Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials.Modern electron microscopy routinely achieves atomic resolution and is capable to resolve...Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials.Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision.Here,we present AI-STEM,an automatic,artificial-intelligence based method,for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy(STEM)images of polycrystalline materials.The method is based on a Bayesian convolutional neural network(BNN)that is trained only on simulated images.AI-STEM automatically and accurately identifies crystal structure,lattice orientation,and location of interface regions in synthetic and experimental images.The model is trained on cubic and hexagonal crystal structures,yielding classifications and uncertainty estimates,while no explicit information on structural patterns at the interfaces is included during training.This work combines principles from probabilistic modeling,deep learning,and information theory,enabling automatic analysis of experimental,atomic-resolution images.展开更多
Intrinsic carrier transport properties of single-walled carbon nanotubes have been probed by two parallel methods on the same individual tubes： The contactless dielectric force microscopy （DFM） technique and the co...Intrinsic carrier transport properties of single-walled carbon nanotubes have been probed by two parallel methods on the same individual tubes： The contactless dielectric force microscopy （DFM） technique and the conventional field-effect transistor （FET） method. The dielectric responses of SWNTs are strongly correlated with electronic transport of the corresponding FETs. The DC bias voltage in DFM plays a role analogous to the gate voltage in FET. A microscopic model based on the general continuity equation and numerical simulation is built to reveal the link between intrinsic properties such as carrier concentration and mobility and the macroscopic observable, i.e. dielectric responses, in DFM experiments. Local transport barriers in nanotubes, which influence the device transport behaviors, are also detected with nanometer scale resolution.展开更多
Due to fiber swelling,textile fabrics containing hygroscopic fibers tend to decrease pore size under wet or increasing humid-ity and moisture conditions,the reverse being true.Nevertheless,for personal thermal regulat...Due to fiber swelling,textile fabrics containing hygroscopic fibers tend to decrease pore size under wet or increasing humid-ity and moisture conditions,the reverse being true.Nevertheless,for personal thermal regulation and comfort,the opposite is desirable,namely,increasing the fabric pore size under increasing humid and sweating conditions for enhanced ventila-tion and cooling,and a decreased pore size under cold and dry conditions for heat retention.This paper describes a novel approach to create such an unconventional fabric by emulating the structure of the plant leaf stomata by designing a water responsive polymer system in which the fabric pores increase in size when wet and decrease in size when dry.The new fabric increases its moisture permeability over 50%under wet conditions.Such a water responsive fabric can find various applications including smart functional clothing and sportswear.展开更多
Moirésuperlattices of transition metal dichalcogenide(TMD)heterostructures give rise to rich excitonic phenomena associated with the interlayer twist angle.Theoretical calculations of excitons in such systems are...Moirésuperlattices of transition metal dichalcogenide(TMD)heterostructures give rise to rich excitonic phenomena associated with the interlayer twist angle.Theoretical calculations of excitons in such systems are typically based on model moirépotentials that mitigate the computational cost.However,predictive understanding of the electron-hole coupling dominating the excitations is crucial to realize the twist-induced modifications of the optical selection rules.In this work,we use many-body perturbation theory to evaluate the relation between twist angle and exciton properties in TMD heterostructures.We present an approach for unfolding excitonic states from the moiréBrillouin zone onto the separate-layer ones.Applying this method to a large-angle twisted MoS^(2)/MoSe^(2) bilayer,we find that the optical spectrum is dominated by mixed electron–hole transitions with different momenta in the separate monolayers,leading to unexpected hybridization between interlayer and intralayer excitons.Our findings offer a design pathway for exciton layer-localization in TMD heterostructures.展开更多
基金L.M.G.acknowledges funding from the European Union’s Horizon 2020 research and innovation program,under grant agreements No.951786(NOMAD CoE)and No.740233(TEC1p)Furthermore,the authors acknowledge the Max Planck Computing and Data facility(MPCDF)for computational resources and support,which enabled neural-network training on 1 GPU(Tesla Volta V10032GB)on the Talos machine learning clusterB.C.Y.acknowledges funding from the National Research Foundation(NRF)of Korea under Project Number 2021M3A7C2090586.
