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Two-dimensional materials for future information technology: status and prospects

Science China(Information Sciences) 2024年第6期67卷 1-147页

作者： Hao QIU Zhihao YU Tiange ZHAO Qi ZHANG Mingsheng XU Peifeng LI Taotao LI Wenzhong BAO Yang CHAI Shula CHEN Yiqi CHEN Hui-Ming CHENG Daoxin DAI Zengfeng DI Zhuo DONG Xidong DUAN Yuhan FENG Yu FU Jingshu GUO Pengwen GUO Yue HAO Jun HE Xiao HE Jingyi HU Weida HU Zehua HU Xinyue HUANG Ziyang HUANG Ali IMRAN Ziqiang KONG Jia LI Qian LI Weisheng LI Lei LIAO Bilu LIU Can LIU Chunsen LIU Guanyu LIU Kaihui LIU Liwei LIU Sheng LIU Yuan LIU Donglin LU Likuan MA Feng MIAO Zhenhua NI Jing NING Anlian PAN Tian-Ling REN Haowen SHU Litao SUN Yue SUN Quanyang TAO Zi-Ao TIAN Dong WANG Hao WANG Haomin WANG Jialong WANG Junyong WANG Wenhui WANG Xingjun WANG Yeliang WANG Yuwei WANG Zhenyu WANG Yao WE... Department of Applied Physics The Hong Kong Polytechnic University Key Laboratory for Micro-Nano Physics and Technology of Hunan Province College of Materials Science and EngineeringHunan University College of Integrated Circuits Zhejiang University Shenzhen Geim Graphene Center Shenzhen Key Laboratory of Layered Materials for Value-Added ApplicationsTsinghua-Berkeley Shenzhen Institute & Institute of Materials ResearchTsinghua Shenzhen International Graduate SchoolTsinghua University State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZijingang CampusZhejiang University National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences CAS Key Laboratory of Nanophotonic Materials and Devices & Key Laboratory of Nanodevices and Applications i-LabSuzhou Institute of Nano-Tech and Nano-Bionics (SINANO)Chinese Academy of Sciences College of Chemistry and Chemical Engineering Hunan University Key Laboratory of Quantum State Construction and Manipulation (Ministry of Education) Department of PhysicsRenmin University of China School of Integrated Circuits Beijing National Research Center for Information Science and Technology (BNRist)Tsinghua University School of Electronic Science and Engineering Nanjing University The State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology Shaanxi Joint Key Laboratory of GrapheneSchool of MicroelectronicsXidian University Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education School of Physics and TechnologyWuhan University School of Integrated Circuits Huazhong University of Science and Technology Center for Nanochemistry (CNC) Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular SciencesCollege of Chemistry and Molecular EngineeringPeking University State Key Laboratory for Artificial Microstruct

Over the past 70 years, the semiconductor industry has undergone transformative changes,largely driven by the miniaturization of devices and the integration of innovative structures and materials. Two-dimensional(2D) materials like transition metal dichalcogenides(TMDs) and graphene are pivotal in overcoming the limitations of silicon-based technologies, offering innovative approaches in transistor design and functionality, enabling atomic-thin channel transistors and monolithic 3D integration. We review the important progress in the application of 2D materials in future information technology, focusing in particular on microelectronics and optoelectronics. We comprehensively summarize the key advancements across material production, characterization metrology, electronic devices, optoelectronic devices, and heterogeneous integration on silicon. A strategic roadmap and key challenges for the transition of 2D materials from basic research to industrial development are outlined. To facilitate such a transition, key technologies and tools dedicated to 2D materials must be developed to meet industrial standards, and the employment of AI in material growth, characterizations, and circuit design will be essential. It is time for academia to actively engage with industry to drive the next 10 years of 2D material research.

关键词： two-dimensional (2D) materials information technology production technology standardization of characterization microelectronic devices optoelectronic devices multi-functional integration

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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GridSpice: A Distributed Simulation Platform for the Smart Grid

GridSpice: A Distributed Simulation Platform for the Smart G...

