XVIII Brain Storming Day - Unict · XVIII Brain Storming Day ... 0.075 0.08 0.085 0.09 0.095 water 5 Hz - air 12 Hz Time [s] Voltage [V] ... Water pumped 10Hz Water pumped 10Hz

XVIII Brain Storming Day

UNIVERSITA’ DEGLI STUDI DI CATANIADipartimento di Ingegneria Elettrica Elettronica e dei Sistemi DIEES

Florinda Schembri

Tutors: prof. Luigi Fortuna, prof. Maide Bucolo

Microfluidic SystemsMicrofluidic Systems

� In vitro

� In vivo

� in vitro pro in vivo

OptoOpto--Sensing SystemSensing System

Identification & ModelingIdentification & Modeling

� Microscopy-Based

� Opto-Mechanic System

� Polymeric micro-Optic Interface

RealReal--Time Monitoring Time Monitoring

� Point-wise (0D)

� Full-Field (2D)

� Droplet Formation

� Chaotic Advection

� Multiphysics

� CFD on GRID

� 2D numerical

modeling

OutlineCorrelation between

Spatial and Temporal

nonlinear behaviour

Correlation between

Spatial and Temporal

nonlinear behaviour Experimental Modeling of

Two-Phase microfluidic Flow

Experimental Modeling of

Two-Phase microfluidic Flow

Synchronization between a ‘microfluidic air bubble ’ and a

‘bubble robot’ (in collaborazione con l’ ing. Camerano).

Synchronization between a ‘microfluidic air bubble ’ and a

‘bubble robot’ (in collaborazione con l’ ing. Camerano).

Bubbles in microchannels…some applications

Bubble Logic Microreactors

‘Beakers’Mixing

Experimental Modeling

CONTROL

Micro Total Analisys Sistem (µTAS)

Emulsion Science

F. Sapuppo, F.Schembri , M. Bucolo, “Nonlinear Dynamics in Experimental Two-Phase Microfluidics Timeseries”, Chaos 09, June 22-24, 2009, London, UK.

generation and transport of

micrometric bubbles and

droplets in IN VITRO systems

Observing nonlinear Phenomena in Microfluidics

Microscope Opto sensors

Electro – Optical Workbench

frame 3

Processing

- Preprocessing

Nonlinear Time Series Analysis� Reconstructed attractor

� Divergence of trajectories

� Largest Lyapunov Exponent

0.06

0.07

0.08

0.09

0.1

0.11 0.0650.07

0.0750.08

0.0850.09

0.095

0.065

0.07

0.075

0.08

0.085

0.09

0.095

x2x1

x3

Analysis tool: TISEAN 2.1

ThinXXS, Germany

Complex Microfluidic Flow

Two Phase FlowSerpentine Microchannel

Micro pumps:- Frequency- Flow rate [ml/s]

H2O

Water

Analog Signals

relative effect of viscous forces versus surface tension acting

across an interface between a liquid and a gas

The microfluidic process

Droplets Formation

Nonlinear InstabilityFinite time singularity

[Eggers, Rev. Mod. Phys., 1997]

µρ uL=Re

γµu

Ca =

� Mutual interaction between fluids; � Interaction with the channel boundary ;� Flow rates;

Break up driven by:� normal stress� tangential stress

( )( )[ ] ( )NFuupIuut

u T φσκδηρ ++∇+∇+−⋅∇=

∇⋅+∂∂

0=⋅∇ u

Navier Stokes and Mass Conservation Dimensionless Number

1Re

100Re

<<<

Laminar flow

Inertial Force / Viscous Force

)10( 2−≈ OCa

Droplet FormationJunction

Flow FocusingT-junction

Serpentine

One

Phase

Two

Phases

Axi-symmetric flow focusing bubble

generator

The microfluidic process

Nonlinear convection

Two Phase Flow

DynamicsTwo Phase Flow

Dynamics

Nonlinear temporal

dynamics of bubbles

The baker’s trasformation

From Microscopic Process …

… to Macroscopic Behavior

FLOW PATTERN

frame 3

[Song et al., Chem. , Int. Ed. Engl. , 2003]

Reorientation

Centrifugal Forces

Nonlinear Convection

Experimental Setup

R1

R2

S

Serpentine Geometric Specification

Frequency �� Volumetric Flow Rate [V]

� S: 640 µm;� R1: 280 µm;� R2: 920 µm;

Optical System

Reynolds number <20Capillary number<0.01

ThinXXS, Germany

Pulsatile Pumps

Air

Water (carried fluid)

9.5 9.55 9.6 9.65 9.7 9.75 9.8 9.85 9.9 9.95 100.065

0.07

0.075

0.08

0.085

0.09

0.095water 5 Hz - air 12 Hz

Time [s]

Vol

tage

[V

]

The electro-optic system

Photodiodes (Silonex , SLD-70BG2A)Infrared Rejection Filter -Planar Photodiode

Captur light variation caused by bubbles flow.

