Deep-learning-based inverse design model for intelligent discovery of organic molecules

查看全文 作　　者：Kyungdoc [1]Kim;Seokho [2]Kang;Jiho [1]Yoo;Youngchun [1]Kwon;Youngmin [1]Nam;Dongseon [1]Lee;Inkoo [1]Kim;Youn-Suk [1]Choi;Yongsik [1]Jung;Sangmo [1]Kim;Won-Joon [1]Son;Jhunmo [1]Son;Hyo Sug [1]Lee;Sunghan [1]Kim;Jaikwang [1]Shin;Sungwoo [1]Hwang

机构地区：[1]Samsung Advanced Institute of Technology,Samsung Electronics Co.Ltd.,130 Samsung-ro,Yeongtong-gu,Suwon-si,Gyeonggi-do 16678,Republic of Korea;[2]Department of Systems Management Engineering,Sungkyunkwan University,2066 Seobu-ro,Jangan-gu,Suwon-si,Gyeonggi-do 16419,Republic of Korea

出　　处：《npj Computational Materials》索引2018年第1期,共7页

摘　　要：The discovery of high-performance functional materials is crucial for overcoming technical issues in modern industries.Extensive efforts have been devoted toward accelerating and facilitating this process,not only experimentally but also from the viewpoint of materials design.Recently,machine learning has attracted considerable attention,as it can provide rational guidelines for efficient material exploration without time-consuming iterations or prior human knowledge.In this regard,here we develop an inverse design model based on a deep encoder-decoder architecture for targeted molecular design.Inspired by neural machine language translation,the deep neural network encoder extracts hidden features between molecular structures and their material properties,while the recurrent neural network decoder reconstructs the extracted features into new molecular structures having the target properties.In material design tasks,the proposed fully data-driven methodology successfully learned design rules from the given databases and generated promising light-absorbing molecules and host materials for a phosphorescent organic light-emitting diode by creating new ligands and combinatorial rules. 关键词：INVERSE LEARNING devoted

相关文献

参考文献（43）
引证文献（7）
耦合文献（0）

参考文献(43)

引证文献(7)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Deep-learning-based inverse design model for intelligent discovery of organic molecules

参考文献(43)

引证文献(7)

用户提示