All-Carbon Spin Logic Sensor for RRAM Arrays

Size: px
Start display at page:

Download "All-Carbon Spin Logic Sensor for RRAM Arrays"

Transcription

1 All-Carbon Spin Logic Sensor for RRAM Arrays Stephen K. Heinrich-Barna Connected Microcontrollers Texas Instruments, Inc Dallas, TX USA Jean-Pierre Leburton Electrical and Computer Engineering Univ. Illinois at Urbana-Champaign Urbana, IL USA Joseph S. Friedman Electrical and Computer Engineering Univ. Texas at Dallas Richardson, TX USA Abstract The high speed of all-carbon spin logic (ACSL) is an ideal match for the non-volatility of resistive random-access memory (RRAM). Combining these two technologies in a computing system provides exceptionally high efficiency, with the possibility of replacing traditional CMOS due to the potential for high speed, low cost, and low energy. Before such a system can be realized, circuits must be designed that interface the ACSL processing with the RRAM storage. This work therefore proposes an ACSL sensor circuit that enables detection of the resistance states in an RRAM array. This sensor circuit and the underlying symmetric latch are validated through a novel behavioral model that enables SPICE simulations of ACSL circuits. Keywords RRAM, spintronics, all-carbon spin logic, graphene nanoribbon, carbon nanotube, magnetoresistance, sense amplifier I. INTRODUCTION Resistive random-access memory (RRAM) has emerged as a potential replacement for embedded non-volatile memories used in the commercial space [1]. The reduced mask count needed for RRAM when compared with FLASH at the same technology node offers a significant cost reduction without significant deleterious impact on power or performance. In order to maximally exploit the advantages that RRAM brings to novel memories, it is necessary to develop logical interface circuits that provide exceptional behavior with the potential for low cost. The recently proposed all-carbon spin logic (ACSL) family [2] is a potential logical counterpart to a computing system with RRAM non-volatile memory. This spintronic logic family is composed of magnetoresistive graphene nanoribbon (GNR) transistors connected with and controlled by carbon nanotubes (CNTs). As the ACSL logical states are encoded with current rather than voltage magnitudes, the delay of ACSL circuits approaches the time required for an electromagnetic wave to propagate through the CNT interconnect. Preliminary estimates indicate an ACSL gate delay in the range of a few hundred femtoseconds and a power-delay product that is two orders of magnitude smaller than 22nm CMOS [2]. Given the exciting potential of carbon-based RRAM structures [3] [5], a solely carbon-based computer can be envisioned with potential economic benefits over CMOS resulting from a fully-carbon system with potential reductions in lithography steps. The advance of this vision is dependent on the interface between the RRAM array and the ACSL information processing circuits. A single-device toggle latch was previously shown [2], providing an ACSL memory concept that can be extended to RRAM interface circuits. However, control logic, drivers, decoders, and power switches have not yet been proposed. It is therefore of interest to develop a stable symmetric latch that serves as a state retention device. This device can then be used to store the value obtained from the state of a resistive memory cell for further processing downstream. The concepts developed for the symmetric latch can then be extended to an RRAM sensor circuit that translates the small-signal bitline current (representing either a 0 or 1 resistive state) to create a fullswing ACSL current output. This paper describes the operation of ACSL and the GNR and CNT devices in section II, presenting physical device parameters and a preliminary model in accordance with the available experimental and simulation data. Section III proposes a symmetric latch and discusses its functionality and performance. In section IV, the symmetric latch concept is extended with the proposal of an RRAM sensor circuit, demonstrating the ability to efficiently transfer information from the RRAM non-volatile memory to the ACSL information processing circuits. Finally, concluding remarks are provided in Section V. II. BACKGROUND: ALL-CARBON SPIN LOGIC Zigzag GNRs have been experimentally and theoretically demonstrated to exhibit negative magnetoresistance when subjected to an applied magnetic field [6] [10]. As depicted in Fig. 1, this GNR magnetoresistance can be controlled by the magnetic fields created by adjacent CNTs [2]. The relative current magnitude and directions of current through these CNTs can be considered as a logical input, while the magnitude of current through the GNR is the output of this logic gate. In ACSL, current magnitudes define the binary states, with a 1 represented as a large current magnitude while a 0 is represented as a small current magnitude [11], [12]. A constant voltage is applied across each GNR such that a change in resistance results in a change in current. These logic gates can Figure 1. An ACSL gate with two CNT control wires adjacent to a GNR [2].

2 be cascaded by using the output GNR current from one logic gate as the input CNT current for another logic gate, as described in [2]. A. ACSL Device Functionality Depending on the relative magnetization at the two zigzag edges of a GNR, the GNR is in either the ferromagnetic (FM) or antiferromagnetic (AFM) state. The FM state is highly conductive, and is a result of aligned edge magnetization; the GNR is highly resistive when in the AFM state, which results from opposite edge magnetizations [6], [13]. Resistance in the FM state is approximately two orders of magnitude lower than AFM. Placing one or more conductive elements in parallel and in close proximity to the edges of a GNR as in Fig. 1, the currents through these conductive elements can modulate the GNR edge magnetization. In ACSL, CNTs are used as these controlling conductive elements, and are covalently bonded to the GNRs for efficient electrical connectivity. When the currents through the CNT control wires are in the same direction, an XOR gate results in which the inputs and output are current magnitudes. When the currents through the CNT control wires are in opposite directions, the GNR performs the OR function based on the input current magnitudes. This logical functionality is a result of switching between the FM and AFM states due to the edge magnetic fields created by CNT control currents, as described thoroughly in [2]. B. Behavioral Device Model As the physics underlying the GNR magnetoresistance is not fully understood [9], and the analyses of the ACSL basis logic gate remain preliminary [2], the design and simulation of ACSL circuits is impeded by the lack of a device model. In order to initiate the investigation of complex ACSL circuits, a behavioral model is necessary to evaluate the effect of device parameters on the circuit and system. While not predictive of precise voltage and current magnitudes, this behavioral model permits the analysis of circuit structures and design techniques, while also providing materials science researchers with guidance towards the optimization of the device structure. The behavior of a general magnetoresistive spin-diode [14] can be described by = + ( ) ( ), (1) which is here applied to GNRs. R GNR is the resistance of the GNR, R MIN is the minimum resistance in the FM state, R MAX is the maximum resistance in the AFM state, I NET is the additive or counteractive sum of the two input control currents, I CRIT is the threshold I NET current magnitude at which the GNR switches between the FM and AFM states, and N is a slope constant that determines the abruptness of the transition between the FM and AFM states. The CNT is modeled as a resistor with values matching those experimentally observed in [15]. For several of these parameters, reasonable values can be determined based on previously published work [2], [15]. For others, no previous experimental or theoretical work provides guidance for the choice of parameters; values were chosen that TABLE I. GNR BEHAVIORAL MODEL PARAMETER VALUES Parameter Value Reference R GNR 12.6 kω (FM) [2] 1.29 MΩ (AFM) R CNT 20 KΩ [15] I CRIT 2.5 µa V IN 0.12 V N 8 matched intuitive expectations. The GNR parameter values used to analyze the circuits described here are shown in Table I. The resistance changes smoothly from R MAX to R MIN, achieving 37% of the R MAX value at the threshold current, I CRIT. The combined effect of both CNTs determines the state of the GNR by summing the net current (and thus the net magnetic field) adjacent to the GNR. Equal currents flowing in each CNT in the same direction create counteracting magnetic fields, causing the GNR to be in the AFM state. Current flowing in only one of the CNTs, or in opposite directions through both CNTs causes the GNR to be in the FM state when the net current is above a critical level (I CRIT). While not physically precise, this model adequately captures the device behavior to enable transient and operating-point simulations. III. ACSL SYMMETRIC LATCH Latches provide a method by which a state can be stored until a controlling signal alters the state. An initial ACSL latch circuit design was presented in [2], where a toggle latch was shown to maintain a binary state until switched by a toggle pulse. However, the timing constraints of this toggle latch are rather challenging, as the input toggle signal must induce a change in the GNR resistance without interference from the switched output signal. Though the ability to provide this toggle latch functionality with a single GNR is intriguing, the development of a stable symmetric latch is a necessary component for the further advancement of ACSL. A symmetric ACSL latch is shown in Fig. 2. The SET/RESET input current switches the two GNRs such that both GNRs are always in the same state, either FM or AFM. Thus, I CB and I CT are always similar to each other at steady-state, either both being a large 1 current or both being a small 0 current. The output current I OUT is a function of the left GNR resistance, with this I OUT current flowing from a V IN outside this circuit, along the CNT, and through the left GNR to the electrical ground. Thus, when both GNRs are in the AFM state, I OUT is a small 0 current; when both GNRs are in the FM state, I OUT is a large 1 current. The RESET operation is performed as follows: given two GNRs initially in the FM state, large 1 currents flow through the CNTs as shown by the two arrows I CB and I CT. This current Figure 2. ACSL symmetric latch

