588 research outputs found

    Physical Modeling of Graphene Nanoribbon Field Effect Transistor Using Non-Equilibrium Green Function Approach for Integrated Circuit Design

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    The driving engine for the exponential growth of digital information processing systems is scaling down the transistor dimensions. For decades, this has enhanced the device performance and density. However, the International Technology Roadmap for Semiconductors (ITRS) states the end of Moore’s law in the next decade due to the scaling challenges of silicon-based CMOS electronics, e.g. extremely high power density. The forward-looking solutions are the utilization of emerging materials and devices for integrated circuits. The Ph.D. dissertation focuses on graphene, one atomic layer of carbon sheet, experimentally discovered in 2004. Since fabrication technology of emerging materials is still in early stages, transistor modeling has been playing an important role for evaluating futuristic graphene-based devices and circuits. The GNR FET has been simulated by solving a numerical quantum transport model based on self-consistent solution of the 3D Poisson equation and 1D Schrödinger equations within the non-equilibrium Green’s function (NEGF) formalism. The quantum transport model fully treats short channel-length electrostatic effects and the quantum tunneling effects, leading to the technology exploration of graphene nanoribbon field effect transistors (GNRFETs) for the future. A comprehensive study of static metrics and switching attributes of GNRFET has been presented including the performance dependence of device characteristics to the GNR width and the scaling of its channel length down to 2.5 nanometer. It has been found that increasing the GNR width deteriorate the off-state performance of the GNRFET, such that, narrower armchair GNRs improved the device robustness to short channel effects, leading to better off-state performance considering smaller off-current, larger ION/IOFF ratio, smaller subthreshold swing and smaller drain-induced barrier-lowering. The wider armchair GNRs allow the scaling of channel length and supply voltage resulting in better on-state performance such as higher drive current, smaller intrinsic gate-delay time and smaller power-delay product. In addition, the width-dependent characteristics of GNR FETs is investigated for two GNR semiconducting families (3p,0) and (3p+1,0). It has been found that the GNRs(3p+1,0) demonstrates superior off-state performance, while, on the other hand, GNRs(3p,0) shows superior on-state performance. Thus, GNRs(3p+1,0) are promising for low-power design, while GNRs(3p,0) indicate a more preferable attribute for high frequency applications

