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MEMRISTORS
A Technical Seminar Report
Submitted to
JAWAHARLAL NEHRU TECHNOLOGYICAL UNIVERSITY,
ANANTAPUR
In partial fulfillment of the requirement for the award of the degree of
BACHELOR OF TECHNOLOGY
In
ELECTRONICS AND COMMUNICATION ENGINEERING
By
B.VENKATA SAI SRAVAN KUMAR
08691A04B7
Department of Electronics and Communication Engineering
MADANAPALLE INSTITUTE OF TECHNOLOGY AND SCIENCE
(Approved by AICTE, New Delhi, Affiliated to JNTU, Anantapur)
P.B.No.14,Angallu,Madanapalle 517325,Andhra Pradesh
MADANAPALLE INSTITUTE OF TECHNOLOGY & SCIENCE
(Approved by AICTE, New Delhi, Affiliated to JNTU, Anantapur)
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
BONAFIDE CERTIFICATE
This is to certify that this seminar report “MEMRISTORS” submitted in partial
fulfillment of the requirement for the award of the degree of Bachelor of Technology in
Electronics and communication Engineering is a result of the bonafide work carried out by
B.Venkata Sai Sravan Kumar (08691A04B7). He/She/They is /are bonafide student
/students of this college studying IV year B.Tech during the academic year 2011-2012.
Prof.A.R.REDDY,M.Tech.,Ph.D
Head of the department
Dept of ECE
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acknoeledment
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INDEX
(I) Abstract
5
Chapter 1. INTRODUCTION
6
Chapter 2. BACKGROUND
8
2.1 Physical restrictions
Chapter 3. MEMRISTIVE SYSTEMS
10
11
3.1 Operation as a Switch
3.2 Physical restrictions
3.3 Types of Memristors
11
12
14
Chapter 4. APPLICATIONS OF MEMRISTORS
15
4.1 Potential Applications
18
Chapter 5. CONCLUSION
21
Chapter 6. REFERNCES
22
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(1)ABSTRACT
The Mysterious Memristor-The future memory device
Imagine a computer system that can think like the human brain & take the
decisions on its own. Researches at HP (Hewlett Packard) labs have solved a
decades-old mystery by proving the existence of a fourth element in integrated
circuits that could make it possible to develop computers with some of the
pattern-matching abilities of the human brain. A memristor is a passive twoterminal circuit element in which the resistance is a function of the history of
the current through and voltage across the device. Memristor theory was
formulated and named by Leon Chua in 1971.Considering the relationships
between charge and flux in resistors, capacitors, and inductors Chua postulated
the existence of a fourth element called the memory resistor. Such a device, he
figured, would provide a similar relationship between magnetic flux and charge
that a resistor gives between voltage and current. In practice, that would mean it
acted like a resistor whose value could vary according to the current passing
through it and which would remember that value even after the current
disappeared.Here we are going to present about the resent trends in electronics
about the memristor as a future fastest memory device.
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MEMRISTORS
CHAPTER 1
INTRODUCTION
What Are Memristors?
Fig 1.1 Classification of devices
What is a MEMRISTOR? Memristors are basically a fourth class of electrical
circuit, joining the resistor, the capacitor, and the inductor, that exhibit their
unique properties primarily at the nanoscale. Theoretically, Memristors, a
concatenation of “memory resistors”, are a type of passive circuit elements that
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maintain a relationship between the time
integrals of current and voltage across a
two terminal element. Thus, a memristors
resistance varies according to a devices
memristance function, allowing, via tiny
read charges, access to a “history” of
applied
voltage.
The
material
implementation of memristive effects can
Fig 1.2 Memristor
be determined in part by the presence of
hysteresis (an accelerating rate of change as an object moves from one state to
another) which, like many other non-linear “anomalies” in contemporary circuit
theory, turns out to be less an anomaly than a fundamental property of passive
circuitry.
Researchers were able to formulate a physics-based model of a memristor and
build nanoscale devises in their lab that demonstrates all of the necessary
operating characteristics to prove that the memristor was real. A solid-state
device could have the characteristics of a memristor based on the behavior of
nanoscale thin films. The device neither uses magnetic flux as the theoretical
memristor suggested, nor stores charge as a capacitor does, but instead achieves
a resistance dependent on the history of current.
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CHAPTER 2
BACKGROUND
A memristor is a passive two-terminal electronic component for which the
resistance (dV/dI) depends in some way on the amount of charge that has
flowed through the circuit. When current flows in one direction through the
device, the resistance increases; and when current flows in the opposite
direction, the resistance decreases, although it must remain positive. When the
current is stopped, the component retains the last resistance that it had, and
when the flow of charge starts again, the resistance of the circuit will be what it
was when it was last active.