3 reinforces the FM states in both GNRs, stabilizing the latch. When a low resistance path to ground is provided at the SET/RESET input node, current flows from the latch to the input, thus reducing the current through I CB. There is therefore reduced current controlling the left GNR, resulting in reduced magnetic field applied to the left GNR. When I CB reaches a value of less than half of I CRIT (and therefore I NET becomes less than I CRIT), the left GNR state changes from FM to AFM. This in turn causes a reduction in the current I CT. When I CT becomes less than half the value of I CRIT (and therefore I NET becomes less than I CRIT), the right GNR also transitions from an FM to AFM state, thus completing the RESET operation. The resistance to ground through I OUT is now maximized at R MAX, due to the fact that the left GNR is in the AFM state. At this point, the low resistance between the input and ground can be removed and the latch retains its AFM/AFM condition and continues to produce a small 0 output current. The SET operation is performed by injected current to the latch from the input node. This current raises I CB from a small 0 current produced by the AFM GNR to a large 1 current due to the inclusion of the input RESET signal current. When the current in I CB is equal to half of I CRIT, the left GNR enters the FM state. The FM state in the left GNR causes sufficient I CT current to also switch the right GNR to the FM state. This right GNR then provides sufficient current into I CB to maintain both GNRs in the FM state. The output current thus becomes 1, and the input SET current can be removed without destabilizing the latch. The operation of this symmetric latch has been demonstrated through the simulation results of Fig. 3 with the behavioral model described in section II.B. The input is driven by pull-up and pull-down ACSL gates, each comprised of a GNR controlled by two CNTs. The output is loaded by two series CNTs from cascaded ACSL gates. V IN has been chosen to be high enough to ensure that the current in the upper and lower CNTs is approximately 60% greater than the current needed to change the two GNRs to FM. As shown in the figure, the latch changes from an initial 0 state, is SET to 1, and then RESET back to 0. Note that when the input current is not applied to the latch (indicated by zero SET and RESET current), the latch maintains its state. IV. SENSOR FOR RRAM ARRAYS As shown in Fig. 4, a non-volatile RRAM array is composed of an RRAM device at each intersection between a bit line and Figure 4. RRAM array with sensors (SA) terminating each bit line (blue) with bits controlled by a word line (red) connecting multiple cells. a word line. When voltage is supplied to a word line, current flows to the various bit lines through the RRAM devices. Depending on the resistance states of the RRAM devices, this bit line current is either large or small. A sensor connected to each bit line converts the RRAM current into a binary signal that can be used within the logic structure. To sense the state within RRAM arrays, it is necessary to detect whether a bit line current is large or small. This task of determining whether an RRAM device is in a conductive or resistive state is well-suited to ACSL circuits, where large and small currents define 1 and 0 states. Therefore, the translation to a voltage required by CMOS sensor circuits is not necessary with ACSL. A. Single-Level Sensor The proposed sensor circuit leverages the concept of the symmetric latch but adds the ability to set the level of the transition to a particular reference value. In this manner, regular reads can be performed at a certain level, with the level later changed for margining or test purposes. The output of the sensing circuit is a measurable change in the resistance of a GNR where the AFM and FM states represent 0 and 1 respectively. Fig. 5 depicts the ACSL bit-current sensor for RRAM arrays comprised of twin ACSL gates. I BIT is the input to the sensor and Figure 3. SPICE simulation of the symmetric latch demonstrating the RESET and SET functionality. Figure 5. ACSL sensor for RRAM arrays.

4 Figure 7. Cascaded RRAM sensors. Figure 6. The left (blue) and right (red) GNR resistance as a function of I BIT, with I REF = 4 µa. represents the current from the memory cell on the bit line. A non-zero, tunable reference level, I REF, is placed on both sides of the sensor with opposing polarity to create the gain mechanism. At an I BIT near zero, both of the GNR devices are in the FM state and divide the I BIT current, and transfer that portion to the other side s second CNT. As the I BIT is increased, the effect on the left device where the reference and I CR currents are in the same direction is to reduce the net current controlling the GNR. As the reduction of the net current approaches the I CRIT for the left GNR, that device begins to change state to AFM and all of the current from I BIT then flows through the right GNR due to the high impedance seen at the left branch. Fig. 6 shows the change in the resistance of the left GNR as the I BIT is varied from 0 to 10 µa in a DC sweep. As the current approaches the reference level minus the I CRIT, the resistance begins to change until it saturates near the reference level. An interesting feature of Fig. 5 is that as I BIT increases beyond I REF plus I CRIT, both the left and right devices begin to saturate and because the I CR and I CL currents are well above I REF, the I BIT current evenly divides again between the left and right sides. This causes the resistance of the left GNR to drop by almost two orders of magnitude from the R MAX value. Further increasing I BIT above 10 µa results in both GNRs returning to the FM state. In this fashion, the I CRIT level can be considered as the ACSL analog of an input offset on the lower end and a differential common-mode range on the upper end. B. Cascaded Sensors The symmetry in the behavior of the ACSL gates highlights an issue that limits the range of a single sensing circuit. Options to improve the range can include tuning the ACSL gates to have a higher I CRIT, but this gain comes at the cost of the output of the sensor reading high earlier in the I BIT sweep since the width of the region of high resistance can be approximated by twice the value of I CRIT. The sensor can also be made more accurate by reducing the I CRIT level and moving the onset of the resistive increase in the left GNR closer to the I REF level at the cost of saturating at a lower value above I REF. An alternative solution to this issue can be realized by virtue of the current-controlled aspect of the ACSL devices. In the sensor of Fig. 5, I BIT divides between the two branches and provides the values for I CR and I CL. As there is no loss of current Figure 8. The cascaded left GNR resistance as a function of the current I BIT for I REF=4µA (blue), 6uA (green), and 8uA (purple). The right GNR (red) resistance is constant. to a supply, it is therefore possible to recombine the two currents I CR and I I CL and again form I BIT. The recombined current can then be used in a cascaded sensor as shown in Fig. 7. Each sensor can be used with a separate I REF level, and a simple OR function of all left GNR resistance values can be used to ensure the logic state sensed is correct up to higher and higher values of I BIT. GNR resistances for the three cascaded sensors are shown in Fig. 8. With the overlap between each stage, it is therefore possible to tune the I CRIT to a smaller value to provide for a more accurate result at the lower end of the distribution. V. CONCLUSIONS Interfacing RRAM non-volatile storage with ACSL processing has been demonstrated here with novel latch and sensor circuits. These interface circuits have been shown to be feasible using physical device parameters and a preliminary model in accordance with the available experimental and simulation data. An initial exploration of the capabilities and limitations of these circuits was provided, along with techniques for leveraging the current-based nature of ACSL in novel cascaded sensor circuits. These interface circuits serve as building blocks for the potential replacement of CMOS with a computing system that exploits the high speed of ACSL and the non-volatility of RRAM arrays in an economically viable manner. REFERENCES [1] H. Akinaga and H. Shima, Resistive random access memory (ReRAM) based on metal oxides, Proc. IEEE, vol. 98, no. 12, pp , 2010.

