Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have b...Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have been adopted as an alternative,nevertheless a major challenge is a lack of sufficient actual training images.Here we report the generation of synthetic two-dimensional materials images using StyleGAN3 to complement the dataset.DeepLabv3Plus network is trained with the synthetic images which reduces overfitting and improves recognition accuracy to over 90%.A semi-supervisory technique for labeling images is introduced to reduce manual efforts.The sharper edges recognized by this method facilitate material stacking with precise edge alignment,which benefits exploring novel properties of layered-material devices that crucially depend on the interlayer twist-angle.This feasible and efficient method allows for the rapid and high-quality manufacturing of atomically thin materials and devices.展开更多
In recent years,valleytronics researches based on 2D semiconducting transition metal dichalcogenides have attracted considerable attention.On the one hand,strong spin–orbit interaction allows the presence of spin–va...In recent years,valleytronics researches based on 2D semiconducting transition metal dichalcogenides have attracted considerable attention.On the one hand,strong spin–orbit interaction allows the presence of spin–valley coupling in this system,which provides spin addressable valley degrees of freedom for information storage and processing.On the other hand,large exciton binding energy up to hundreds of me V enables excitons to be stable carriers of valley information.Valley polarization,marked by an imbalanced exciton population in two inequivalent valleys(+K and-K),is the core of valleytronics as it can be utilized to store binary information.Motivated by the potential applications,we present a thorough overview of the recent advancements in the generation,relaxation,manipulation,and transport of the valley polarization in nonmagnetic transition metal dichalcogenide layered semiconductors.We also discuss the development of valleytronic devices and future challenges in this field.展开更多
基金Project supported by the National Key Research and Development Program of China(Grant No.2022YFB2803900)the National Natural Science Foundation of China(Grant Nos.61974075 and 61704121)+2 种基金the Natural Science Foundation of Tianjin Municipality(Grant Nos.22JCZDJC00460 and 19JCQNJC00700)Tianjin Municipal Education Commission(Grant No.2019KJ028)Fundamental Research Funds for the Central Universities(Grant No.22JCZDJC00460).
文摘Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have been adopted as an alternative,nevertheless a major challenge is a lack of sufficient actual training images.Here we report the generation of synthetic two-dimensional materials images using StyleGAN3 to complement the dataset.DeepLabv3Plus network is trained with the synthetic images which reduces overfitting and improves recognition accuracy to over 90%.A semi-supervisory technique for labeling images is introduced to reduce manual efforts.The sharper edges recognized by this method facilitate material stacking with precise edge alignment,which benefits exploring novel properties of layered-material devices that crucially depend on the interlayer twist-angle.This feasible and efficient method allows for the rapid and high-quality manufacturing of atomically thin materials and devices.
基金Project supported by the National Key Research and Development Program of China(Grant No.2022YFB2803900)the National Natural Science Foundation of China(Grant Nos.61704121 and 61974075)+2 种基金Natural Science Foundation of Tianjin City(Grant Nos.19JCQNJC00700 and 22JCZDJC00460)Tianjin Municipal Education Commission(Grant No.2019KJ028)Fundamental Research Funds for the Central Universities(Grant No.22JCZDJC00460)。
文摘In recent years,valleytronics researches based on 2D semiconducting transition metal dichalcogenides have attracted considerable attention.On the one hand,strong spin–orbit interaction allows the presence of spin–valley coupling in this system,which provides spin addressable valley degrees of freedom for information storage and processing.On the other hand,large exciton binding energy up to hundreds of me V enables excitons to be stable carriers of valley information.Valley polarization,marked by an imbalanced exciton population in two inequivalent valleys(+K and-K),is the core of valleytronics as it can be utilized to store binary information.Motivated by the potential applications,we present a thorough overview of the recent advancements in the generation,relaxation,manipulation,and transport of the valley polarization in nonmagnetic transition metal dichalcogenide layered semiconductors.We also discuss the development of valleytronic devices and future challenges in this field.