    Fault Modeling of Graphene Nanoribbon FET Logic Circuits

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    [EN] Due to the increasing defect rates in highly scaled complementary metal-oxide-semiconductor (CMOS) devices, and the emergence of alternative nanotechnology devices, reliability challenges are of growing importance. Understanding and controlling the fault mechanisms associated with new materials and structures for both transistors and interconnection is a key issue in novel nanodevices. The graphene nanoribbon field-effect transistor (GNR FET) has revealed itself as a promising technology to design emerging research logic circuits, because of its outstanding potential speed and power properties. This work presents a study of fault causes, mechanisms, and models at the device level, as well as their impact on logic circuits based on GNR FETs. From a literature review of fault causes and mechanisms, fault propagation was analyzed, and fault models were derived for device and logic circuit levels. This study may be helpful for the prevention of faults in the design process of graphene nanodevices. In addition, it can help in the design and evaluation of defect- and fault-tolerant nanoarchitectures based on graphene circuits. Results are compared with other emerging devices, such as carbon nanotube (CNT) FET and nanowire (NW) FET.This work was supported in part by the Spanish Government under the research project TIN2016-81075-R and by Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion, Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV), under the project 200190032.Gil Tomás, DA.; Gracia-Morán, J.; Saiz-Adalid, L.; Gil, P. (2019). Fault Modeling of Graphene Nanoribbon FET Logic Circuits. Electronics. 8(8):1-18. https://doi.org/10.3390/electronics8080851S11888International Technology Roadmap for Semiconductors (ITRS) 2013http://www.itrs2.net/2013-itrs.htmlSchuegraf, K., Abraham, M. C., Brand, A., Naik, M., & Thakur, R. (2013). Semiconductor Logic Technology Innovation to Achieve Sub-10 nm Manufacturing. IEEE Journal of the Electron Devices Society, 1(3), 66-75. doi:10.1109/jeds.2013.2271582International Technology Roadmap for Semiconductors (ITRS) 2015https://bit.ly/2xiiT8PNovoselov, K. S. (2004). Electric Field Effect in Atomically Thin Carbon Films. Science, 306(5696), 666-669. doi:10.1126/science.1102896Geim, A. K., & Novoselov, K. S. (2007). The rise of graphene. Nature Materials, 6(3), 183-191. doi:10.1038/nmat1849Wu, Y., Farmer, D. B., Xia, F., & Avouris, P. (2013). Graphene Electronics: Materials, Devices, and Circuits. Proceedings of the IEEE, 101(7), 1620-1637. doi:10.1109/jproc.2013.2260311Choudhury, M. R., Youngki Yoon, Jing Guo, & Mohanram, K. (2011). Graphene Nanoribbon FETs: Technology Exploration for Performance and Reliability. IEEE Transactions on Nanotechnology, 10(4), 727-736. doi:10.1109/tnano.2010.2073718Avouris, P. (2010). Graphene: Electronic and Photonic Properties and Devices. Nano Letters, 10(11), 4285-4294. doi:10.1021/nl102824hBanadaki, Y. M., & Srivastava, A. (2015). Scaling Effects on Static Metrics and Switching Attributes of Graphene Nanoribbon FET for Emerging Technology. IEEE Transactions on Emerging Topics in Computing, 3(4), 458-469. doi:10.1109/tetc.2015.2445104Avouris, P., Chen, Z., & Perebeinos, V. (2007). Carbon-based electronics. Nature Nanotechnology, 2(10), 605-615. doi:10.1038/nnano.2007.300Banerjee, S. K., Register, L. F., Tutuc, E., Basu, D., Kim, S., Reddy, D., & MacDonald, A. H. (2010). Graphene for CMOS and Beyond CMOS Applications. Proceedings of the IEEE, 98(12), 2032-2046. doi:10.1109/jproc.2010.2064151Schwierz, F. (2013). Graphene Transistors: Status, Prospects, and Problems. Proceedings of the IEEE, 101(7), 1567-1584. doi:10.1109/jproc.2013.2257633Fregonese, S., Magallo, M., Maneux, C., Happy, H., & Zimmer, T. (2013). Scalable Electrical Compact Modeling for Graphene FET Transistors. IEEE Transactions on Nanotechnology, 12(4), 539-546. doi:10.1109/tnano.2013.2257832Chen, Y.