5 [2] J. S. Friedman et al., Cascaded spintronic logic with low-dimensional carbon, Nat. Commun., vol. 8, p , [3] M. Rinkiö, A. Johansson, G. S. Paraoanu, and P. Törmä, High-speed memory from carbon nanotube field-effect transistors with high-κ gate dielectric, Nano Lett., vol. 9, no. 2, pp , Feb [4] B. Cho, K. Kim, C. L. Chen, A. M. Shen, Q. Truong, and Y. Chen, Nonvolatile analog memory transistor based on carbon nanotubes and C60 molecules, Small, vol. 9, no. 13, pp , [5] X.-D. Zhuang et al., Conjugated-polymer-functionalized graphene oxide: Synthesis and nonvolatile rewritable memory effect, Adv. Mater., vol. 22, no. 15, pp , Apr [6] L. Pisani, J. A. Chan, B. Montanari, and N. M. Harrison, Electronic structure and magnetic properties of graphitic ribbons, Phys. Rev. B, vol. 75, no. 6, p , Feb [7] F. Munoz-Rojas, J. Fernandez-Rossier, J. J. Palacios, F. Muñoz-Rojas, J. Fernández-Rossier, and J. J. Palacios, Giant magnetoresistance in ultrasmall graphene based devices, Phys. Rev. Lett., vol. 102, no. 13, p , Apr [8] H. Santos, L. Chico, and L. Brey, Carbon nanoelectronics: unzipping tubes into graphene ribbons, Phys. Rev. Lett., vol. 103, no. 8, p , Aug [9] J. Bai et al., Very large magnetoresistance in graphene nanoribbons, Nat. Nanotechnol., vol. 5, no. 9, pp , Sep [10] C. Hyun et al., Graphene edges and beyond: Temperature-driven structures and electromagnetic properties, ACS Nano, vol. 9, no. 5, pp , [11] J. S. Friedman, N. Rangaraju, Y. I. Ismail, and B. W. Wessels, A spindiode logic family, IEEE Trans. Nanotechnol., vol. 11, no. 5, pp , [12] J. S. Friedman, E. R. Fadel, B. W. Wessels, D. Querlioz, and A. V Sahakian, Bilayer avalanche spin-diode logic, AIP Adv., vol. 5, no. 11, p , [13] Y. Hancock, A. Uppstu, K. Saloriutta, A. Harju, and M. J. Puska, Generalized tight-binding transport model for graphene nanoribbonbased systems, Phys. Rev. B, vol. 81, no. 24, p , Jun [14] J. S. Friedman, B. W. Wessels, D. Querlioz, and A. V. Sahakian, Highperformance computing based on spin-diode logic, in SPIE Spintronics, 2014, vol. 9167, p J. [15] A. Javey et al., High-field quasiballistic transport in short carbon nanotubes, Phys. Rev. Lett., vol. 92, no. 10, p , 2004.

An Autonomous Nonvolatile Memory Latch

An Autonomous Nonvolatile Memory Latch Radiant Technologies, Inc. 2835D Pan American Freeway NE Albuquerque, NM 87107 Tel: 505-842-8007 Fax: 505-842-0366 e-mail: radiant@ferrodevices.com www.ferrodevices.com An Autonomous Nonvolatile Memory

More information

Digital Integrated Circuits A Design Perspective

Digital Integrated Circuits A Design Perspective Semiconductor Memories Adapted from Chapter 12 of Digital Integrated Circuits A Design Perspective Jan M. Rabaey et al. Copyright 2003 Prentice Hall/Pearson Outline Memory Classification Memory Architectures

More information

Advanced Flash and Nano-Floating Gate Memories

Advanced Flash and Nano-Floating Gate Memories Advanced Flash and Nano-Floating Gate Memories Mater. Res. Soc. Symp. Proc. Vol. 1337 2011 Materials Research Society DOI: 10.1557/opl.2011.1028 Scaling Challenges for NAND and Replacement Memory Technology

More information

Digital Integrated Circuits A Design Perspective. Semiconductor. Memories. Memories

Digital Integrated Circuits A Design Perspective. Semiconductor. Memories. Memories Digital Integrated Circuits A Design Perspective Semiconductor Chapter Overview Memory Classification Memory Architectures The Memory Core Periphery Reliability Case Studies Semiconductor Memory Classification

More information

Lecture 6. Alternative storage technologies. All optical recording. Racetrack memory. Topological kink solitons. Flash memory. Holographic memory

Lecture 6. Alternative storage technologies. All optical recording. Racetrack memory. Topological kink solitons. Flash memory. Holographic memory Lecture 6 Alternative storage technologies All optical recording Racetrack memory Topological kink solitons Flash memory Holographic memory Millipede Ferroelectric memory All-optical recording It is possible

More information

Semiconductor Memories

Semiconductor Memories Semiconductor References: Adapted from: Digital Integrated Circuits: A Design Perspective, J. Rabaey UCB Principles of CMOS VLSI Design: A Systems Perspective, 2nd Ed., N. H. E. Weste and K. Eshraghian

More information

ESE 570: Digital Integrated Circuits and VLSI Fundamentals

ESE 570: Digital Integrated Circuits and VLSI Fundamentals ESE 570: Digital Integrated Circuits and VLSI Fundamentals Lec 19: March 29, 2018 Memory Overview, Memory Core Cells Today! Charge Leakage/Charge Sharing " Domino Logic Design Considerations! Logic Comparisons!

