memristors: a new age in electronics for sensors and...

S.Carrara, EPFL Lausanne

(Switzerland)1

Moscow, 12 Moscow, 12 Sept.Sept., 2011, 2011

Memristors: Memristors:

A New Age A New Age

in Electronicsin Electronics

for Sensors for Sensors

and Memoriesand Memories


(Switzerland)2

Tutorial OverviewTutorial Overview

� Concepts about Memristors

� Methods to fabricate memristors

� Structures of cross-bars based and

single- wires Memristors

� Measurements on Memristive effects

� Applications to Memories

� Applications to Neural Nets

� Applications to Nano-Bio-sensing

S.Carrara, EPFL - Lausanne

(Switzerland)3

Memristors First ConceptMemristors First Concept

dq

dv

di

dϕ

Four different circuit parameters:

dq

dϕ

)(),(),(),( ttqtitv ϕ

di

dv

The missed equation!

R=

C

1=

L=

M=


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The Memristor requestThe Memristor request

Symmetry reasons seem demanding for Memristors


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So, M = R in

case of constant

charge!

( )[ ]( )

dq

qdtqM

ϕ=

( )( )

Rtdi

tdv=

( )

dt

dqdt

qdϕ

=

Memristor depending on Charge Flux:

The usual Resistance:

( )di

qdv=

While, M will be an R with memory

effect in case of varying charge!

)(qR=


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The NameThe Name

Memory

Resistor

MEMRISTOR


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Memristor with lateral injectionMemristor with lateral injection

Carriers are injected by the source side

S D


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A two-terminals Memristor may be modeled by through two resistors as an element which vary the

resistance upon the applied voltage

Possible Memristor ModelPossible Memristor Model


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( ) )()(

1)(

tiD

twR

D

twRtv OFFON

−+=

)()(

tiD

R

dt

tdw ONVµ=

−= )(1)(

2tq

D

RRqM ONV

OFF

µ

)()( tqD

Rtw ON

Vµ=

More evident at nano-scale!


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Current/Voltage CharacteristicsCurrent/Voltage Characteristics

Memristic effects are observable in I-V curves

as a memory of the channel doping in time


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How to build a Memristor?How to build a Memristor?

“These results serve as the foundation for

understanding a wide range of hysteretic

current-voltage behavior observed in many

nano-scale electronic devices”

“[…] until now no one has presented either a

useful physical model or an example of a

memristor”


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Pt/TiOPt/TiO22--xx/TiO/TiO22/Pt memristors/Pt memristors

12

Source: Yang et al, Nature Nanotechnology 2008

O-v i


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Memristors by organicMemristors by organic

Carrier may be injected by the top polymer

S D


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Organic MemristorOrganic Memristor

14

Source: Berzina et al, Applied Materials & Interfaces 2009

Li or Rb+v i


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Memristors in polyMemristors in poly--SiliconSilicon

Thursday, September 22, 2011 15

Source: Ben-Jamaa, Carrara et al., IEEE Nano 2009


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Sizes OverviewSizes Overview

Insulator

(SiO2)

Poly-Si

spacer

Si substrate

• Dimensions are

not true to scale!

• Only frontend

processing is

depicted

• Backend includes

passivation +

metallization

~ 400 nm~ 400 nm

~ 70 nm

~ 70 nm~ 20 nm


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Fabrication ResultsFabrication Results

The SEM imaging shows the quality of poly-silicon wires fabricated by using spacers technique


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The registered I/V curves show memristic effects due to

a memory of the swept voltage windows


Electrons de-trapping

Electrons trapping

Holes trapping

Holes de-trapping


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Conductivity MechanismsConductivity Mechanisms

Both electrons and holes based conductivity is affected by Memristor effect


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The registered I/V curves show memristic effects due to

a memory of the swept voltage windows



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)()()()()( EgEgEgEgEg GDGATDTA +++=

TD

v

W

EE

TDTD eNEg

−

=)(

2

)(

−−

= GA

GA

W

EE

GAGA eNEg

2

)(

−−

= GD

GD

W

EE

GDGA eNEg

TA

c

W

EE

TATA eNEg

−

=)(

Tail States Gaussian StatesAcceptors State

Donors State

Simulations by Simulations by

driftdrift--diffusion modeldiffusion model


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2D Simulations by Atlas follow the experimental

data accounting for negative trapped charges at the

Poly-Si/SiO2 interface

-20 -10 0 10 20

10-11

10-10

10-9

10-8

10-7

Simulation

Dra

in C

urr

en

t (

A)

