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 exp...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.展开更多
Transistor size is constantly being reduced to improve performance as well as power consumption. For the channel length to be reduced, the corresponding gate dielectric thickness should also be reduced. Unfortunately,...Transistor size is constantly being reduced to improve performance as well as power consumption. For the channel length to be reduced, the corresponding gate dielectric thickness should also be reduced. Unfortunately, graphene devices are more complicated due to an extra capacitance called quantum capacitance （CQ） which limits the effective gate dielectric reduction. In this work, we analyzed the effect of CQ on device-scaling issues by extracting it from scaling of the channel length of devices. In contrast to previous reports for metal-insulator- metal structures, a practical device structure was used in conjunction with direct radio-frequency field-effect transistor measurements to describe the graphene channels. In order to precisely extract device parameters, we reassessed the equivalent circuit, and concluded that the on-state model should in fact be used. By careful consideration of the underlap region, our device modeling was shown to be in good agreement with the experimental data. CQ contributions to equivalent oxide thickness were analyzed in detail for varying impurity concentrations in graphene. Finally, we were able to demonstrate that despite contributions from CQ, graphene＇s high mobility and low-voltage operation allows for ~raphene channels suitable for next generation transistors.展开更多
Using scanning tunneling microscopy/spectroscopy(STM/STS),we examine quasiparticle scattering and interference properties at the surface of WTe2.WTe2,layered transition metal dichalcogenide,is predicted to be a type-l...Using scanning tunneling microscopy/spectroscopy(STM/STS),we examine quasiparticle scattering and interference properties at the surface of WTe2.WTe2,layered transition metal dichalcogenide,is predicted to be a type-ll Weyl semimetal.The Weyl fermion states in WTe2 emerge as topologically protected touching points of electron and hole pockets,and Fermi arcs connecting them can be visible in the spectral function on the surface.To probe the properties of surface states,we have conducted low-temperature STM/STS(at 2.7 K)on the surfaces of WTe2 single crystals.We visualize the surface states of WTe2 with atomic scale resolution.Clear surface states emerging from the bulk electron pocket have been identified and their connection with the bulk electronic states shows good agreement with calculations.We show the interesting double resonance peaks in the local density of states appearing at localized impurities.The low-energy resonant peak occurs near the Weyl point above the Fermi energy and it may be mixed with the surface state of Weyl points,which makes it difficult to observe the topological nature of the Weyl semimetal WTe2.展开更多
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.
文摘Transistor size is constantly being reduced to improve performance as well as power consumption. For the channel length to be reduced, the corresponding gate dielectric thickness should also be reduced. Unfortunately, graphene devices are more complicated due to an extra capacitance called quantum capacitance （CQ） which limits the effective gate dielectric reduction. In this work, we analyzed the effect of CQ on device-scaling issues by extracting it from scaling of the channel length of devices. In contrast to previous reports for metal-insulator- metal structures, a practical device structure was used in conjunction with direct radio-frequency field-effect transistor measurements to describe the graphene channels. In order to precisely extract device parameters, we reassessed the equivalent circuit, and concluded that the on-state model should in fact be used. By careful consideration of the underlap region, our device modeling was shown to be in good agreement with the experimental data. CQ contributions to equivalent oxide thickness were analyzed in detail for varying impurity concentrations in graphene. Finally, we were able to demonstrate that despite contributions from CQ, graphene＇s high mobility and low-voltage operation allows for ~raphene channels suitable for next generation transistors.
基金We thank K.Lee and J.Heo for useful discussions and other colleagues at the Samsung Advanced Institute of Technology(SAIT)This work has been supported by the Global Research Laboratory Program(No.2016K1A1A2912707)+5 种基金Quantum Computing Development Program(No.2019M3E4A 1080227)the Basic Science Research Program(No.2015M3A7B4050455)the SRC Center for Topological Matter(No.2018R1A5A6075964)through the National Research Foundation(NRF)funded by the Ministry of Science and ICT(MSIT)in KoreaThis work has been supported by Indutrial Strategic Technology Development Program(No.10085617)funded by the Ministry of Trade Industry&Energy(MOTIE)in KoreaThis work has been supported by Institute for Basic Science(No.IBS-R011-D1)Supercomputing resources including technical service were supported by National Institute of Supercomputing and Network through Korea Institute of Science and Technology Information(No.KSC 2018-51-0008).
文摘Using scanning tunneling microscopy/spectroscopy(STM/STS),we examine quasiparticle scattering and interference properties at the surface of WTe2.WTe2,layered transition metal dichalcogenide,is predicted to be a type-ll Weyl semimetal.The Weyl fermion states in WTe2 emerge as topologically protected touching points of electron and hole pockets,and Fermi arcs connecting them can be visible in the spectral function on the surface.To probe the properties of surface states,we have conducted low-temperature STM/STS(at 2.7 K)on the surfaces of WTe2 single crystals.We visualize the surface states of WTe2 with atomic scale resolution.Clear surface states emerging from the bulk electron pocket have been identified and their connection with the bulk electronic states shows good agreement with calculations.We show the interesting double resonance peaks in the local density of states appearing at localized impurities.The low-energy resonant peak occurs near the Weyl point above the Fermi energy and it may be mixed with the surface state of Weyl points,which makes it difficult to observe the topological nature of the Weyl semimetal WTe2.