More information

Center for Spintronic Materials, Interfaces, and Novel Architectures. Voltage Controlled Antiferromagnetics and Future Spin Memory

Center for Spintronic Materials, Interfaces, and Novel Architectures. Voltage Controlled Antiferromagnetics and Future Spin Memory Center for Spintronic Materials, Interfaces, and Novel Architectures Voltage Controlled Antiferromagnetics and Future Spin Memory Maxim Tsoi The University of Texas at Austin Acknowledgments: H. Seinige,

More information

Semiconductor Memory Classification

Semiconductor Memory Classification Semiconductor Memory Classification Read-Write Memory Non-Volatile Read-Write Memory Read-Only Memory Random Access Non-Random Access EPROM E 2 PROM Mask-Programmed Programmable (PROM) SRAM FIFO FLASH

More information

Wouldn t it be great if

Wouldn t it be great if IDEMA DISKCON Asia-Pacific 2009 Spin Torque MRAM with Perpendicular Magnetisation: A Scalable Path for Ultra-high Density Non-volatile Memory Dr. Randall Law Data Storage Institute Agency for Science Technology

More information

! Charge Leakage/Charge Sharing. " Domino Logic Design Considerations. ! Logic Comparisons. ! Memory. " Classification. " ROM Memories.

! Charge Leakage/Charge Sharing.  Domino Logic Design Considerations. ! Logic Comparisons. ! Memory.  Classification.  ROM Memories. ESE 57: Digital Integrated Circuits and VLSI Fundamentals Lec 9: March 9, 8 Memory Overview, Memory Core Cells Today! Charge Leakage/ " Domino Logic Design Considerations! Logic Comparisons! Memory " Classification

More information

Emerging Interconnect Technologies for CMOS and beyond-cmos Circuits

Emerging Interconnect Technologies for CMOS and beyond-cmos Circuits Emerging Interconnect Technologies for CMOS and beyond-cmos Circuits Sou-Chi Chang, Rouhollah M. Iraei Vachan Kumar, Ahmet Ceyhan and Azad Naeemi School of Electrical & Computer Engineering Georgia Institute

More information

From Spin Torque Random Access Memory to Spintronic Memristor. Xiaobin Wang Seagate Technology

From Spin Torque Random Access Memory to Spintronic Memristor. Xiaobin Wang Seagate Technology From Spin Torque Random Access Memory to Spintronic Memristor Xiaobin Wang Seagate Technology Contents Spin Torque Random Access Memory: dynamics characterization, device scale down challenges and opportunities

More information

ECE 546 Lecture 10 MOS Transistors

ECE 546 Lecture 10 MOS Transistors ECE 546 Lecture 10 MOS Transistors Spring 2018 Jose E. Schutt-Aine Electrical & Computer Engineering University of Illinois jesa@illinois.edu NMOS Transistor NMOS Transistor N-Channel MOSFET Built on p-type

More information

and V DS V GS V T (the saturation region) I DS = k 2 (V GS V T )2 (1+ V DS )

and V DS V GS V T (the saturation region) I DS = k 2 (V GS V T )2 (1+ V DS ) ECE 4420 Spring 2005 Page 1 FINAL EXAMINATION NAME SCORE /100 Problem 1O 2 3 4 5 6 7 Sum Points INSTRUCTIONS: This exam is closed book. You are permitted four sheets of notes (three of which are your sheets

More information

Advanced Topics In Solid State Devices EE290B. Will a New Milli-Volt Switch Replace the Transistor for Digital Applications?

Advanced Topics In Solid State Devices EE290B. Will a New Milli-Volt Switch Replace the Transistor for Digital Applications? Advanced Topics In Solid State Devices EE290B Will a New Milli-Volt Switch Replace the Transistor for Digital Applications? August 28, 2007 Prof. Eli Yablonovitch Electrical Engineering & Computer Sciences

More information

LOGIC CIRCUITS. Basic Experiment and Design of Electronics. Ho Kyung Kim, Ph.D.

LOGIC CIRCUITS. Basic Experiment and Design of Electronics. Ho Kyung Kim, Ph.D. Basic Experiment and Design of Electronics LOGIC CIRCUITS Ho Kyung Kim, Ph.D. hokyung@pusan.ac.kr School of Mechanical Engineering Pusan National University Digital IC packages TTL (transistor-transistor

More information

CMOS Digital Integrated Circuits Lec 13 Semiconductor Memories

CMOS Digital Integrated Circuits Lec 13 Semiconductor Memories Lec 13 Semiconductor Memories 1 Semiconductor Memory Types Semiconductor Memories Read/Write (R/W) Memory or Random Access Memory (RAM) Read-Only Memory (ROM) Dynamic RAM (DRAM) Static RAM (SRAM) 1. Mask

More information

Topics. Dynamic CMOS Sequential Design Memory and Control. John A. Chandy Dept. of Electrical and Computer Engineering University of Connecticut

Topics. Dynamic CMOS Sequential Design Memory and Control. John A. Chandy Dept. of Electrical and Computer Engineering University of Connecticut Topics Dynamic CMOS Sequential Design Memory and Control Dynamic CMOS In static circuits at every point in time (except when switching) the output is connected to either GND or V DD via a low resistance

More information

SEMICONDUCTOR MEMORIES

SEMICONDUCTOR MEMORIES SEMICONDUCTOR MEMORIES Semiconductor Memory Classification RWM NVRWM ROM Random Access Non-Random Access EPROM E 2 PROM Mask-Programmed Programmable (PROM) SRAM FIFO FLASH DRAM LIFO Shift Register CAM

More information

Digital Circuits. 1. Inputs & Outputs are quantized at two levels. 2. Binary arithmetic, only digits are 0 & 1. Position indicates power of 2.

Digital Circuits. 1. Inputs & Outputs are quantized at two levels. 2. Binary arithmetic, only digits are 0 & 1. Position indicates power of 2. Digital Circuits 1. Inputs & Outputs are quantized at two levels. 2. inary arithmetic, only digits are 0 & 1. Position indicates power of 2. 11001 = 2 4 + 2 3 + 0 + 0 +2 0 16 + 8 + 0 + 0 + 1 = 25 Digital

More information

Hw 6 and 7 Graded and available Project Phase 2 Graded Project Phase 3 Launch Today

Hw 6 and 7 Graded and available Project Phase 2 Graded Project Phase 3 Launch Today EECS141 1 Hw 8 Posted Last one to be graded Due Friday April 30 Hw 6 and 7 Graded and available Project Phase 2 Graded Project Phase 3 Launch Today EECS141 2 1 6 5 4 3 2 1 0 1.5 2 2.5 3 3.5 4 Frequency

More information

GMU, ECE 680 Physical VLSI Design 1

GMU, ECE 680 Physical VLSI Design 1 ECE680: Physical VLSI Design Chapter VIII Semiconductor Memory (chapter 12 in textbook) 1 Chapter Overview Memory Classification Memory Architectures The Memory Core Periphery Reliability Case Studies

More information

MTJ-Based Nonvolatile Logic-in-Memory Architecture and Its Application

MTJ-Based Nonvolatile Logic-in-Memory Architecture and Its Application 2011 11th Non-Volatile Memory Technology Symposium @ Shanghai, China, Nov. 9, 20112 MTJ-Based Nonvolatile Logic-in-Memory Architecture and Its Application Takahiro Hanyu 1,3, S. Matsunaga 1, D. Suzuki

More information

Ultralow-Power Reconfigurable Computing with Complementary Nano-Electromechanical Carbon Nanotube Switches

Ultralow-Power Reconfigurable Computing with Complementary Nano-Electromechanical Carbon Nanotube Switches Ultralow-Power Reconfigurable Computing with Complementary Nano-Electromechanical Carbon Nanotube Switches Presenter: Tulika Mitra Swarup Bhunia, Massood Tabib-Azar, and Daniel Saab Electrical Eng. And