Gate Voltage (V)

Experiment

Simulations ResultSimulations Result


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Memristors by BulkMemristors by Bulk--Silicon, tooSilicon, too



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Memristors by CrystallineMemristors by Crystalline--SiliconSilicon

24

Source: D.Sacchetto, .., Carrara, et al., IEEE ISCAS 2010


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Silicon NanowiresSilicon Nanowires

25

Polysilicon

Gate All

Around

c-Si nanowire

channel


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Reliable for High ParallelismReliable for High Parallelism

Silicon nanowire transistors with Schottky Barrier Source/Drain are emerging devices candidates for next generation transistor technology

26

Source: Sacchetto et al., ESSDERC 2009


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Memristive BehaviorMemristive Behavior

27

V0(Vds)

Vds Ids

Vgs and t are

constants

Vds as the

input

x80

c-SiNW : Ids-Vds


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Hysteretic Charge TrappingHysteretic Charge Trapping


c-SiNW : Sweep frequency dependence

V0(Vgs,

t)

Vgs

t

Ids

Vds as the

constant

Vgs and t as the

input

t


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Theory of Operation (1)Theory of Operation (1)


e- h+

constant Vds

Vgs polarity

selects the

type of carrier

S SD D

e-/h+v i


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( )1/))((/ 0 −⋅=

−− kTVVVkT

sdsdsB eeII

φ

Schottky Barrier height

Schottky barrier built-in voltage

),,()( 00 tVVVVV gsds=

Ids

S D


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V0(Vds,Vgs,t)

Vgs

Vds

t

Ids

INP

UT

S

STATE

variable

OUTPUT


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Simplification of model-w structure


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Model-w equivalent circuit


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∫=⇒ dttVL

aw )(

µ

[ ]btaL

w +=⇒ )(ϕµ

Eadt

dwµ=

L

tVa

)(µ=


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VVV rl γ=−

0)(1 =

−−+− ti

L

wRVVV sirl

That’s the Kirchoff’s Voltage Law


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0)(1 =

−−− ti

L

wRVV SIγ

That’s the Kirchoff’s Voltage Law

)(

1

)1(ti

L

wR

V

SI

=

−

−γ)()()( tVGti ϕ=⇒


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Comparison of model-w with measurements


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State variable after addition of phase parameter


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Equivalent Circuit Model


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Explanation of circuit operation


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Equivalent Circuit Model vs measurements


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Applications to MemoryApplications to Memory

Monolithic 3D integration of state-of-the-art transistor technologies with memristive devices, with opportunities for high-density 3D crossbar

construction:

� Multi-level Resistive RAMs

� Dynamic RAMs

42

GATE

lines

CHANNEL lines


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Crossbar Memristors for (RRAM)

resistive random-access-memory (RRAM) from hysteretic resistive memristive devices


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Crossbar Memristors for (RRAM)Crossbar Memristors for (RRAM)


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Memristive Programmable Devices by Through Silicon Vias

Concept image of planar Re-RAM made of Pt/TiO2/Pt stack


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Reconstructed 3D photograph of the TSV −Cu/TiO2/Pt device stack.


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Resistive switching through I − V sweeps for planar Pt/TiO2/Pt


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Resistive switching through I − V sweeps using TSV

− Cu/TiO2/Pt programmable fuse

Memristive Programmable Memristive Programmable

Devices by Through Silicon Devices by Through Silicon ViasVias


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Resistive switching through I − V sweeps using TSV − Pt/TiO2/Pt programmable fuse

Memristive Programmable Memristive Programmable

Devices by Through Silicon Devices by Through Silicon ViasVias


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Applications to NeuralApplications to Neural--NetsNets

Nanoscale Memristor Device as Synapse in Neuromorphic Systems


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The change in current in sequential voltage sweeps

The The

LearningLearning


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Neural Nets by organic materials as well


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Homo- (a) and hetero- (b)

Synaptic junctionsModel of learning for Limnea

Stagnalis: association of the

mechanical stimulus with presence of

food

Neural Network of a Snail

SYNAPSES


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Input 1 – mechanical (neutral) stimulus

Input 2 – presence of food

Output: current as a result of the presence

of the neutral stimulus only

Training: application of both stimuli

Organic

memristive device

–synapse analog

V. Erokhin et al., BioNanoScience, 1, 24-30 (2011)

Neural Network of a Snail


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Measure of the Carriers Measure of the Carriers

injectioninjection

The Li+ ions normally used to dope PEO were not

adequate for such measurements because their fluorescent

energy cannot be detected at atmospheric conditions.