-Y., Sangai, A., Rogachev, A., Gholipour, M., Iannaccone, G., Fiori, G., & Chen, D. (2015). A SPICE-Compatible Model of MOS-Type Graphene Nano-Ribbon Field-Effect Transistors Enabling Gate- and Circuit-Level Delay and Power Analysis Under Process Variation. IEEE Transactions on Nanotechnology, 14(6), 1068-1082. doi:10.1109/tnano.2015.2469647Ferrari, A. C., Bonaccorso, F., Fal’ko, V., Novoselov, K. S., Roche, S., Bøggild, P., … Pugno, N. (2015). Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems. Nanoscale, 7(11), 4598-4810. doi:10.1039/c4nr01600aHong, A. J., Song, E. B., Yu, H. S., Allen, M. J., Kim, J., Fowler, J. D., … Wang, K. L. (2011). Graphene Flash Memory. ACS Nano, 5(10), 7812-7817. doi:10.1021/nn201809kJeng, S.-L., Lu, J.-C., & Wang, K. (2007). A Review of Reliability Research on Nanotechnology. IEEE Transactions on Reliability, 56(3), 401-410. doi:10.1109/tr.2007.903188Srinivasu, B., & Sridharan, K. (2017). A Transistor-Level Probabilistic Approach for Reliability Analysis of Arithmetic Circuits With Applications to Emerging Technologies. IEEE Transactions on Reliability, 66(2), 440-457. doi:10.1109/tr.2016.2642168Teixeira Franco, D., Naviner, J.-F., & Naviner, L. (2006). Yield and reliability issues in nanoelectronic technologies. annals of telecommunications - annales des télécommunications, 61(11-12), 1422-1457. doi:10.1007/bf03219903Lin, Y.-M., Jenkins, K. A., Valdes-Garcia, A., Small, J. P., Farmer, D. B., & Avouris, P. (2009). Operation of Graphene Transistors at Gigahertz Frequencies. Nano Letters, 9(1), 422-426. doi:10.1021/nl803316hLiao, L., Lin, Y.-C., Bao, M., Cheng, R., Bai, J., Liu, Y., … Duan, X. (2010). High-speed graphene transistors with a self-aligned nanowire gate. Nature, 467(7313), 305-308. doi:10.1038/nature09405Wang, X., Tabakman, S. M., & Dai, H. (2008). Atomic Layer Deposition of Metal Oxides on Pristine and Functionalized Graphene. Journal of the American Chemical Society, 130(26), 8152-8153. doi:10.1021/ja8023059Geim, A. K. (2009). Graphene: Status and Prospects. Science, 324(5934), 1530-1534. doi:10.1126/science.1158877Mistewicz, K., Nowak, M., Wrzalik, R., Śleziona, J., Wieczorek, J., & Guiseppi-Elie, A. (2016). Ultrasonic processing of SbSI nanowires for their application to gas sensors. Ultrasonics, 69, 67-73. doi:10.1016/j.ultras.2016.04.004Jesionek, M., Nowak, M., Mistewicz, K., Kępińska, M., Stróż, D., Bednarczyk, I., & Paszkiewicz, R. (2018). Sonochemical growth of nanomaterials in carbon nanotube. Ultrasonics, 83, 179-187. doi:10.1016/j.ultras.2017.03.014Chen, X., Seo, D. H., Seo, S., Chung, H., & Wong, H.-S. P. (2012). Graphene Interconnect Lifetime: A Reliability Analysis. IEEE Electron Device Letters, 33(11), 1604-1606. doi:10.1109/led.2012.2211564Wang, Z. F., Zheng, H., Shi, Q. W., & Chen, J. (2009). Emerging nanodevice paradigm. ACM Journal on Emerging Technologies in Computing Systems, 5(1), 1-19. doi:10.1145/1482613.1482616Dong, J., Xiang, G., Xiang-Yang, K., & Jia-Ming, L. (2007). Atomistic Failure Mechanism of Single Wall Carbon Nanotubes with Small Diameters. Chinese Physics Letters, 24(1), 165-168. doi:10.1088/0256-307x/24/1/045Bu, H., Chen, Y., Zou, M., Yi, H., Bi, K., & Ni, Z. (2009). Atomistic simulations of mechanical properties of graphene nanoribbons. Physics Letters A, 373(37), 3359-3362. doi:10.1016/j.physleta.2009.07.04

