Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology...

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Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biolog y Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856. [email protected]

Transcript of Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology...

Page 1: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Molecular Simulations of Nano- and Bio-Materials

Venkat Ganesan

Computations

Fluid Mechanics

Biology

Statistical Mechanics

Venkat Ganesan: CPE 3.414, 471-4856. [email protected]

Page 2: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Research Group and Projects

Graduate Students & Projects

M. Shah: Photovoltaics and Solar Cells.Landry K: Properties of Polymer Nanocomposites.David Trombly: Protein-Polysaccharide Mixtures.C. Mahajan: Properties of Fuel Cell Membranes.Thomas Lewis: Dendrimer-DNA complexes. Postdocs

Dr. Victor Pryamitsyn: Simulations of properties of polymer nanocomposites.

Theme: Computer simulations and models to address how the synthetic chemistry controls the self-assembly and properties of polymeric, colloidal and biological materials

Page 3: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Recent Graduates

• Brian Besancon: Air Liquide.• Bharad Narayanan : Frito Lay, Pepsico.• Megha Surve: Shell R&D for Computational Research.• Jamie Kropka: Sandia National Laboratories.• Brad Olsen – co-advisor (Primary advisor: Rachel Segalman, UC Berkeley): Assistant Professor, MIT.• Bill Krekelberg (w/Prof. Truskett): Postdoc at UT Austin

Page 4: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Materials Science: The New Challenges

MolecularCharacteristics

Thermodynamic Conditions

Flow Fields (Nonequilibrium

)

Advanced Materials

Required: A fundamental understanding leading to predictive tools and models for the rational design of

new materials.

Lack of fundamental understanding of the properties of the new materials (Back to “Mix

and Shake ?”)

Page 5: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Fuel Cell Membranes

Proton conducting polymer membrane

(CF2)nC (CF2)n

O

O

SO3-

O

F

H+

O

O

SO3-

H+H2O

CF2

CFF3C

O

CF2CF2

SO3-H+

O

OSO3

-H+

OO

SO3-

H+

A B C

H2O

H2O

H2O

H2O

100 oC

Proton transfer throughpolymer backbone

Performance

Burning issue in fuel cell design

Can we design polymers and exploit their assembly toenhance the cell performance ?

Missing fundamental link

How does morphology determine the cell performance ?

Page 6: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Fuel Cell Membranes

Synthesize Polymers Evaluate Cell Performance

Develop predictive models relatingpolymer chemistry to cell performance

Prof. Bielawski (Chemistry) Prof. Manthiram (ME)

Prof. Ganesan (ChE)

Test and validateDevelop newpolymers

Funded by Office of Naval Research to develop efficient portable power sources

Page 7: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

•Such polymers self-assemble into morphologies

Similarities between Fuel Cell, Photovoltaics andSolar Cells

•Solar cells require continuous nano-channels for transport of electrons and holes between the two electrodes• Recent idea: Use a block copolymer

donoracceptor

Design question in polymer solar cells/photovoltaics

Can we design polymers and exploit their assembly toenhance the device performance ?

Missing fundamental link

How does morphology determine the cell performance ?

Page 8: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

What are Polymer Nanocomposites ?

Polymers (Blends,Block copolymers)

Nano-Fillers

Nanocomposites

Single- and Multi-WalledCarbon Nanotubes

Fullerenes/Buckyballs Montmorillonite

Clays

Page 9: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16

(S

/m)

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

(tan

)-1

0.001

0.01

0.1

1

Electrical ConductivityRheology

Electrical Conductivity of Polymer-Nanotube Composites

A 108 enhancement at a loading of 0.2%!

Page 10: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Issues in Polymer Nanocomposites

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16

(S

/m)

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

(ta

n )

-10.001

0.01

0.1

1

Electrical ConductivityRheology

Polymer-Polymer Polymer-Filler

Why ? How ?

Filler-Filler

Landry

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Outstanding Technical ChallengesNeed to understand phenomena over a vast span of length and time scales !!

Properties

A - nm nm mm

mm tocm

&

Page 12: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Tools of The Trade

Time

Length

Quantum Mechanics(Electrons)

Molecular Dynamics

(Atoms, Bonds)

Mesoscale Models

(Segments, Blobs)

Continuum Models(Fields)

Process Models(Unit Operations)

Statistical Mechanics,Models

New, novel simulationtools

Montecarlo, Molecular dynamicsincorporating atomistic details

Fundamental mechanisms of proton conduction

Page 13: Molecular Simulations of Nano- and Bio-Materials Venkat Ganesan Computations Fluid Mechanics Biology Statistical Mechanics Venkat Ganesan: CPE 3.414, 471-4856.

Research Philosophy for the Group: Provide a collaborative environment with strong interactions with complementary experimentalists and theorists to enable the students to achieve the best education and professional goals.

Experimental Collaborators• Prof. Chris Bielawski• Prof. Ram Manthiram• Prof. Al Bard• Prof. Donald Paul• Prof. Benny Freeman• Prof. Rachel Segalman (Berkeley)• Prof. Chang Ryu (RPI)

Theory Collaborators

Prof. Thomas Truskett Prof. Dima Makarov (Chemistry)