More information

Semiconductor memories

Semiconductor memories Semiconductor memories Semiconductor Memories Data in Write Memory cell Read Data out Some design issues : How many cells? Function? Power consuption? Access type? How fast are read/write operations? Semiconductor

More information

Chapter Overview. Memory Classification. Memory Architectures. The Memory Core. Periphery. Reliability. Memory

Chapter Overview. Memory Classification. Memory Architectures. The Memory Core. Periphery. Reliability. Memory SRAM Design Chapter Overview Classification Architectures The Core Periphery Reliability Semiconductor Classification RWM NVRWM ROM Random Access Non-Random Access EPROM E 2 PROM Mask-Programmed Programmable

More information

NRAM: High Performance, Highly Reliable Emerging Memory

NRAM: High Performance, Highly Reliable Emerging Memory NRAM: High Performance, Highly Reliable Emerging Memory Sheyang Ning,2, Tomoko Ogura Iwasaki, Darlene Viviani 2, Henry Huang 2, Monte Manning 2, Thomas Rueckes 2, Ken Takeuchi Chuo University 2 Nantero

More information

A 68 Parallel Row Access Neuromorphic Core with 22K Multi-Level Synapses Based on Logic- Compatible Embedded Flash Memory Technology

A 68 Parallel Row Access Neuromorphic Core with 22K Multi-Level Synapses Based on Logic- Compatible Embedded Flash Memory Technology A 68 Parallel Row Access Neuromorphic Core with 22K Multi-Level Synapses Based on Logic- Compatible Embedded Flash Memory Technology M. Kim 1, J. Kim 1, G. Park 1, L. Everson 1, H. Kim 1, S. Song 1,2,

More information

F14 Memory Circuits. Lars Ohlsson

F14 Memory Circuits. Lars Ohlsson Lars Ohlsson 2018-10-18 F14 Memory Circuits Outline Combinatorial vs. sequential logic circuits Analogue multivibrator circuits Noise in digital circuits CMOS latch CMOS SR flip flop 6T SRAM cell 1T DRAM

More information

LOGIC CIRCUITS. Basic Experiment and Design of Electronics

LOGIC CIRCUITS. Basic Experiment and Design of Electronics Basic Experiment and Design of Electronics LOGIC CIRCUITS Ho Kyung Kim, Ph.D. hokyung@pusan.ac.kr School of Mechanical Engineering Pusan National University Outline Combinational logic circuits Output

More information

Analysis and design of a new SRAM memory cell based on vertical lambda bipolar transistor

Analysis and design of a new SRAM memory cell based on vertical lambda bipolar transistor Microelectronics Journal 34 (003) 855 863 www.elsevier.com/locate/mejo Analysis and design of a new SRAM memory cell based on vertical lambda bipolar transistor Shang-Ming Wang*, Ching-Yuan Wu Institute

More information

1. Introduction : 1.2 New properties:

1. Introduction : 1.2 New properties: Nanodevices In Electronics Rakesh Kasaraneni(PID : 4672248) Department of Electrical Engineering EEL 5425 Introduction to Nanotechnology Florida International University Abstract : This paper describes

More information

Memory, Latches, & Registers

Memory, Latches, & Registers Memory, Latches, & Registers 1) Structured Logic Arrays 2) Memory Arrays 3) Transparent Latches 4) How to save a few bucks at toll booths 5) Edge-triggered Registers L13 Memory 1 General Table Lookup Synthesis

More information

ECE 342 Electronic Circuits. Lecture 35 CMOS Delay Model

ECE 342 Electronic Circuits. Lecture 35 CMOS Delay Model ECE 34 Electronic Circuits Lecture 35 CMOS Delay Model Jose E. Schutt-Aine Electrical & Computer Engineering University of Illinois jesa@illinois.edu ECE 34 Jose Schutt Aine 1 Digital Circuits V IH : Input

More information

This document is an author-formatted work. The definitive version for citation appears as:

This document is an author-formatted work. The definitive version for citation appears as: This document is an author-formatted work. The definitive version for citation appears as: A. Roohi, R. Zand, D. Fan and R. F. DeMara, "Voltage-based Concatenatable Full Adder using Spin Hall Effect Switching,"

More information

Modeling and optimization of noise coupling in TSV-based 3D ICs

Modeling and optimization of noise coupling in TSV-based 3D ICs LETTER IEICE Electronics Express, Vol.11, No.20, 1 7 Modeling and optimization of noise coupling in TSV-based 3D ICs Yingbo Zhao, Yintang Yang, and Gang Dong a) School of Microelectronics, Xidian University,

More information

University of Toronto. Final Exam

University of Toronto. Final Exam University of Toronto Final Exam Date - Apr 18, 011 Duration:.5 hrs ECE334 Digital Electronics Lecturer - D. Johns ANSWER QUESTIONS ON THESE SHEETS USING BACKS IF NECESSARY 1. Equation sheet is on last

More information

ECE 407 Computer Aided Design for Electronic Systems. Simulation. Instructor: Maria K. Michael. Overview

ECE 407 Computer Aided Design for Electronic Systems. Simulation. Instructor: Maria K. Michael. Overview 407 Computer Aided Design for Electronic Systems Simulation Instructor: Maria K. Michael Overview What is simulation? Design verification Modeling Levels Modeling circuits for simulation True-value simulation

More information

CMOS Inverter. Performance Scaling

CMOS Inverter. Performance Scaling Announcements Exam #2 regrade requests due today. Homework #8 due today. Final Exam: Th June 12, 8:30 10:20am, CMU 120 (extension to 11:20am requested). Grades available for viewing via Catalyst. CMOS

More information

5.0 CMOS Inverter. W.Kucewicz VLSICirciuit Design 1

5.0 CMOS Inverter. W.Kucewicz VLSICirciuit Design 1 5.0 CMOS Inverter W.Kucewicz VLSICirciuit Design 1 Properties Switching Threshold Dynamic Behaviour Capacitance Propagation Delay nmos/pmos Ratio Power Consumption Contents W.Kucewicz VLSICirciuit Design

More information

EE141-Fall 2011 Digital Integrated Circuits

EE141-Fall 2011 Digital Integrated Circuits EE4-Fall 20 Digital Integrated Circuits Lecture 5 Memory decoders Administrative Stuff Homework #6 due today Project posted Phase due next Friday Project done in pairs 2 Last Lecture Last lecture Logical

More information

Miniature Electronically Trimmable Capacitor V DD. Maxim Integrated Products 1

Miniature Electronically Trimmable Capacitor V DD. Maxim Integrated Products 1 19-1948; Rev 1; 3/01 Miniature Electronically Trimmable Capacitor General Description The is a fine-line (geometry) electronically trimmable capacitor (FLECAP) programmable through a simple digital interface.