CA

D

Design

Projected image

Open Space Design� Multiple Access � Tunable Magnification � Easy Sensing Integration

SIDE VIEW TOP VIEW Magnification=3.1X

Analog Signals

0 10 20 30 40 50 600

5

10

15

20

25

30

35

40

Frequency [Hz]

Am

plitu

de

Pre-processing analysis and filtering

8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 100.065

0.07

0.075

0.08

0.085

0.09


Time [s]

Vol

tage

[V

]

9.5 9.55 9.6 9.65 9.7 9.75 9.8 9.85 9.9 9.95 100.065

0.07

0.075

0.08

0.085

0.09


Time [s]

Vol

tage

[V

]

Fast Fourier TransformFast Fourier Transform

Filtering• Low pass (cut off 60 Hz)• Notch (50Hz, pump frequencies)

Filtering• Low pass (cut off 60 Hz)• Notch (50Hz, pump frequencies)

ValidationFiltered vs not filtered

signal

ValidationFiltered vs not filtered

signal

11 11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9 120.05

0.06

0.07

0.08

0.09

0.1

0.11

Vol

tage

[V

]

fitered signalfitered signalfitered signalfitered signalnot filtered signalnot filtered signalnot filtered signalnot filtered signal

Experimental validation

Two phase FlowWater 5Hz-Air 7HzTwo phase Flow

Water 5Hz-Air 7Hz

Time [s]

Vol

tage

[V

]

Reference SignalsReference Signals

Water pumped 10Hz Water pumped 10Hz

Air pumped 10Hz Air pumped 10Hz

6.5 6.55 6.6 6.65 6.7 6.75 6.8 6.85 6.9 6.95 70.04

0.042

0.044

0.046

0.048

0.05

0.052

0.054

0.056

0.058

0.06Photodiode Signals

TIme [s]

Vol

tage

[V

]

water 10Hz

water 30Hz air 25Hz

water 30Hz air 5Hzwater 30Hz air 60Hz

water 50Hz air 25Hz

Different input frequencies produce different Bubble Flow

Different input frequencies produce different Bubble Flow

Signals comparison

Time window0.5 sec

Time window0.5 sec

Volumetric Flow rate vs Frequency

Nonlinear time series analysis

� Delay ;

� Embedding Dimension ;

� Divergence of trajectories (dj);

� Asymptotic value of the dj (d∞ )

�Finite size Lyapunov exponents;

False nearest neighbours

[Rosenstein et al., Physica D 65, 117 ,1993].

[E. Aurell et al., J. Phys. A 30, 1, 1997] d∞

Typical trend of the

ddjj between nearby

chaotic trajectories

in semilog scale

(Chua’s system)

( ) ( )i

j

N

i

ijj xx

Nd '

1

1 −⋅= ∑=

∑=

∞→∞ ⋅=N

jj

Nd

Nd

1

1lim

Distance between pairs of j-iteration long

trajectories mediate over N couples

Analysis tool: TISEAN 2.1

Autocorrelation function

Experiment Design

Experimental CampaignExperimental Campaign

Controller (frequency

signal)

H2O

Air

Frequency �� Volumetric Flow Rate

ThinXXS, Germany

Water freq fixed-Air freq

multiple of the water

freq

Water freq fixed-Air freq

not multiple of the

water freq

Air freq fixed- Water

freq not multiple of the

water freq


freq multiple of the

water freq


flow rate constant

Nonlinear time series analysis results

0.08

0.09

0.1 0.075 0.08 0.085 0.09 0.095

0.075

0.08

0.085

0.09

0.095

x2x1

x3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-3

-2.8

-2.6

-2.4

-2.2

-2

-1.8

-1.6

dj

Time [s]

log(

d j)