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Workshop on Modeling and Simulation of Cyber-Physical Energy systems

作者： Kyle Anderson Jimmy Du Amit Narayan Abbas El Gamal Circuits Systems and Artificial Neural Networks Laboratory Michigan State University East Lansing MI DLR - German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

ISBN: (纸本)9781479913060

GridSpice is a simulation framework for the smart grid that integrates existing electric power point tools. The framework provides computational scale and modeling capability to represent diverse scenarios in large interconnected grid systems. Currently, GridSpice integrates a transmission and economic dispatch package based on MatPOWER and the distribution system simulator Gridlab-D. GridSpice provides computational scale by parallelizing large simulation jobs across many virtual machines using Amazon Web Services. GridSpice provides three primary mechanisms for setting up simulations: a Python library, a browser-based user interface, and a Representational State Transfer (REST) API, which allows users to interface with existing data management systems or post-processing tools. GridSpice is available in open-source under the BSD license.

关键词： Power System Simulation Electric Vehicles Multiagent systems

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New hyperbolic source density models for blind source recovery score functions

New hyperbolic source density models for blind source recove...

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IEEE International Symposium on circuits and systems (ISCAS)

作者： K. Waheed F.M. Salem Circuits Systems and Artificial Neural Networks Laboratory Michigan State University East Lansing MI USA

We present two new hyperbolic source probability models to effectively represent sub-Gaussian and super-Gaussian families of sources for dynamic and convolutive Blind Source Recovery (BSR). Both models share a common boundary for the Gaussian density function. The proposed hyperbolic probability model for the sub-Gaussian densities is an extension of the Pearson density model. The model can represent a broader range of sub-Gaussian densities including multi-modal densities as compared to the original Pearson Model. Similarly, the proposed super-gaussian model is an extension of the generalized hyperbolic-Cauchy density function with an added degree of freedom. Combining these two proposed models we propose an adaptive score function for Blind Source Recovery from mixtures of multiple (and unknown) source densities. An adaptive algorithm, to determine the regulation parameters for the proposed score function, using the batch kurtosis of BSR output is also presented. The primary advantage of the proposed online parameter estimation is that it renders the adaptive estimation of the demixing network to be completely blind. The proposed algorithms have been extensively used in multi-distribution convolutive Blind Source Recovery problems.

关键词： Density functional theory Adaptive estimation circuits artificial neural networks laboratories Adaptive algorithm Parameter estimation Blind source separation Source separation Blind equalizers

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A completely integrated, low noise, low power CMOS frequency synthesizer for GSM communications

A completely integrated, low noise, low power CMOS frequency...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： K. Waheed K. Desai P. Seddighrad F.M. Salam Circuits Systems and Artificial Neural Networks Laboratory Michigan State University East Lansing MI USA

A low power 22-mW 900-MHz frequency synthesizer (FS), with an on-chip LCtuned voltage controlled oscillator (VCO) for GSM applications is presented. The synthesizer possesses several novel features that include a completely integrated structure, a low phase noise on-chip LC VCO, a low-power Dual-Modulus Divider (DMD) in CML topology, a compensated charge pump with balanced switching, an on-chip third order loop filter and a proposed relatively easy to implement fractional accumulator based frequency synthesis technique. The complete synthesizer achieves in-band phase noise characteristics better than -110 dBc/Hz at 100 kHz offset. The channel switching time is less than 500 /spl mu/s for a 25 MHz frequency hop. The synthesizer is able to accommodate all 195 transmit and receive channels in the R-GSM band. The proposed architecture has been realized using the 0.5 /spl mu/m AMI C5N technology. The complete integrated synthesizer occupies less than 1500 /spl times/ 700 /spl mu/m/sup 2/ of die real estate.

