Kongyang Yi, Wen Qin, Yamin Huang, Yao Wu, Shaopeng Feng, Qiyi Fang, Xun Cao, Ya Deng, Chao Zhu, Xilu Zou, Kah-Wee Ang, Taotao Li, Xinran Wang, Jun Lou, Keji Lai, Zhili Hu, Zhuhua Zhang, Yemin Dong, Kourosh Kalantar-Zadeh, Zheng Liu
{"title":"Integration of high-κ native oxides of gallium for two-dimensional transistors","authors":"Kongyang Yi, Wen Qin, Yamin Huang, Yao Wu, Shaopeng Feng, Qiyi Fang, Xun Cao, Ya Deng, Chao Zhu, Xilu Zou, Kah-Wee Ang, Taotao Li, Xinran Wang, Jun Lou, Keji Lai, Zhili Hu, Zhuhua Zhang, Yemin Dong, Kourosh Kalantar-Zadeh, Zheng Liu","doi":"10.1038/s41928-024-01286-x","DOIUrl":"10.1038/s41928-024-01286-x","url":null,"abstract":"The deposition of a metal oxide layer with good dielectric properties is a critical step in fabricating the gate dielectric of transistors based on two-dimensional semiconductors. However, current techniques for depositing ultrathin metal oxide layers on two-dimensional semiconductors suffer from quality issues that can compromise transistor performance. Here, we show that an ultrathin and uniform native oxide of gallium (Ga2O3) that naturally forms on the surface of liquid metals in an ambient environment can be prepared on the surface of molybdenum disulfide (MoS2) by squeeze-printing and surface-tension-driven methods. The Ga2O3 layer possesses a high dielectric constant of around 30 and equivalent oxide thickness of around 0.4 nm. Due to the good dielectric properties and van der Waals integration, MoS2 transistors with Ga2O3 gate dielectrics exhibit a subthreshold swing down to 60 mV dec−1, an on/off ratio of 108 and a gate leakage down to around 4 × 10−7 A cm−2. Ultrathin films of gallium oxide with a dielectric constant of around 30 can be formed on the surface of molybdenum disulfide using a liquid metal-based approach and used as the gate insulator in transistors.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"7 12","pages":"1126-1136"},"PeriodicalIF":33.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hearable devices with sound bubbles","authors":"Tuochao Chen, Malek Itani, Sefik Emre Eskimez, Takuya Yoshioka, Shyamnath Gollakota","doi":"10.1038/s41928-024-01276-z","DOIUrl":"10.1038/s41928-024-01276-z","url":null,"abstract":"The human auditory system has a limited ability to perceive distance and distinguish speakers in crowded settings. A headset technology that can create a sound bubble in which all speakers within the bubble are audible but speakers and noise outside the bubble are suppressed could augment human hearing. However, developing such technology is challenging. Here, we report an intelligent headset system capable of creating sound bubbles. The system is based on real-time neural networks that use acoustic data from up to six microphones integrated into noise-cancelling headsets and are run on the device, processing 8 ms audio chunks in 6.36 ms on an embedded central processing unit. Our neural networks can generate sound bubbles with programmable radii between 1 m and 2 m, and with output signals that reduce the intensity of sounds outside the bubble by 49 dB. With previously unseen environments and wearers, our system can focus on up to two speakers within the bubble, with one to two interfering speakers and noise outside the bubble. An intelligent headset system that uses real-time neural networks run on an embedded central processing unit can create sound bubbles that selectively isolate groups of users from outside sounds.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"7 11","pages":"1047-1058"},"PeriodicalIF":33.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142609957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Creating sound bubbles with intelligent headsets","authors":"Dong Ma","doi":"10.1038/s41928-024-01281-2","DOIUrl":"10.1038/s41928-024-01281-2","url":null,"abstract":"A combination of artificial intelligence and noise-cancelling technology can be used to create headsets with customizable auditory zones — or sound bubbles — that allow users to focus on sounds within a designated area while suppressing sounds outside of it.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"7 11","pages":"952-953"},"PeriodicalIF":33.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142609985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Piezoelectric biomaterials printed on the fly","authors":"Katharina Zeissler","doi":"10.1038/s41928-024-01301-1","DOIUrl":"10.1038/s41928-024-01301-1","url":null,"abstract":"","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"7 11","pages":"940-940"},"PeriodicalIF":33.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142609980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Polarization detection in miniature","authors":"Fan Zhang, Fengnian Xia","doi":"10.1038/s41928-024-01292-z","DOIUrl":"10.1038/s41928-024-01292-z","url":null,"abstract":"A compact on-chip polarimeter can be created using subpixels made from metasurface photodetectors and a machine learning algorithm.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"7 11","pages":"948-949"},"PeriodicalIF":33.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bingjie Dang, Teng Zhang, Xulei Wu, Keqin Liu, Ru Huang, Yuchao Yang
{"title":"Reconfigurable in-sensor processing based on a multi-phototransistor–one-memristor array","authors":"Bingjie Dang, Teng Zhang, Xulei Wu, Keqin Liu, Ru Huang, Yuchao Yang","doi":"10.1038/s41928-024-01280-3","DOIUrl":"10.1038/s41928-024-01280-3","url":null,"abstract":"Memristors with photonic sensory capabilities can be used as elements in machine vision systems but face challenges in terms of encoding and processing optical data. This has led to different neural network architectures being developed for specific vision tasks, which limits progress towards more versatile in-sensor vision computing platforms. Here we describe a multi-phototransistor and one-memristor array that is based on niobium oxide memristors. It has reconfigurable dynamics and is compatible with both machine learning (analogue) and bioinspired (spiking) neural network architectures. The array can sense and process optical images and synchronize spatio-temporal data across different encoding formats. When the array is coupled with a classifier network using a one-transistor and one-memristor non-volatile memory array, it supports a variety of optical neural networks (including optical convolutional neural networks, recurrent neural networks and spiking neural networks). The resulting system can perform various computing vision tasks, such as recognizing static, motion and colour images. Niobium oxide memristors with reconfigurable dynamics can be used to make an array integrated with phototransistors that can encode image information in analogue or spiking form and can support different neural network architectures for image processing tasks.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"7 11","pages":"991-1003"},"PeriodicalIF":33.7,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}