More information

Optical studies of current-induced magnetization

Optical studies of current-induced magnetization Optical studies of current-induced magnetization Virginia (Gina) Lorenz Department of Physics, University of Illinois at Urbana-Champaign PHYS403, December 5, 2017 The scaling of electronics John Bardeen,

More information

A Universal Memory Model for Design Exploration. Ketul Sutaria, Chi-Chao Wang, Yu (Kevin) Cao School of ECEE, ASU

A Universal Memory Model for Design Exploration. Ketul Sutaria, Chi-Chao Wang, Yu (Kevin) Cao School of ECEE, ASU A Universal Memory Model for Design Exploration Ketul Sutaria, Chi-Chao Wang, Yu (Kevin) Cao School of ECEE, ASU Universal Memory Modeling because there is no universal memory device! Modeling needs in

More information

EE141- Fall 2002 Lecture 27. Memory EE141. Announcements. We finished all the labs No homework this week Projects are due next Tuesday 9am EE141

EE141- Fall 2002 Lecture 27. Memory EE141. Announcements. We finished all the labs No homework this week Projects are due next Tuesday 9am EE141 - Fall 2002 Lecture 27 Memory Announcements We finished all the labs No homework this week Projects are due next Tuesday 9am 1 Today s Lecture Memory:» SRAM» DRAM» Flash Memory 2 Floating-gate transistor

More information

Addressing Challenges in Neuromorphic Computing with Memristive Synapses

Addressing Challenges in Neuromorphic Computing with Memristive Synapses Addressing Challenges in Neuromorphic Computing with Memristive Synapses Vishal Saxena 1, Xinyu Wu 1 and Maria Mitkova 2 1 Analog Mixed-Signal and Photonic IC (AMPIC) Lab 2 Nanoionic Materials and Devices

More information

A Novel LUT Using Quaternary Logic

A Novel LUT Using Quaternary Logic A Novel LUT Using Quaternary Logic 1*GEETHA N S 2SATHYAVATHI, N S 1Department of ECE, Applied Electronics, Sri Balaji Chockalingam Engineering College, Arani,TN, India. 2Assistant Professor, Department

More information

Chapter 2 Fault Modeling

Chapter 2 Fault Modeling Chapter 2 Fault Modeling Jin-Fu Li Advanced Reliable Systems (ARES) Lab. Department of Electrical Engineering National Central University Jungli, Taiwan Outline Why Model Faults? Fault Models (Faults)

More information

Construction of a reconfigurable dynamic logic cell

Construction of a reconfigurable dynamic logic cell PRAMANA c Indian Academy of Sciences Vol. 64, No. 3 journal of March 2005 physics pp. 433 441 Construction of a reconfigurable dynamic logic cell K MURALI 1, SUDESHNA SINHA 2 and WILLIAM L DITTO 3 1 Department

More information

GRAPHENE NANORIBBONS Nahid Shayesteh,

GRAPHENE NANORIBBONS Nahid Shayesteh, USC Department of Physics Graduate Seminar 1 GRAPHENE NANORIBBONS Nahid Shayesteh, Outlines 2 Carbon based material Discovery and innovation of graphen Graphene nanoribbons structure Application of Graphene

More information

Carbon Nanotube Synaptic Transistor Network for. Pattern Recognition. Supporting Information for

Carbon Nanotube Synaptic Transistor Network for. Pattern Recognition. Supporting Information for Supporting Information for Carbon Nanotube Synaptic Transistor Network for Pattern Recognition Sungho Kim 1, Jinsu Yoon 2, Hee-Dong Kim 1 & Sung-Jin Choi 2,* 1 Department of Electrical Engineering, Sejong

More information

Graphene, the two-dimensional allotrope of carbon,

Graphene, the two-dimensional allotrope of carbon, External Bias Dependent Direct To Indirect Band Gap Transition in Graphene Nanoribbon Kausik Majumdar,*, Kota V. R. M. Murali, Navakanta Bhat, and Yu-Ming Lin pubs.acs.org/nanolett Department of Electrical

More information

ESE 570: Digital Integrated Circuits and VLSI Fundamentals

ESE 570: Digital Integrated Circuits and VLSI Fundamentals ESE 570: Digital Integrated Circuits and VLSI Fundamentals Lec 21: April 4, 2017 Memory Overview, Memory Core Cells Penn ESE 570 Spring 2017 Khanna Today! Memory " Classification " ROM Memories " RAM Memory

More information

Biasing BJTs CHAPTER OBJECTIVES 4.1 INTRODUCTION

Biasing BJTs CHAPTER OBJECTIVES 4.1 INTRODUCTION 4 DC Biasing BJTs CHAPTER OBJECTIVES Be able to determine the dc levels for the variety of important BJT configurations. Understand how to measure the important voltage levels of a BJT transistor configuration

More information

Symetrix Corporation Background

Symetrix Corporation Background Symetrix Corporation Background Symetrix has strong history as IP provider > 25 years of development >200 U.S. and foreign patents. > $70M in research revenues, royalties and other income from development.

More information

NEM Relay Design for Compact, Ultra-Low-Power Digital Logic Circuits

NEM Relay Design for Compact, Ultra-Low-Power Digital Logic Circuits NEM Relay Design for Compact, Ultra-Low-Power Digital Logic Circuits T.-J. K. Liu 1, N. Xu 1, I.-R. Chen 1, C. Qian 1, J. Fujiki 2 1 Dept. of Electrical Engineering and Computer Sciences University of

More information

Lecture 25. Semiconductor Memories. Issues in Memory

Lecture 25. Semiconductor Memories. Issues in Memory Lecture 25 Semiconductor Memories Issues in Memory Memory Classification Memory Architectures TheMemoryCore Periphery 1 Semiconductor Memory Classification RWM NVRWM ROM Random Access Non-Random Access

More information

NTE74LS181 Integrated Circuit TTL Arithmetic Logic Unit/Function Generator

NTE74LS181 Integrated Circuit TTL Arithmetic Logic Unit/Function Generator NTE74LS181 Integrated Circuit TTL Arithmetic Logic Unit/Function Generator Description: The NTE74LS181 is an arithmetic logic unit (ALU)/function generator in a 24 Lead DIP type package that has the complexity

More information

EE141Microelettronica. CMOS Logic

EE141Microelettronica. CMOS Logic Microelettronica CMOS Logic CMOS logic Power consumption in CMOS logic gates Where Does Power Go in CMOS? Dynamic Power Consumption Charging and Discharging Capacitors Short Circuit Currents Short Circuit

More information

Compact Models for Giga-Scale Memory System. Mansun Chan, Dept. of ECE, HKUST

Compact Models for Giga-Scale Memory System. Mansun Chan, Dept. of ECE, HKUST Compact Models for Giga-Scale Memory System Mansun Chan, Dept. of ECE, HKUST Memory System Needs BL0 Bitline Precharge Circuits BLn WL Read Address Address Decoder H.-S. P. Wong, Stanford Timing Circuits

More information

Performance Analysis of Multilayer Graphene Nano Ribbon as on chip Interconnect.