Here in this figure we can see the relation between the flux & voltage(Φ & v)
and the relation between voltage & charge(v & q) and the relation between
charge & current(q & i) but the missing relation is in between the charge &
flux(q & Φ). So, this is given by the memristive relation. This made the
scientists think of the fourth fundamental element the MEMRISTOR.
More generally, a memristor is a twoterminal component in which the resistance
depends on the integral of the input applied
to the terminals (rather than on the
instantaneous value of the input as in a
resistor). Since the element "remembers"
the amount of current that has passed
through it in the past, it was tagged by with
the name "memristor."
Fig 2.1 Relationship with devices
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Another way of describing a memristor is that it is any passive two-terminal
circuit elements that maintains a functional relationship between the time
integral of current (called charge) and the time integral of voltage (often called
flux, as it is related to magnetic flux). The slope of this function is called the
memristance (M) and is similar to variable resistance.
Batteries can be considered to have memristance, but they are not passive
devices. The definition of the memristor is based only on the fundamental
circuit variables of current and voltage and their time-integrals, just like the
resistor, capacitor, and inductor. Unlike those three elements however, which
are allowed in linear time-invariant or LTI system theory, memristors of interest
have a nonlinear function and may be described by any of a variety of functions
of net charge. There is no such thing as a standard memristor. Instead, each
device implements a particular function, wherein the integral of voltage
determines the integral of current, and vice versa. A linear time-invariant
memristor is simply a conventional resistor.
Memristor theory was formulated and named by Leon Chua, extrapolating the
conceptual symmetry between the resistor, inductor, and capacitor, and inferring
the memristor was a similarly fundamental device. Other scientists had already
proposed fixed nonlinear flux-charge relationships, but Chua's theory
introduced generality.
Like other two-terminal components (e.g., resistor, capacitor, inductor), realworld devices are never purely memristors ("ideal memristor"), but will also
exhibit some amount of capacitance, resistance, and inductance. Note however
that a "memristor" with constant M and a resistor with constant R are the same
thing.
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Newton said that force is proportional to acceleration–the change in velocity.
This is exactly the situation with electronic circuit theory today. All electronic
textbooks have been teaching using the wrong variables–voltage and charge–
explaining away inaccuracies as anomalies. What they should have been
teaching is the relationship between changes in voltage, or flux, and charge.”
2.1 Physical restrictions on M(q)
M(q) is physically restricted to be positive for all values of q (assuming the
device is passive and does not become superconductive at some q). A negative
value would mean that it would perpetually supply energy when operated with
alternating current.An applied constant voltage potential results in uniformly
increasing Φm. It is not realistic for the function M(q) to contain an infinite
amount of information over this infinite range. Three alternatives avoid this
physical impossibility:

M(q) approaches zero, such that Φm = ∫M(q)dq = ∫M(q(t))I(t) dt
remains bounded but continues changing at an ever-decreasing rate.
Eventually, this would encounter some kind of quantization and non-ideal
behavior.

M(q) is periodic, so that M(q) = M(q − Δq) for all q and some Δq,
e.g. sin2(q/Q).

The device enters hysteresis once a certain amount of charge has
passed through, or otherwise ceases to act as a memristor.
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Chapter 3
MEMRISTIVE SYSTEMS
The memristor was generalized to memristive systems in 1976 by Leon Chua.
Whereas a memristor has mathematically
scalar state, a system has vector
state. The number of state variables is independent of and usually greater than,
the number of terminals.
Chua applied this model to empirically observed phenomena, including the
Hodgkin-Huxley model of the axon and a thermistor at constant ambient
temperature. He also described memristive systems in terms of energy storage
and easily observed electrical characteristics. These characteristics match
resistive random-access memory and phase-change memory, relating the theory
to active areas of research.
3.1 Operation as a switch
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For some memristors, applied current or voltage will cause a great change in
resistance. Such devices may be characterized as switches by investigating the
time and energy that must be spent in order to achieve a desired change in
resistance. Here we will assume that the applied voltage remains constant and
solve for the energy dissipation during a single switching event.
This power characteristic differs fundamentally from that of a metal oxide
semiconductor transistor, which is a capacitor-based device. Unlike the
transistor, the final state of the memristor in terms of charge does not depend on
bias voltage.
Another kind of switch would have a cyclic M(q) so that each off-on event
would be followed by an on-off event under constant bias. Such a device would
act as a memristor under all conditions, but would be less practical.
3.2 Replacement for D-RAM
The research team made it possible for engineers to develop integrated circuit
designs that take advantage of its ability to retain information. This opens up a
whole new door in thinking about how chips could be designed and operated.