10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 12

0.075

0.08

0.085

0.09

0.095segnale filtrato con Notch

Time [s]

Vol

tage

[V

]

Delay Emb. Largest

λ

Dj ris. T

[s]

|D_inf|

10 4 1,10 0,052 1,93


0.06

0.07

0.08

0.09

0.1

0.11 0.06

0.07

0.08

0.09

0.1

0.11

0.06

0.08

0.1

0.12

x2

3d 355 new

x1

x3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-3.6

-3.4

-3.2

-3

-2.8

-2.6

-2.4

-2.2

dj

Time [s]

log(

d j)

10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 120.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

Time [s]

Vol

tage

[V

]

Delay Emb. Largest

λ

Dj ris. T

[s]

|D_inf|

9 4 0,64 0,25 2,15


0.060.065

0.070.075

0.080.085

0.09 0.06

0.065

0.07

0.075

0.08

0.085

0.09

0.06

0.07

0.08

0.09

x2

x1

x3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-3.8

-3.6

-3.4

-3.2

-3

-2.8

-2.6

-2.4

dj

Time [s]

log(

d j)

10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 120.06

0.065

0.07

0.075

0.08

0.085

0.09

Time [s]

Vol

tage

[V

]

Delay Emb. Largest

λ

Dj ris. T

[s]

|D_inf|

19 4 0,88 0,082 2,73


3025

0.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

0.065

0.070.075

0.080.085

0.090.095

0.1

0.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

x1

3d 205 new

x2

x3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-3.3

-3.2

-3.1

-3

-2.9

-2.8

-2.7

-2.6

-2.5

-2.4

dj

Time [s]

log(

d j)

10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 120.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

Time [s]

Vol

tage

[V

]

Delay Emb. Largest

λ

Dj ris. T

[s]

|D_inf|

12 5 0,58 0,222 2,51

10 Attractors…

0.06

0.08

0.1

0.12 0.06 0.065 0.07 0.075 0.08 0.085 0.09 0.095

0.06

0.07

0.08

0.09

0.1

0.11

x2x1

0.06

0.08

0.1

0.12 0.065 0.07 0.075 0.08 0.085 0.09 0.095

0.065

0.07

0.075

0.08

0.085

0.09

0.095

x2x1

x3

0.06

0.07

0.08

0.09

0.06

0.07

0.08

0.090.06

0.065

0.07

0.075

0.08

0.085

0.09

x1

3d 532 new

x2

x3

0.06

0.08

0.1

0.12

0.065 0.07 0.075 0.08 0.085 0.09 0.095

0.065

0.07

0.075

0.08

0.085

0.09

0.095

x1

3d 305 new

x2

x3

0.06 0.08 0.1 0.120.065 0.07 0.075 0.08 0.085 0.09 0.095 0.1

0.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

x2

3d 405 new

x1

x3

0.08 0.09 0.1 0.075 0.08 0.085 0.09 0.095

0.075

0.08

0.085

0.09

0.095

x2

3d 155 new

x1

x3

0.08

0.09

0.10.075 0.08 0.085 0.09 0.095

0.075

0.08

0.085

0.09

0.0953d 55 new

x2x1

x3

0.06

0.07

0.08

0.09

0.1

0.11

0.060.07

0.08

0.090.1

0.06

0.08

0.1

0.12

x1

3d 540 new

x2

x3 0.06

0.08

0.1

0.120.065 0.07 0.075 0.08 0.085 0.09 0.095 0.1

0.06

0.07

0.08

0.09

0.1

0.11

x2

3d 205 new

x1x3

0.06

0.07

0.08

0.09

0.10.11 0.065 0.07 0.075 0.08 0.085 0.09 0.095 0.1

0.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

x2

3d 355 new

x1

x3

Nonlinear time series analysisD-infinite

(aria 5 Hz, acqua 25:2:35 Hz)Aria 5 Hz, acqua 7:5:37 Hz

Noise Rejection

Conclusions

CFD analysis and experimental observation

Computational

Fluid Dynamics

(CFD)Experimentation

Nonlinearity inside droplets

Temporal nonlinear flow

Correlation between spatial and temporal

NONLINEAR BEHAVIOUR

Primary FlowSecondary Flow

Velocity of the bubble relative to

wall

Flow within bubble

F. Sapuppo, F.Schembri , M. Bucolo, “Correlation between Spatial and Temporal Chaotic Behaviour in Two-Phase Microfluidics”, Chaos 09 June 22-24, 2009,

London, UK.