Performance Analysis of Multilayer Graphene Nano Ribbon as on chip Interconnect. Performance Analysis of Multilayer Graphene Nano Ribbon as on chip Interconnect. G.Chitra 1, P.Murugeswari 2 1 (Post Graduate Student, VLSI Design, Theni Kammavar Sangam College of Technology, Theni, India)

More information

GRAPHENE NANORIBBONS TRANSPORT PROPERTIES CALCULATION. Jan VOVES

GRAPHENE NANORIBBONS TRANSPORT PROPERTIES CALCULATION. Jan VOVES GRAPHENE NANORIBBONS TRANSPORT PROPERTIES CALCULATION Jan VOVES Czech Technical University in Prague, Faculty of Electrical Engineering, Technicka 2, CZ-16627 Prague 6 Czech Republic, voves@fel.cvut.cz

More information

Delay and Energy Consumption Analysis of Conventional SRAM

Delay and Energy Consumption Analysis of Conventional SRAM World Academy of Science, Engineering and Technology 13 8 Delay and Energy Consumption Analysis of Conventional SAM Arash Azizi-Mazreah, Mohammad T. Manzuri Shalmani, Hamid Barati, and Ali Barati Abstract

More information

TRANSVERSE SPIN TRANSPORT IN GRAPHENE

TRANSVERSE SPIN TRANSPORT IN GRAPHENE International Journal of Modern Physics B Vol. 23, Nos. 12 & 13 (2009) 2641 2646 World Scientific Publishing Company TRANSVERSE SPIN TRANSPORT IN GRAPHENE TARIQ M. G. MOHIUDDIN, A. A. ZHUKOV, D. C. ELIAS,

More information

Semiconductor Memories. Jan M. Rabaey Anantha Chandrakasan Borivoje Nikolic Paolo Spirito

Semiconductor Memories. Jan M. Rabaey Anantha Chandrakasan Borivoje Nikolic Paolo Spirito Semiconductor Memories Jan M. Rabaey Anantha Chandrakasan Borivoje Nikolic Paolo Spirito Memory Classification Memory Classification Read-Write Memory Non-Volatile Read-Write Memory Read-Only Memory Random

More information

Fault Modeling. 李昆忠 Kuen-Jong Lee. Dept. of Electrical Engineering National Cheng-Kung University Tainan, Taiwan. VLSI Testing Class

Fault Modeling. 李昆忠 Kuen-Jong Lee. Dept. of Electrical Engineering National Cheng-Kung University Tainan, Taiwan. VLSI Testing Class Fault Modeling 李昆忠 Kuen-Jong Lee Dept. of Electrical Engineering National Cheng-Kung University Tainan, Taiwan Class Fault Modeling Some Definitions Why Modeling Faults Various Fault Models Fault Detection

More information

EE141. EE141-Spring 2006 Digital Integrated Circuits. Administrative Stuff. Class Material. Flash Memory. Read-Only Memory Cells MOS OR ROM

EE141. EE141-Spring 2006 Digital Integrated Circuits. Administrative Stuff. Class Material. Flash Memory. Read-Only Memory Cells MOS OR ROM EE141-pring 2006 igital Integrated Circuits Lecture 29 Flash memory Administrative tuff reat job on projects and posters! Homework #10 due today Lab reports due this week Friday lab in 353 Final exam May

More information

Semiconductor Memories

Semiconductor Memories Introduction Classification of Memory Devices "Combinational Logic" Read Write Memories Non Volatile RWM Read Only Memory Random Access Non-Random Access Static RAM FIFO Dynamic RAM LIFO Shift Register

More information

Design of 3D Nanomagnetic Logic Circuits: a Full-Adder Case Study

Design of 3D Nanomagnetic Logic Circuits: a Full-Adder Case Study Design of 3D Nanomagnetic Logic Circuits: a Full-Adder Case Study Robert Perricone, X. Sharon Hu, Joseph Nahas, and Michael Niemier Department of Computer Science and Engineering, University of Notre Dame

More information

Chapter 4 Field-Effect Transistors

Chapter 4 Field-Effect Transistors Chapter 4 Field-Effect Transistors Microelectronic Circuit Design Richard C. Jaeger Travis N. Blalock 5/5/11 Chap 4-1 Chapter Goals Describe operation of MOSFETs. Define FET characteristics in operation

More information

An Extended Hückel Theory based Atomistic Model for Graphene Nanoelectronics

An Extended Hückel Theory based Atomistic Model for Graphene Nanoelectronics Journal of Computational Electronics X: YYY-ZZZ,? 6 Springer Science Business Media, Inc. Manufactured in The Netherlands An Extended Hückel Theory based Atomistic Model for Graphene Nanoelectronics HASSAN

More information

Author : Fabrice BERNARD-GRANGER September 18 th, 2014

Author : Fabrice BERNARD-GRANGER September 18 th, 2014 Author : September 18 th, 2014 Spintronic Introduction Spintronic Design Flow and Compact Modelling Process Variation and Design Impact Semiconductor Devices Characterisation Seminar 2 Spintronic Introduction

More information

ECE 342 Solid State Devices & Circuits 4. CMOS

ECE 342 Solid State Devices & Circuits 4. CMOS ECE 34 Solid State Devices & Circuits 4. CMOS Jose E. Schutt-Aine Electrical & Computer Engineering University of Illinois jschutt@emlab.uiuc.edu ECE 34 Jose Schutt Aine 1 Digital Circuits V IH : Input

More information

Novel Bit Adder Using Arithmetic Logic Unit of QCA Technology

Novel Bit Adder Using Arithmetic Logic Unit of QCA Technology Novel Bit Adder Using Arithmetic Logic Unit of QCA Technology Uppoju Shiva Jyothi M.Tech (ES & VLSI Design), Malla Reddy Engineering College For Women, Secunderabad. Abstract: Quantum cellular automata

More information

Switched Mode Power Conversion Prof. L. Umanand Department of Electronics Systems Engineering Indian Institute of Science, Bangalore

Switched Mode Power Conversion Prof. L. Umanand Department of Electronics Systems Engineering Indian Institute of Science, Bangalore Switched Mode Power Conversion Prof. L. Umanand Department of Electronics Systems Engineering Indian Institute of Science, Bangalore Lecture - 19 Modeling DC-DC convertors Good day to all of you. Today,

More information

EE241 - Spring 2000 Advanced Digital Integrated Circuits. References

EE241 - Spring 2000 Advanced Digital Integrated Circuits. References EE241 - Spring 2000 Advanced Digital Integrated Circuits Lecture 26 Memory References Rabaey, Digital Integrated Circuits Memory Design and Evolution, VLSI Circuits Short Course, 1998.» Gillingham, Evolution

More information

ES250: Electrical Science. HW1: Electric Circuit Variables, Elements and Kirchhoff s Laws

ES250: Electrical Science. HW1: Electric Circuit Variables, Elements and Kirchhoff s Laws ES250: Electrical Science HW1: Electric Circuit Variables, Elements and Kirchhoff s Laws Introduction Engineers use electric circuits to solve problems that are important to modern society, such as: 1.

More information

ECE 342 Electronic Circuits. 3. MOS Transistors

ECE 342 Electronic Circuits. 3. MOS Transistors ECE 342 Electronic Circuits 3. MOS Transistors Jose E. Schutt-Aine Electrical & Computer Engineering University of Illinois jschutt@emlab.uiuc.edu 1 NMOS Transistor Typically L = 0.1 to 3 m, W = 0.2 to

More information

Gate Carrier Injection and NC-Non- Volatile Memories

Gate Carrier Injection and NC-Non- Volatile Memories Gate Carrier Injection and NC-Non- Volatile Memories Jean-Pierre Leburton Department of Electrical and Computer Engineering and Beckman Institute University of Illinois at Urbana-Champaign Urbana, IL 61801,

More information

Spintronics at Nanoscale

Spintronics at Nanoscale Colloquium@NTHU Sep 22, 2004 Spintronics at Nanoscale Hsiu-Hau Lin Nat l Tsing-Hua Univ & Nat l Center for Theoretical Sciences What I have been doing Spintronics: Green s function theory for diluted magnetic

More information

Up/down binary counter with separate up/down clocks

Up/down binary counter with separate up/down clocks FEATURES Synchronous reversible 4-bit counting Asynchronous parallel load capability Asynchronous reset (clear) Cascadable without external logic DESCRIPTION The is a 4-bit synchronous up/down counter

More information

ECE 438: Digital Integrated Circuits Assignment #4 Solution The Inverter

ECE 438: Digital Integrated Circuits Assignment #4 Solution The Inverter ECE 438: Digital Integrated Circuits Assignment #4 The Inverter Text: Chapter 5, Digital Integrated Circuits 2 nd Ed, Rabaey 1) Consider the CMOS inverter circuit in Figure P1 with the following parameters.