Engineers could develop a new kind of computer memory that would
supplement and eventually replace today’s commonly used dynamic random
access memory (D-RAM).
Computers using conventional D-RAM lack the ability to retain information
once they are turned off. when power is restored to a D-RAM based computers ,
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a slow ,energy –consuming “Boot up “ process is necessary to retrieve data
stored on a magnetic disc required to run the system.
fig 3.2 Computer Memristor
Memristor- based computers would not require that process, using less power
and possibly increasing system resiliency and reliability. The memristor could
have applications for computing, cell phones, video games-anything that
requires a lot of memory without a lot of battery power drain.
They can also be fashioned into non-volatile solid – state memory, which
would allow greater data density than hard drives with access times potentially
similar to D-RAM, replacing both components.
A crossbar latch memory using the devices that can fit 100 gigabits in a square
centimeter, and has designed a highly scalable 3D design (consisting of up to
1000 layers or 1 petabit per cm3).The memristor is currently about one – tenth
the speed of D-RAM. The device’s resistance would be read with alternating
current so that the stored value would not be affected.
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The applications of memristors are innumerable from programmable logic,
signal processing, neural networks, and control systems and many other devices
will use these in future.
3.3 TYPES OF MEMRISTORS
Many types of memristors are under development such as:
 Titanium dioxide memristors
 Polymeric (ionic) memristors
 Manganite memristive systems
 Resonant-tunneling diode memristors
 Spin based and magnetic memristive systems
 Spintronic memristors
 3-terminal memristors
 Hybrid memristor-transistor
 Meminductor and memcapacitor
fig 3.3 Types of Memristor
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CHAPTER 4
APPLICATION OF MEMRISTOR
What Memristive applications are on
the horizon, and how close are they to
reality? We look at a survey of
memristor
applications
and
technology, starting from what the first
devices will look like, and where they
might go. This reference page will be
updated as advances in each of the
areas are made.
Non-volatile memory applications:
fig 4.1 NVRAM
Memristors can retain memory states, and data, in power-off modes. Nonvolatile random access memory, or NVRAM, is pretty much the first to-market
memristor application we’ll be seeing. There are already 3nm Memristors in
fabrication now. Crossbar latch memory (see below) developed by Hewlett
Packard is reportedly currently about one-tenth the speed of DRAM.
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Low-power and remote sensing applications:
Coupled with memcapacitors and meminductors, the complementary circuits to
the memristor which allow for the storage of charge, memristors can possibly
allow for nano-scale low power memory and distributed state storage, as a
further extension of NVRAM capabilities. These are currently all hypothetical
in terms of time to market.
Crossbar Latches as Transistor Replacements or Augmenters:
The hungry power consumption of transistors has been a barrier to both
miniaturization and microprocessor controller development. Solid-state
memristors can be combined into devices called crossbar latches, which could
replace transistors in future computers, taking up a much smaller area. There are
difficulties in this area though, although the benefits these could bring are
focusing a lot of money in their development. Unless a competition war
amongst industry giants becomes one of those patent showdowns, where
companies buy out technological advances to bury them. Remember 3G? Well,
someone bought out 4G back in 2004, before 3G even came to market, and has
been sitting on it ever since. And have profited greatly.
Analog computation and circuit Applications:
Analog computations embodied a whole area of research which, unfortunately,
were not as scalable, reproducible, or dependable (or politically expedient in
some cases) as digital solutions. However, there still exist some very important
areas of engineering and modeling problems which require extremely complex
and difficult workarounds to synthesize digitally: in part, because they map
economically onto analog models. The early work of Norbert Wiener has
already started to be revisited, after the analog/digital split between him and
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John von Neumann. Analog was great, but required management for scalability
beyond what even the extremely complex initial digital vacuum tube computers
could provide.
Programmable Logic and Signal Processing, and a variety of Control System
memristor patents are out there, waiting for the microchips to fall where they
may. The memristive applications in these areas will remain relatively the same,
because it will only be a change in the underlying physical architecture,
allowing their capabilities to expand, however, to the point where their
applications will most likely be unrecognizable as related.
Memristor on a chip, by substituting some transistors with memristors, more
physical space can be created for more components to be added, increasing the
computing power in the process-and reducing energy consumption.
Brain-like systems, Memristors are virtually immune from radiation that can
disrupt transistor–based technology; they are an attractive way to allow eversmaller but ever-more-powerful devises. Because they do not “forgot”.
Memristors can allow computers that turn on and off like a light switch. Since
our brains are made of memristors, the flood gate is now open for
commercialization of computers that would compute like human brains, which
is totally different from the von Neumann architecture underpinning all digital
computers.
