is promising to apply not only to gas storage in MOFs but in many other material science projects. | Giorgos Borboudakis Taxiarchis Stergiannakos Maria Frysali Emmanuel Klontzas Ioannis Tsamardinos George E.Froudakis | 2017 | npj Computational Materials2017，，1： | 2 |
| 2 | Author Correction:Chemically intuited,large-scale screening of MOFs by machine learning techniques显示文摘The affiliation details for George E.Froudakis were incorrect in this article.The correct affiliation details for this author are given below:Department of Chemistry,University of Crete,Voutes Campus,GR-70013 Heraklion,Crete,Greece This has now been corrected in the HTML and PDF versions of this article. | Giorgos Borboudakis Taxiarchis Stergiannakos Maria Frysali Emmanuel Klontzas Ioannis Tsamardinos George E.Froudakis | 2017 | npj Computational Materials2017，，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员