More information

Design Of Ternary Logic Gates Using CNTFET

Design Of Ternary Logic Gates Using CNTFET International Journal of Research in Computer and Communication Technology, Vol 4, Issue 3, March -2015 ISSN (Online) 2278-5841 ISSN (Print) 2320-5156 Design Of Ternary Logic Gates Using CNTFET Aashish

More information

JUNCTION LEAKAGE OF A SiC-BASED NON-VOLATILE RANDOM ACCESS MEMORY (NVRAM) K. Y. Cheong ABSTRACT INTRODUCTION

JUNCTION LEAKAGE OF A SiC-BASED NON-VOLATILE RANDOM ACCESS MEMORY (NVRAM) K. Y. Cheong ABSTRACT INTRODUCTION JUNCTION LEAKAGE OF A SiC-BASED NON-VOLATILE RANDOM ACCESS MEMORY (NVRAM) K. Y. Cheong Electronic Materials Research Group, School of Materials and Mineral Resources Engineering, Engineering Campus, Universiti

More information

Topic 4. The CMOS Inverter

Topic 4. The CMOS Inverter Topic 4 The CMOS Inverter Peter Cheung Department of Electrical & Electronic Engineering Imperial College London URL: www.ee.ic.ac.uk/pcheung/ E-mail: p.cheung@ic.ac.uk Topic 4-1 Noise in Digital Integrated

More information

Memory Trend. Memory Architectures The Memory Core Periphery

Memory Trend. Memory Architectures The Memory Core Periphery Semiconductor Memories: an Introduction ti Talk Overview Memory Trend Memory Classification Memory Architectures The Memory Core Periphery Reliability Semiconductor Memory Trends (up to the 90 s) Memory

More information

INTEGRATED CIRCUITS. 74LV259 8-bit addressable latch. Product specification Supersedes data of 1997 Jun 06 IC24 Data Handbook.

INTEGRATED CIRCUITS. 74LV259 8-bit addressable latch. Product specification Supersedes data of 1997 Jun 06 IC24 Data Handbook. INTEGRATED CIRCUITS Supersedes data of 1997 Jun 06 IC24 Data Handbook 1998 May 20 FEATURES Optimized for low voltage applicatio: 1.0 to 3.6 V Accepts TTL input levels between = 2.7 V and = 3.6 V Typical

More information

Realization of 2:4 reversible decoder and its applications

Realization of 2:4 reversible decoder and its applications Realization of 2:4 reversible decoder and its applications Neeta Pandey n66pandey@rediffmail.com Nalin Dadhich dadhich.nalin@gmail.com Mohd. Zubair Talha zubair.talha2010@gmail.com Abstract In this paper

More information

Surface atoms/molecules of a material act as an interface to its surrounding environment;

Surface atoms/molecules of a material act as an interface to its surrounding environment; 1 Chapter 1 Thesis Overview Surface atoms/molecules of a material act as an interface to its surrounding environment; their properties are often complicated by external adsorbates/species on the surface

More information

Exploring Autonomous Memory Circuit Operation

Exploring Autonomous Memory Circuit Operation Exploring Autonomous Memory Circuit Operation October 21, 2014 Autonomous Au-to-no-mous: Merriam-Webster Dictionary (on-line) a. Existing independently of the whole. b. Reacting independently of the whole.

More information

Homework Assignment 09

Homework Assignment 09 Homework Assignment 09 Question 1 (Short Takes) Two points each unless otherwise indicated. 1. What is the 3-dB bandwidth of the amplifier shown below if r π = 2.5K, r o = 100K, g m = 40 ms, and C L =

More information

Lecture 6 NEW TYPES OF MEMORY

Lecture 6 NEW TYPES OF MEMORY Lecture 6 NEW TYPES OF MEMORY Memory Logic needs memory to function (efficiently) Current memories Volatile memory SRAM DRAM Non-volatile memory (Flash) Emerging memories Phase-change memory STT-MRAM (Ferroelectric

More information

NANOTECHNOLOGY FOR ELECTRONICS AND SENSORS APPLICATIONS

NANOTECHNOLOGY FOR ELECTRONICS AND SENSORS APPLICATIONS NANOTECHNOLOGY FOR ELECTRONICS AND SENSORS APPLICATIONS SMALLER FASTER MORE SENSETIVE MORE EFFICIENT NANO CONNECT SCANDINAVIA www.nano-connect.org Chalmers University of Technology DTU Halmstad University

More information

Magnetic core memory (1951) cm 2 ( bit)

Magnetic core memory (1951) cm 2 ( bit) Magnetic core memory (1951) 16 16 cm 2 (128 128 bit) Semiconductor Memory Classification Read-Write Memory Non-Volatile Read-Write Memory Read-Only Memory Random Access Non-Random Access EPROM E 2 PROM

More information

EE105 Fall 2014 Microelectronic Devices and Circuits. NMOS Transistor Capacitances: Saturation Region

EE105 Fall 2014 Microelectronic Devices and Circuits. NMOS Transistor Capacitances: Saturation Region EE105 Fall 014 Microelectronic Devices and Circuits Prof. Ming C. Wu wu@eecs.berkeley.edu 511 Sutardja Dai Hall (SDH) 1 NMOS Transistor Capacitances: Saturation Region Drain no longer connected to channel

More information

THE INVERTER. Inverter

THE INVERTER. Inverter THE INVERTER DIGITAL GATES Fundamental Parameters Functionality Reliability, Robustness Area Performance» Speed (delay)» Power Consumption» Energy Noise in Digital Integrated Circuits v(t) V DD i(t) (a)

More information

Challenges for Materials to Support Emerging Research Devices

Challenges for Materials to Support Emerging Research Devices Challenges for Materials to Support Emerging Research Devices C. Michael Garner*, James Hutchby +, George Bourianoff*, and Victor Zhirnov + *Intel Corporation Santa Clara, CA + Semiconductor Research Corporation

More information

MAHARASHTRA STATE BOARD OF TECHNICAL EDUCATION (Autonomous) (ISO/IEC Certified) State any two Boolean laws. (Any 2 laws 1 mark each)

MAHARASHTRA STATE BOARD OF TECHNICAL EDUCATION (Autonomous) (ISO/IEC Certified) State any two Boolean laws. (Any 2 laws 1 mark each) Subject Code: 17333 Model Answer Page 1/ 27 Important Instructions to examiners: 1) The answers should be examined by key words and not as word-to-word as given in the model answer scheme. 2) The model

More information

Design Considerations for Integrated Semiconductor Control Electronics for a Large-scale Solid State Quantum Processor

Design Considerations for Integrated Semiconductor Control Electronics for a Large-scale Solid State Quantum Processor Design Considerations for Integrated Semiconductor Control Electronics for a Large-scale Solid State Quantum Processor Hendrik Bluhm Andre Kruth Lotte Geck Carsten Degenhardt 1 0 Ψ 1 Quantum Computing

More information