关键词： Frequency synthesizers GSM Voltage-controlled oscillators Phase frequency detector Phase noise Charge pumps Frequency conversion Filters Circuit noise Mobile communication

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A robust algorithm for detecting speech segments using an entropic contrast

A robust algorithm for detecting speech segments using an en...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： K. Waheed K. Weaver F.M. Salam Circuits Systems and Artificial Neural Networks Laboratory Michigan State University East Lansing MI USA

This paper addresses the issue of automatic word/sentence boundary detection in both quiet and noisy environments. We propose to use an entropy based contrast function between the speech segments and the background noise. A simplified data based scheme of computing the entropy of the speech data is presented. The entropy-based contrast exhibits better-behaved characteristics as compared to the energy-based methods. An adaptive threshold is used to determine the candidate speech segments, which are subjected to word/sentence constraints. Experimental. results show that this algorithm outperforms energy-based algorithms. The improved detection accuracy of speech segments results in at least 25% improvement of recognition performance for isolated speech and more than 16% for connected speech. For continuous speech, a preprocessing stage comprising of the proposed speech segment detection makes the overall HMM based scheme more computationally efficient by rejection of silence periods.

关键词： Robustness Entropy Working environment noise Speech enhancement Speech recognition Automatic speech recognition Engines Signal to noise ratio Background noise Detection algorithms

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A data-derived quadratic independence measure for adaptive blind source recovery in practical applications

A data-derived quadratic independence measure for adaptive b...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： K. Waheed F.M. Salam Circuits Systems and Artificial Neural Networks Laboratory Michigan State University East Lansing MI USA

We present a novel performance index to measure the statistical independence of data sequences and apply it to the framework of blind source recovery (BSR) that includes blind source separation, deconvolution and equalization. This performance index is capable of measuring the mutual independence of data sequences directly from the data. This information theoretic; quadratic independence measure (QIM) is derived based on Renyi's quadratic entropy estimated by a finite data length Parzen window using a Gaussian kernel. Simulation results are presented to validate the performance of the proposed benchmark and compare it with other established benchmarks.

关键词： Signal to noise ratio Extraterrestrial measurements Deconvolution Performance analysis Blind source separation Blind equalizers Entropy Signal processing algorithms Transfer functions Intersymbol interference

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Cascaded structures for blind source recovery

Cascaded structures for blind source recovery

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Midwest Symposium on circuits and systems (MWSCAS)

作者： K. Waheed F.M. Salam Circuits Systems and Artificial Neural Networks Laboratory Michigan State University East Lansing MI USA

Blind Source Recovery (BSR) is an interesting autonomous and unsupervised stochastic adaptation problem that includes the well-known blind adaptive problems of Blind Source Separation (BSS), Deconvolution (BSD) and Equalization (BSE). BSR includes also the nonlinear case and hence focuses on reproducing or estimating the source signals even if environment identification is not achieved. A number of outstanding research contributions have been made in this field, however, the issues of application are still in their infancy. Most of the BSR algorithms have characteristics, which make them suitable for a particular subclass of problems. In order to develop a generalized source recovery framework and yet achieve optimal performance in all cases, there is a need to explore further architectural and/or algorithmic domains. In this paper, we approach this goal in the architecture domain by focusing on the use of cascaded structures for BSR. The paper discusses the need, choice, possible forms and properties of several cascaded structures. Some illustrative simulations have been included to highlight the advantages of some of the proposed structures.

关键词： circuits artificial neural networks laboratories Stochastic systems Blind source separation Source separation Deconvolution Adaptive equalizers Blind equalizers Signal processing

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State space blind source recovery for mixtures of multiple source distributions

State space blind source recovery for mixtures of multiple s...

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IEEE International Symposium on circuits and systems (ISCAS)

作者： K. Waheed F.M. Salam Circuits Systems and Artificial Neural Networks Laboratory Department of Electrical and Computer Engineering Michigan State University East Lansing MI USA

The paper discusses state space blind source recovery (BSR) for minimum phase and non-minimum phase mixtures of Gaussian and non-Gaussian distributions. The state space natural gradient approach results in compact iterative update laws for BSR. Two separate state space algorithms for minimum phase and non-minimum phase mixing environments are presented. The advantages and disadvantages of both algorithms in the context of multiple source distribution mixtures are examined. The presented BSR algorithms require use of nonlinearities, which depend on the distribution of the unknown sources. We propose use of an adaptive nonlinearity based on the batch kurtosis of the output. This renders the adaptive estimation of the demixing network completely blind.

关键词： State-space methods Signal processing algorithms Iterative algorithms Gaussian distribution circuits artificial neural networks laboratories Iterative methods Adaptive estimation Adaptive signal processing

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