    VLSI Design

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    This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc

    Overview of emerging nonvolatile memory technologies

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    Novel High Performance Ultra Low Power Static Random Access Memories (SRAMs) Based on Next Generation Technologies

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    Title from PDF of title page viewed January 27, 2021Dissertation advisor: Masud H. ChowdhuryVitaIncludes bibliographical references (page 107-120)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2019Next Big Thing Is Surely Small: Nanotechnology Can Bring Revolution. Nanotechnology leads the world towards many new applications in various fields of computing, communication, defense, entertainment, medical, renewable energy and environment. These nanotechnology applications require an energy-efficient memory system to compute and process. Among all the memories, Static Random Access Memories (SRAMs) are high performance memories and occupies more than 50% of any design area. Therefore, it is critical to design high performance and energy-efficient SRAM design. Ultra low power and high speed applications require a new generation memory capable of operating at low power as well as low execution time. In this thesis, a novel 8T SRAM design is proposed that offers significantly faster access time and lowers energy consumption along with better read stability and write ability. The proposed design can be used in the conventional SRAM as well as in computationally intensive applications like neural networks and machine learning classifiers [1]-[4]. Novel 8T SRAM design offers higher energy efficiency, reliability, robustness and performance compared to the standard 6T and other existing 8T and 9T designs. It offers the advantages of a 10T SRAM without the additional area, delay and power overheads of the 10T SRAM. The proposed 8T SRAM would be able to overcome many other limitations of the conventional 6T and other 7T, 8T and 9T designs. The design employs single bitline for the write operation, therefore the number of write drivers are reduced. The defining feature of the proposed 8T SRAM is its hybrid design, which is the combination of two techniques: (i) the utilization of single-ended bitline and (ii) the utilization of virtual ground. The single-ended bitline technique ensures separate read and write operations, which eventually reduces the delay and power consumption during the read and write operations. It's independent read and write paths allow the use of the minimum sized access transistors and aid in a disturb-free read operation. The virtual ground weakens the positive feedback in the SRAM cell and improves its write ability. The virtual ground technique is also used to reduce leakages. The proposed design does not require precharging the bitlines for the read operation, which reduces the area and power overheads of the memory system by eliminating the precharging circuit. The design isolates the storage node from the read path, which improves the read stability. For reliability study, we have investigated the static noise margin (SNM) of the proposed 8T SRAM, for which, we have used two methods – (i) the traditional SNM method with the butterfly curve, (ii) the N-curve method A comparative analysis is performed between the proposed and the existing SRAM designs in terms of area, total power consumption during the read and write operations, and stability and reliability. All these advantages make the proposed 8T SRAM design an ideal candidate for the conventional and computationally intensive applications like machine learning classifier and deep learning neural network. In addition to this, there is need for next generation technologies to design SRAM memory because the conventional CMOS technology is approaching its physical and performance boundaries and as a consequence, becoming incompatible with ultra-low-power applications. Emerging devices such as Tunnel Field Effect Transistor (TFET)) and Graphene Nanoribbon Field Effect Transistor (GNRFET) devices are highly potential candidates to overcome the limitations of MOSFET because of their ability to achieve subthreshold slopes below 60 mV/decade and very low leakage currents [6]-[9]. This research also explores novel TFET and GNRFET based 6T SRAM. The thesis evaluates the standby leakage power in the Tunnel FET (TFET) based 6T SRAM cell for different pull-up, pull-down, and pass-gate transistors ratios (PU: PD: PG) and compared to 10nm FinFET based 6T SRAM designs. It is observed that the 10nm TFET based SRAMs have 107.57%, 163.64%, and 140.44% less standby leakage power compared to the 10nm FinFET based SRAMs when the PU: PD: PG ratios are 1:1:1, 1:5:2 and 2:5:2, respectively. The thesis also presents an analysis of the stability and reliability of sub-10nm TFET based 6T SRAM circuit with a reduced supply voltage of 500mV. The static noise margin (SNM), which is a critical measure of SRAM stability and reliability, is determined for hold, read and write operations of the 6T TFET SRAM cell. The robustness of the optimized TFET based 6T SRAM circuit is also evaluated at different supply voltages. Simulations were done in HSPICE and Cadence tools. From the analysis, it is clear that the main advantage of the TFET based SRAM would be the significant improvement in terms of leakage or standby power consumption. Compared to the FinFET based SRAM the standby leakage power of the T-SRAMs are 107.57%, 163.64%, and 140.44% less for 1:1:1, 1:5:2 and 2:5:2 configurations, respectively. Since leakage/standby power is the primary source of power consumption in the SRAM, and the overall system energy efficiency depends on SRAM power consumption, TFET based SRAM would lead to massive improvement of the energy efficiency of the system. Therefore, T-SRAMs are more suitable for ultra-low power applications. In addition to this, the thesis evaluates the standby leakage power of types of Graphene Nanoribbon FETs based 6T SRAM bitcell and compared to 10nm FinFET based 6T SRAM bitcell. It is observed that the 10nm MOS type GNRFET based SRAMs have 16.43 times less standby leakage power compared to the 10nm FinFET based SRAMs. The double gate SB-GNRFET based SRAM consumes 1.35E+03 times less energy compared to the 10nm FinFET based SRAM during write. However, during read double gate SB-GNRFET based SRAM consume 15 times more energy than FinFET based SRAM. It is also observed that GNRFET based SRAMs are more stable and reliable than FinFET based SRAM.Introduction -- Background -- Novel High Performance Ultra Low Power SRAM Design -- Tunnel FET Based SRAM Design -- Graphene Nanoribbon FET Based SRAM Design -- Double-gate FDSOI Based SRAM Designs -- Novel CNTFET and MEMRISTOR Based Digital Designs -- Conclusio