Ch

an

ne

l W

idth

Digital Image25 fps

Digital SlitTime Series

Experimental SetupOptic System Analog Digital

Acquisition

PC based Image

processingPump Control

Discrete Opto-Mechanical System

Two phaseFlow

ThinXXS, Germany

Computational Fluid Dynamics (CFD)

Numerical Model (PDEs)

( )

∇∇−−∇⋅∇=∇⋅+

∂∂

φφφφφεγφ

1ut

0

0

0

2

1

>Φ=Φ

<Φ

phase

countour

phase

( )( )[ ] ( )NFuupIuut

u T φσκδηρ ++∇+∇+−⋅∇=

∇⋅+∂∂

0=⋅∇ u

( ) ( )φρρρρ Hphasephasephase 121 −+=

( ) ( )φηηηη Hphasephasephase 121 −+=

Level Set Equations

Navier Stokes and

mass conservation

Properties of the Two fluids

How we deal with Two Phase Flow?

Mul

tiph

ysic

s A

ppro

ach

Computational Fluid Dynamics (CFD)

y

tyxu

x

tyxu

∂∂−

∂∂ ),,(),,(

2D Vorticity field

amount of “rotation” in a fluid

Spatial nonlinear behaviorSpatial nonlinear behavior

The vorticity is the rotation of thefluid velocity

and as such gives an idea of how the fluid is

moving inside the bubble .

Mixing

2D Analysis

Experiment one: Air 5 Hz Water 10 Hz

-20-10

010

2030

-20

0

20

40-20

-10

0

10

20

30

x1

5 1 3

x2

x3

-20-10

010

20

-20

-10

0

10

20-15

-10

-5

0

5

10

15

x1x2

x3

-15 -10 -5 0 5 10 15-15

-10

-5

0

5

10

15

Aria5-Acqua

20

xy

x1

x2

3D reconstructed attractor and xy view

-40-20

020

40

-40

-20

0

20

40-30

-20

-10

0

10

20

30

x1x2

x3

-30 -20 -10 0 10 20 30-30

-20

-10

0

10

20

305 4 x

x1

x2

Experiment three: Air 5 Hz Water 40 Hz

Volume Fraction of water and Vorticity Field

Experiment two: Air 5 Hz Water 20 Hz

FROM…..Numerical Modeling To….. Experimental Campaigns

IdentificationIdentification …… Chaotic Advection

Synchronization between a ‘microfluidic air bubble ’ and

a ‘bubble robot’CFD Simulation

(Comsol Multiphysics ®)CFD Simulation

(Comsol Multiphysics ®)

Cod

e Im

plem

enta

tion

Cod

e Im

plem

enta

tion File TXT (Velocity Field) File TXT (Velocity Field)

Matlab scriptMatlab script

File TXTVelocity, Time


Bluetooth


a ‘bubble robot’

(in collaborazione con l’ ing. Camerano)(in collaborazione con l’ ing. Camerano)

Water 25 Hz-Air 2HzWater 25 Hz-Air 2Hz

Tw

o-P

hase

Flo

w a

nd C

FD

(C

omso

l Mul

tiphy

sics

®)

T

wo-

Pha

se F

low

and

CF

D

(Com

sol M

ultip

hysi

cs ®

)

Serpentine Channel

Velocity field Vorticity

Volume fraction……..

Velocity field Vorticity

Volume fraction……..




0.220.23

0.240.25

0.260.27 0.135

0.14

0.145

0.15

0.1550

0.2

0.4

0.6

0.8

yx

velo

ciy

filed

[m

/s]

v=0.527 m/s

T=0.1 sec

Velocity FieldVelocity Field

Bub

ble

Tra

king

B

ubbl

e T

raki

ng

0.225

0.23

0.235

0.24

0.245

0.25

0.255

0.26 0.136

0.138

0.14

0.142

0.144

0.146

0.148

0.15

0.152

0.154

0.156

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

y

x

velo

city

fie

ld [

m/s

]

v=0.377 m/s




T=0.2 sec


Bub

ble

Tra

king

B

ubbl

e T

raki

ng

0.225

0.23

0.235

0.24

0.245

0.25

0.255

0.26

0.136 0.138 0.14 0.142 0.144 0.146 0.148 0.15 0.152 0.154 0.156

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

v=0.53 m/s




Bub

ble

Tra

king

B

ubbl

e T

raki

ng

T=0.3 sec





Velocity – Time Micorfluidic Bubble

Velocity – Time Micorfluidic Bubble

Velocity – Time Bubble Robot

Velocity – Time Bubble Robot

Experimental RelationTime-Velocity of the

two systems0.3: 93=0.5275:x

X=Time of the bubble in the new system (Bubble Robot)

[0.1 sec].