A new architecture within which multiple layer of memristor memory can be
stacked on top of each other in a single chip. These chips could be used to create
handles devices that offer ten times greater embedded memory than exists today
or to power supercomputers that allow work like movie rendering and genomic
research to be done dramatically faster.
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Fifaamfsk
Hybrid memristor-transistor, Instead of
increasing the number of transistors on a
circuit,
a
hybrid
circuit
with
fewer
transistors could be built with the addition of
memristors leading to more functionality.
Fig 4.2 Hybrid Memristor
Memristor technologies could enable more energy-efficient high-
density
circuits. A hybrid chip using conventional CMOS technology and nanoscale
switching devices was developed.
“Recently, logic circuits also have been demonstrated that use two or three
elements of a one-dimensional memristor array, although such passive devices
without gain are difficult to cascade. These circuits fall short of the
requirements for a scalable, multifunctional nanoprocessor, owing to challenges
in materials, assembly and architecture on the nanoscale.
4.1 POTENTIAL APPLICATIONS
Solid-state memristors can be combined into devices called crossbar latches,
which could replace transistors in future computers, taking up a much smaller
area.
They can also be fashioned into non-volatile solid-state memory, which would
allow greater data density than hard drives with access times potentially similar
to DRAM, replacing both components. HP prototyped a crossbar latch memory
using the devices that can fit 100 gigabits in a square centimeter, and has
designed a highly scalable 3D design (consisting of up to 1000 layers or 1
petabit per cm3). HP has reported that its version of the memristor is currently
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about one-tenth the speed of DRAM. The devices' resistance would be read with
alternating current so that the stored value would not be affected.
Some patents related to memristors appear to include applications in
programmable logic, signal processing,
neural networks, and control systems.
Recently, a simple electronic circuit
consisting of an LC network and a
memristor
was
used
to
model
experiments on adaptive behavior of
unicellular organisms. It was shown
that the electronic circuit subjected to a
train of periodic pulses learns and
Fig 4.3 Potential Application
anticipates the next pulse to come, similarly to the behavior of slime molds
Physarum polycephalum subjected to periodic changes of environment. Such a
learning circuit may find applications, e.g., in pattern recognition. The
DARPA’s SYNAPSE project has funded HP Labs, in collaboration with the
Boston University Neuromorphics Lab, to develop neuromorphic architectures
which may be based on memristive systems. In 2010, Massimiliano Versace
and Ben Chandler co-wrote an article
describing the MoNETA (Modular
Neural Exploring Traveling Agent) model. MoNETA is the first large-scale
neural network model to implement whole-brain circuits to power a virtual and
robotic agent compatibly with memristive hardware computations.
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CHAPTER 5
CONCLUSION
The semiconductor industry’s obsession with the shrinking of transistors and
their commensurate steady doubling on a chip about every two years has been
the source of a 50 years technical and economic revolution. Whether this scaling
model last for five more years or 15, it will eventually come to an end. The
emphasis in electronics design will have to shift to devices that are not just
increasingly infinitesimal but increasingly capable. Memristor is the perfect
example for such a device.
Emulating the behavior of a single memristor, it was demonstrated that a circuit
with at least 15 transistors and systems could be replaced by a single memristor.
These memristors can be turned into “integrated other passive elements. The
implications are extordinary circuits that remember information, consume far
less power just imagine how many kinds of circuits could be than existing
devices, and may someday learn from past supercharged by replacing a handful
of transistors with one behavior. An analog computer is a computational device
in single memristor.
It turns out that memristance is becoming stronger as the feature sizes in circuits
are getting smaller. At some point as we scale into the realm of nanoelectronics, it will be necessary to explicitly take account of memristance in the
circuit models in order to simulate and design electronic circuits properly.
Combined with transistors in a hybrid chip, memristors could radically improve
the performance of digital circuits without shrinking transistors. In the end,
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memristors might even become the cornerstone of new analog circuits that
compute using architecture much like that of the brain.
The future of memristors is very bright and many applications from virtual
reality, robotics, medical that will have far reaching benefits to the industry as
well as the users.
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CHAPTER 6
REFERNCES
[1] Memristor -the Missing Circuit Element . (1971 ) , Leon Chua
[2] Missing link of electronics (2008-04-30), Marks. P
[3] HP nano device implements memristor ((2 May 2008)), Bush.S
[4] HP makes memory from a once-theoretical circuit (30 April 2008), Kanellos.M
[5] Reproducible switching effect in thin oxide films for memory applications, Beck.A
[6] Memristor Pattern Recognition Circuit Architecture for Robotics, Mouttet Blaise L
[7]Study of Test Structures of a Molecular Memory Element (1993), Krieger
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