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THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for...

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THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Scien Texas Materials Institute Simulation, Theory and Experiments on Multiphase & Interfacial Flows overy & understanding of fundamental fluid mechani ena in multiphase and interfacial flows ication of understanding to modeling, design and u de and natural processes Research Theme:
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Page 1: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTINRoger T. BonnecazeDepartment of Chemical EngineeringInstitute for Computational Engineering & SciencesTexas Materials Institute

Simulation, Theory and Experiments on Multiphase & Interfacial Flows

• Discovery & understanding of fundamental fluid mechanicalphenomena in multiphase and interfacial flows

• Application of understanding to modeling, design and use of man-made and natural processes

Research Theme:

Page 2: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Current Research ActivitiesCurrent Research Activities

• Multiphase flow of suspensions & emulsions

• Rheology of pastes• Self-assembly of

nanoparticles• Fluid management in

Step-and-Flash Imprint Lithography

• Jay Norman• L. Srivatsan• Brooks Rabideau• Shravi Reddy• Jyoti Seth• Bomi Nam

Post-doctoral researcher• Dr. Hebri Nayak

Current research projectsinclude:

Graduate Students

Page 3: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Multiphase Flow of SuspensionsMultiphase Flow of Suspensions

Inline sensor

Flow System

-1.00 -0.50 0.00 0.50 1.00-1.00

-0.50

0.00

0.50

1.000.540.490.440.390.340.290.240.190.140.090.04

y

x

-1.00 -0.50 0.00 0.50 1.00-1.00

-0.50

0.00

0.50

1.00y

x

Nb=18.6

-1.00 -0.50 0.00 0.50 1.00-1.00

-0.50

0.00

0.50

1.00y

x-1.00 -0.50 0.00 0.50 1.00

-1.00

-0.50

0.00

0.50

1.000.440.400.360.320.280.240.200.160.120.080.04

y

x

Experimental Theoretical

Nb= - 10.1

Page 4: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Oscillating Flow – MRI ImagingOscillating Flow – MRI Imaging

Neutrally buoyant particles generally migrate to center

Except with high frequency pressure-gradient oscillations

Axial concentration variationsoccur as well w/oscillations

Page 5: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Self-Assembly of NanoparticlesSelf-Assembly of Nanoparticles

Development of fundamental understanding of the Development of fundamental understanding of the dynamics of pattern formation in colloidal and nanoscale dynamics of pattern formation in colloidal and nanoscale systemssystems

Novel applications for materials with nanoscale patterns of Novel applications for materials with nanoscale patterns of particles as “active material” or templating agentparticles as “active material” or templating agent

Photonic Devices

Joannopoulos et al.

High-density Magnetic Media

Page 6: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Simulation as a GuideSimulation as a Guide

Wall Charge and Ordering= 1%, red = 42wall = -27.3 wall = -250 Phase Diagram

Page 7: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Fluid Management in SFILFluid Management in SFIL

Photolithography requires expensive optics systems & is limited by wavelength of light Imprint lithography is high throughput and low cost Template takes advantage of E-beam technology – smaller features are possible

SFIL is a favorable alternative to traditional lithography methods:

Page 8: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN Critical Fluid Dynamics in SFILCritical Fluid Dynamics in SFIL

• Imprint time

• Base layer thickness

• Filling by multiple

drops

• Preferential flow paths

• Arresting of droplet flow front

• Filling of template

features

Monomer dropsSmall feature pattern

Largefeature

Page 9: THE UNIVERSITY OF AT AUSTIN Roger T. Bonnecaze Department of Chemical Engineering Institute for Computational Engineering & Sciences Texas Materials Institute.

THE UNIVERSITY OF

AT AUSTIN

SFIL Simulation of Feature Filling

• Development of large scalesimulations -Group & ICES parallel computing clusters

• Development of micromechanics and multi-phase continuum mechanics

• Develop and apply experimental methods to discover & characterize new phenomena

Research MethodsResearch Methods


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