Experimental RelationTime-Velocity of the

two systems0.3: 93=0.5275:x

X=Time of the bubble in the new system (Bubble Robot)

[0.1 sec].

Exp

erim

enta

l Ana

lysi

s E

xper

imen

tal A

naly

sis



Future Trend� Several ad hoc experimental campaigns;� New nonlinear analysis methods (peak to peak, Poincaré maps, etc…);� Spectral analysis;� 3D CFD simulations;

Correlation of input parameters to nonlinear indicators (modeling)

Control the nonlinear flow of microbubbles

� Metodi e Modelli Numerici per Campi e Circuiti (Prof. S. Alfonsetti)

� Materiali Polimerici per la Microelettronica (Prof. A. Pollicino)

� Controllo Robusto (Prof. L. Fortuna)

� 6 Febbraio-12 Marzo 2008, International Winter School on Grid

Computing IWSGC’08 (on line course, University of Edimburg)

� 27-29 Novembre 2007, Tutorial su metodi numerici per sistemi di

calcolo parallelo ad alte prestazioni (INFN)

� 14-19 Luglio 2008, Introduzione al Controllo Non Lineare (Scuola

Sidra di Dottorato, Bertinoro (Fo))

� 22-26 Settembre 2008, An Introduction to Computational Fluid

Dynamics (Scuola Superiore di Catania)

Attended courses and Tutorials

Scientific Publications

F. Schembri, F. Sapuppo, E. Leggio, M. Iacono Manno, M. Bucolo, L. Fortuna, “A Grid Computational Approach to a Two Phase Flow in Microfluidics”, Workshop Progetti Grid del PON "Ricerca" 2000-2006 - Avviso 1575, Catania, Italy, February 10-12, 2009.

F. Sapuppo, F.Schembri , M. Bucolo, “Experimental Investigation on Parameters for the Control of Droplets Dynamics ”, Physcon 2009, September 1-4, 2009, Catania, Italy.

F. Sapuppo, F.Schembri , M. Bucolo, “Correlation between Spatial and Temporal Chaotic Behaviour in Two-Phase Microfluidics”, Chaos 09 June 22-24, 2009, London, UK.

F. Sapuppo, F.Schembri , M. Bucolo, “Nonlinear Dynamics in Experimental Two-Phase Microfluidics Timeseries”, Chaos 09, June 22-24, 2009, London, UK.

M. Bucolo, J. Esteve, L. Fortuna, A. Llobera, F. Sapuppo, F. Schembri, ‘A Disposable Micro-lectro-Optical Interface for Flow Monitoring in Bio-Microfluidics’, 12th International Conference on Miniaturized Systems for Chemistry and Life Sciences (µTAS 2008), San Diego, California, October 12-16, 2008.

M. Bucolo, L. Fortuna, A. Llobera, F.Sapuppo, F. Schembri, ‘Integrated Devices for Investigation of Nonlinear Dynamics in Microfluidics’, 10th Experimental Chaos Conference (ECC10), June 3-6, 2008, Catania, Italy

M. Bucolo, L. Fortuna, F. Sapuppo, F. Schembri, ‘Chaotic Dynamics in Microfluidic Experiments’ The 18th Int. Symposium on Mathematical Theory of Networks and Systems (MTNS 2008), Blacksburg, Virginia, USA, 28 July –1 August 2008.

M. Bucolo, L. Fortuna, F. Sapuppo, F. Schembri. (2008). “Experimental Chaos in Microfluidic Devices”. In: The 10th Experimental Chaos Conference”. Catania, Italy, June 3-6, p. 1

XVIII Brain Storming Day - Unict · XVIII Brain Storming Day ... 0.075 0.08 0.085 0.09 0.095 water 5 Hz - air 12 Hz Time [s] Voltage [V] ... Water pumped 10Hz Water pumped 10Hz

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