Thus, the heavier Rb ions were used


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Measure of the Carriers Measure of the Carriers

injectioninjection

Grazing-incidence X-ray fluorescence measurements were applied for a time-resolved study of an organic memristor conductivity variation

mechanism


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Applications to BioApplications to Bio--SensingSensing

Frontend Passivation

BackendFunctionalization

Definition of Silicon

nanowire

Isolation of devices,

via opening for

metalization and

functionalization

Metalization: NiCr

or Cr/NiCr or Al

Grafting of bio-

probes


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pH Dependent SensorpH Dependent Sensor� pH Sensor obtained by modifying Si oxide surface with 3-

aminopropyltriethoxysilane yielding amino and silanol groups (acting as receptors) at surface

Patolsky et al., Nanowire-Based Biosensors, Analytical Chemistry, 2006, 4261-4269

Protonation/deprotonation altered charge density at surface thereby changing conductance


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Detecting Single VirusDetecting Single Virus� When virus binds to antibody receptor, conductance changes from

baseline value

� When it unbinds, conductance returns to baseline value

Patolsky et al., Nanowire-Based Biosensors, Analytical Chemistry, 2006, 4261-4269

Ultra-dense NW device where minimum scale is set by

size of virus


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Concept in Memristors forConcept in Memristors for

NanoNano--BioBio--SensingSensing

The charging from molecules affects the Memristic

effects onto the poly-silicon channel

Back Gate

Nitride Passivation

Nano-wire channel

Top-gate


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Memristors for NanoMemristors for Nano--BioBio--SensingSensing


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Suspended Si ribbon with 600nm trench dimension before sacrificial oxidation



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Suspended Si nanowire with 100nm diameter and hard mask

opened at contact regions before Ni/Ti metal deposition



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14.8nm14.8nm

12.8nm12.8nm

9.3 nm9.3 nm

The size of an AntibodyThe size of an Antibody


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Bio affects MemconductanceBio affects Memconductance

Ids − Vds curves taken (1) before and (2) after

memristive-biosensors functionalization

Minima Minima

VoltageVoltage

GapGap


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Bio affects MemconductanceBio affects Memconductance

Ids − Vds curves: before and after the up-take of 5 pM AG solution.


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The charges of an Antibody?The charges of an Antibody?

The crystallographic structure of an antibody


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Charged ResiduesCharged ResiduesPositively Charged

Arginine

+

Histidine

+

Lysine

+

Polar Uncharged

-

Aspartic Acid

-

Glutamic Acid

Neg. Charged

-

-

+

+

Serine

-

+

Threonine

-

+

Aspargine

-

+

Glutamine

-

+

-

+

-

+ +

-


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The charges of an AntibodyThe charges of an Antibody

The crystallographic structure of an antibody


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• Memristors are devices with a memory of its bias story

• Memristic effect has been registered in I/V characteristics with both organic and inorganic materials, including Silicon

• 2D simulations and Fluorescent Measurements confirmed that Memristic effects are due to charges trapping in the Channel

• Applications of memristic devices are feasible for Memories, biomorphic networks, and Biosensors

• Nano-electronics is now at the beginning of a new age thanks to the exploitation of Memristors

ConclusionsConclusions

(c) S.Carrara, EPFL - Lausanne

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Thanks to:Thanks to:

� Davide Sacchetto

� Haykel Ben Jamaa

� Marie-Agnès Doucey

� Akshat Dave

� Pietro Dalmastro

� Julius Georgiou

� Victor Erokhin

� Yusuf Leblebici

� Giovanni De Micheli


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Coordinates:Dr. Sandro Carrara Ph.D

Integrated Laboratory Systems

Swiss Federal Institute of Technology (EPFL)

CH-1015 Lausanne

Web: http://si2.epfl.ch/~scarrara/

email: [email protected]

Thank you for your attention!Thank you for your attention!

memristors: a new age in electronics for sensors and...

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