| 1 | Deep-learning-based inverse design model for intelligent discovery of organic molecules显示文摘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. | Kyungdoc Kim Seokho Kang Jiho Yoo Youngchun Kwon Youngmin Nam Dongseon Lee Inkoo Kim Youn-Suk Choi Yongsik Jung Sangmo Kim Won-Joon Son Jhunmo Son Hyo Sug Lee Sunghan Kim Jaikwang Shin Sungwoo Hwang | 2018 | npj Computational Materials2018，，1： | 4 |
| 3 | Selective inhibition of cell growth by activin in SNU-16 cells显示文摘瞄准:为了调查苯丙酸诺龙是否通过 mRNA 调整人的胃的癌症房间线 SNU-16 的房间增长,在苯丙酸诺龙受体, Smads 和 p21 (CIP1/WAF1 ) 变化。方法:人的胃的癌症房间线是有教养的, RNA 被净化,并且 RT-PCRs 与为每基因的明确地设计的教材被执行。在他们之中,二房间线 SNU-5 和 SNU-16 与为 24, 48 和 72 h 的苯丙酸诺龙 A 是有教养的。房间增长被 MTT 试金测量。为 SNU-16,在房间与为 24, 48 和 72 h 的苯丙酸诺龙 A 是有教养的以后,在 ActRIA, ActRIB, ActRIIA, ActRIIB, Smad2, Smad4, Smad7,和 p21 (CIP1/WAF1 ) mRNAs 的变化与 RT-PCR 被检测。结果:SNU-16 房间的增长低而另外的房间没显示出变化,由苯丙酸诺龙 A 调整了。除了苯丙酸诺龙的子单元,苯丙酸诺龙受体, Smads ,和 p21 ( CIP1/WAF1 )是的 inhibin/activin 的基础水平标签 mRNAs 被观察在人的胃的癌症房间线有微分表示模式, AGS , KATO III , SNU-1 , SNU-5 , SNU-16 , SNU-484 , SNU-601 , SNU-638 , SNU-668 ,并且 SNU-719 。有趣地, ActR IIA 和 IIB mRNAs 的显著地更高的表情在 SNU-16 房间被观察什么时候与另外的房间相比。而 ActR IIB mRNA 水平在 SNU-16 房间增加了,在苯丙酸诺龙治疗, ActR IA, IB,和 IIA mRNA 以后,层次被减少。而 Smad7 mRNA 在 24 h 严厉地增加了并且在 SNU-16 房间在 48 h 回到了起始的水平, Smad4 mRNA 为多达 48 h 增加了。另外, p21 (CIP1/WAF1 ) 的表示,核分裂抑制剂,在 SNU-16 房间在苯丙酸诺龙治疗以后在 72 h 达到顶点。结论:我们的结果建议由苯丙酸诺龙的细胞生长的抑制被 Smad7 的否定反馈效果在表明小径的苯丙酸诺龙上调整,并且通过 p21 (CIP1/WAF1 ) 被调停在 SNU-16 细胞的激活。 | Young Il Kim Hee Joo Lee Inkoo Khang Byung-Nam Cho Ha Kyu Lee | 2006 | World Journal of Gastroenterology2006，12，19： | 1 |
| 5 | Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs显示文摘We report a high-performance multi graphics processing unit(GPU)implementation of the Kohn–Sham time-dependent density functional theory(TDDFT)within the Tamm–Dancoff approximation.Our algorithm on massively parallel computing systems using multiple parallel models in tandem scales optimally with material size,considerably reducing the computational wall time.A benchmark TDDFT study was performed on a green fluorescent protein complex composed of 4353 atoms with 40,518 atomic orbitals represented by Gaussian-type functions,demonstrating the effect of distant protein residues on the excitation.As the largest molecule attempted to date to the best of our knowledge,the proposed strategy demonstrated reasonably high efficiencies up to 256 GPUs on a custom-built state-of-the-art GPU computing system with Nvidia A100 GPUs.We believe that our GPU-oriented algorithms,which empower first-principles simulation for very large-scale applications,may render deeper understanding of the molecular basis of material behaviors,eventually revealing new possibilities for breakthrough designs on new material systems. | Inkoo Kim Daun Jeong Won-Joon Son Hyung-Jin Kim Young Min Rhee Yongsik Jung Hyeonho Choi Jinkyu Yim Inkook Jang Dae Sin Kim | 2023 | npj Computational Materials2023，，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员