    Enhancing the Simultaneous Alignment and Sorting of Carbon Nanotubes

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    Carbon nanotubes have broken through the barriers of our imagination and are currently being investigated for various nano-electronic device applications. Successful implementation in these applications however, often requires strict control of their properties and orientation. As such, post-synthesis processing must be performed prior to any device fabrication. These processing techniques often aim to either address the challenges associated with sorting and alignment individually. A novel method called the alignment relay technique aims to address both of these issues simultaneously. As the introduction of this process was merely a proof of concept, focus must be put in place to enhance the performance and e cacy. In an attempt to improve this technique, we alter the temperature, liquid crystal, iptycene design as well as means of alignment as attempts to accomplish this. At the same time, mechanistic details are revealed to gain a better insight of the nanoscopic dynamics. Preparation of preliminary materials and apparatuses are initially performed. We rst build a Polarized Optical Microsope (POM) in order to observe the liquid crystal dynamics. Despite its frequent use in a research setting, the cost can be upwards of thousands of dollars. As only qualitative observations are required, we decided to build our own model. In this section, we provide a blueprint for the construction of an economical POM with a heating stage and digital connection for facile recording of data, totaling about 150−150-200. We subsequently demonstrate its e ective application in visualizing liquid crystals. After the microscope is made, various molecules are synthesized to gain the chemical resources needed for the alignment. In an attempt to circumvent some of the hazards asssociated with the original synthesis, an alternate route to create iptycene (5) is rst explored. Despite having success in the initial parts of the synthetic sequence, an inability to replicate literature conditions causes the nal step to produce only a 2% yield. Thus, we are forced to abandon this procedure and revert to using the original route to making the molecule. A smaller iptycene molecule (9) is subsequently made through attaching the anchoring group directly to one of the intermediates appearing in the synthesis of iptycene (5). Finally, a separate liquid crystal (11) is synthesized through two nucleophilic additions with 4- hydroxy-4-biphenylcarboxylic acid. These materials provide us the necessary grounding to perform experiments with the alignment relay technique. After the preliminary materials are gathered, the e ects of changing the temperature, liquid crystal and iptycene on CNT depositions are observed. An increase in temperature from 25 oC to 70 oC with a nematic liquid crystal (ZLI-1185) do not yield great results as standard deviations are over 45 o. Attempts at using a more ordered smectic A liquid crystal mixture do not aid results either. In fact, we obtain no CNT deposition at all with these iv attempts. From this, we gather that controlling both the alignment and functionalization of iptycenes at higher temperatures prove to be a challenging task. As a result of the unknown parameters of both functionalization and alignment kinetics, higher temperature experiments are abandoned. Next, iptycene (9) is used to probe the sorting e ects of the alignment relay technique. As the size of the cavity on this molecule is signi cantly smaller in comparison to the original iptycene (5) we expect smaller CNT's to be deposited onto the surface. Unfortunately, alignment of this molecule in liquid crystal media is a potential issue due to the smaller size. Consequently, no CNT's are spotted on the surface. Valuable mechanistic insights are obtained from these changes in variables in the alignment relay technique. Finally, magnetic elds are explored as a viable method for alignment. From these experiments, we nd that the performance is positively associated with the magnetic eld strength. The standard deviation in alignment between a 0.6 T eld and 0.9 T eld are 55 o and 24 o respectively with also a clear Gaussian distribution found in the latter condition. Trends for selectivity however, are uncon rmed as Raman spectroscopy using 532 nm and 633 nm lasers show con icting information. The 532 nm laser show the best selectivity under a 0.9 T eld while the 633 nm laser suggested that the 0.6 T has the better selectivity. Despite needing further data to establish a pattern between eld strength selectivity, general patterns remain congruent with previous reports as the same diameter CNT's (1.44 nm and 1.59 nm) are present on the substrate surface. These positive results allow the use of magnetic elds to be the basis of future alignment experiments and processes. Bene ts as a result of this change include limiting exposure of the substrate to dust, adjustable alignment and reusability

    The Renaissance of Black Phosphorus

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    One hundred years after its first successful synthesis in the bulk form in 1914, black phosphorus (black P) was recently rediscovered from the perspective of a two-dimensional (2D) layered material, attracting tremendous interest from condensed matter physicists, chemists, semiconductor device engineers and material scientists. Similar to graphite and transition metal dichalcogenides (TMDs), black P has a layered structure but with a unique puckered single layer geometry. Because the direct electronic band gap of thin film black P can be varied from 0.3 to around 2 eV, depending on its film thickness, and because of its high carrier mobility and anisotropic in-plane properties, black P is promising for novel applications in nanoelectronics and nanophotonics different from graphene and TMDs. Black P as a nanomaterial has already attracted much attention from researchers within the past year. Here, we offer our opinions on this emerging material with the goal of motivating and inspiring fellow researchers in the 2D materials community and the broad readership of PNAS to discuss and contribute to this exciting new field. We also give our perspectives on future 2D and thin film black P research directions, aiming to assist researchers coming from a variety of disciplines who are desirous of working in this exciting research field.Comment: 23 pages, 6 figures, perspective article, appeared online in PNA
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