文摘Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials.Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision.Here,we present AI-STEM,an automatic,artificial-intelligence based method,for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy(STEM)images of polycrystalline materials.The method is based on a Bayesian convolutional neural network(BNN)that is trained only on simulated images.AI-STEM automatically and accurately identifies crystal structure,lattice orientation,and location of interface regions in synthetic and experimental images.The model is trained on cubic and hexagonal crystal structures,yielding classifications and uncertainty estimates,while no explicit information on structural patterns at the interfaces is included during training.This work combines principles from probabilistic modeling,deep learning,and information theory,enabling automatic analysis of experimental,atomic-resolution images.
文摘Intrinsic carrier transport properties of single-walled carbon nanotubes have been probed by two parallel methods on the same individual tubes： The contactless dielectric force microscopy （DFM） technique and the conventional field-effect transistor （FET） method. The dielectric responses of SWNTs are strongly correlated with electronic transport of the corresponding FETs. The DC bias voltage in DFM plays a role analogous to the gate voltage in FET. A microscopic model based on the general continuity equation and numerical simulation is built to reveal the link between intrinsic properties such as carrier concentration and mobility and the macroscopic observable, i.e. dielectric responses, in DFM experiments. Local transport barriers in nanotubes, which influence the device transport behaviors, are also detected with nanometer scale resolution.
基金supported by Prof.Fan’s Faculty Startup Fund of the College of Human Ecology,Cornell Universitysupported by the National Science Foundation under Award Number DMR-1719875acknowledge Dr.Xia Zeng for equipment guidance and support,Charles V.Beach and Vincent Chicone for their assistance with the mask fabrication.Finally,the PI,Prof.Fan would like to acknowledge the funding support of RGC GRF project#15213920 and Hong Kong Polytechnic University Project of Strategic Importance#ZE1H for further analysis of the experimental data and improvement of the manuscript.
文摘Due to fiber swelling,textile fabrics containing hygroscopic fibers tend to decrease pore size under wet or increasing humid-ity and moisture conditions,the reverse being true.Nevertheless,for personal thermal regulation and comfort,the opposite is desirable,namely,increasing the fabric pore size under increasing humid and sweating conditions for enhanced ventila-tion and cooling,and a decreased pore size under cold and dry conditions for heat retention.This paper describes a novel approach to create such an unconventional fabric by emulating the structure of the plant leaf stomata by designing a water responsive polymer system in which the fabric pores increase in size when wet and decrease in size when dry.The new fabric increases its moisture permeability over 50%under wet conditions.Such a water responsive fabric can find various applications including smart functional clothing and sportswear.
基金The project has received further funding from the European Research Council(ERC),Grant agreement No.101041159an Israel Science Foundation Grant No.1208/19.M.J.and H.R.K.gratefully acknowledge the National Supercomputing Mission of the Department of Science and Technology,India,and the Science and Engineering Research Board of the Department of Science and Technology,India,for financial support under Grants No.DST/NSM/R&D_HPC_Applications/2021/23 and No.SB/DF/005/2017,respectively+2 种基金Computational resources were provided by the Oak Ridge Leadership Computing Facility through the Innovative and Novel Computational Impact on Theory and Experiment(INCITE)program,which is a DOE Office of Science User Facility supported under Contract No.DE-AC05-00OR22725Supercomputer Education and Research Center at Indian Institute of Sciencethe ChemFarm cluster at the Weizmann Institute of Science.
文摘Moirésuperlattices of transition metal dichalcogenide(TMD)heterostructures give rise to rich excitonic phenomena associated with the interlayer twist angle.Theoretical calculations of excitons in such systems are typically based on model moirépotentials that mitigate the computational cost.However,predictive understanding of the electron-hole coupling dominating the excitations is crucial to realize the twist-induced modifications of the optical selection rules.In this work,we use many-body perturbation theory to evaluate the relation between twist angle and exciton properties in TMD heterostructures.We present an approach for unfolding excitonic states from the moiréBrillouin zone onto the separate-layer ones.Applying this method to a large-angle twisted MoS^(2)/MoSe^(2) bilayer,we find that the optical spectrum is dominated by mixed electron–hole transitions with different momenta in the separate monolayers,leading to unexpected hybridization between interlayer and intralayer excitons.Our findings offer a design pathway for exciton layer-localization in TMD heterostructures.
