acknowledgements - university of notre damepowers/vv.presentations/conlisk.pdfserum albumin in...

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Verification and Validation at the Micro and Nanoscale

Harvey ZambranoA. T. Conlisk

ProfessorDirector, Computational Micro and Nanofluidics Laboratory

Department Of Mechanical and Aerospace EngineeringThe Ohio State UniversityColumbus, Ohio 43210

[email protected]

http://www.mecheng.osu.edu/cmnf

Workshop on Verification and Validation in

Copyright @ A. T. Conlisk 2011

Workshop on Verification and Validation in Computational Science

The University of Notre DameOctober 18, 2011

AcknowledgementsDr. J. P. AlarieDr. Lei ChenDr. Subhra Datta K ll E

Dr. Shuvo RoyDr. Reza Sadr (GT)Prof. Sherwin SingerP f Mi i Y d (GT)

National Science FoundationNSEC (CANPB)Army Research Office

Kelly EversDr. Mauro FerrariDr. William FissellProf. Derek Hansford Ankan Kumar Jennifer McFerranDr. Thompson MeffordProf. Susan Olesik

Prof. Minami Yoda (GT)Dr. Zhi ZhengDr. Wei ZhuHarvey ZambranoDr. Andrew Zydney


Army Research OfficeDARPANIHCCF

Prof. Susan OlesikJessica PengProf. J. Michael RamseyPrashanth Ramesh

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Outline

• Background and motivation (applications)(applications)

• Definitions

• Alternative Plausible Model: Molecular simulation of electroosmotic flow

• Electroosmotic flow: Lennard JonesElectroosmotic flow: Lennard Jones

• Electroosmotic flow: SPC/E water

• Conclusions


MICROSCALE MEASUREMENTS• Measurement techniques should be nonintrusive

– Little space for probes or connections in microchannels

– Optical techniques tracers– Since most microscale flows steady (and low Re),

temporal resolution not a major issue

• To measure (velocity, temperature, pressure) distributions in microscale flows, need spatial resolutions of O(0.1–1 m)


( )– Weak signals Low SNR– Optical interference (e.g. glare) at wall

• Interfacial effects important– Relatively large surface area, small volume

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What We Can’t Do

• Measure velocity temperature and• Measure velocity, temperature and concentration profiles in a nanochannel for both liquids and gases.• Development of analytical/computational models become not only necessary but

ti l


essential.

• iMEDD configuration. All fluid passes directly

Nanopore Membrane

Ports/Ventsfluid passes directly through nanochannels so we consider each one separately and multiply by the number of channels to obtain total system flow rate.

• Working fluid:Phosphate Buffered Saline(PBS)

Nano-channelArray

Electrode


Buffered Saline(PBS)

Receiver/Donor Chambers withElectrolyte Solutions

Courtesy A. Boiarski, iMEDD

20,000-50,000 channelsChannel heights from 4-50nm

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Synthetic nanochannel membrane for a renal assist device (RAD)

Hindered transport of large (>10,000 Da) sol tes s ch as

Implantable artificialkidney

Da) solutes such as serum albumin in synthetic nanochannel membrane for hemofiltration by a Renal Assist Device(Pressurized)


Upstream surface Section through AB

4 mthick

Slit-shaped nanopore:~10 nm deep, ~50 mm wide

Conlisk et al., Annals of Biomedical Eng, vol 37, no 4, pp. 722‐726, 2009.

SEM of membrane

Surface/volume ratio

Volume=hWL

Surface area=2WL

181022 mhV

S


for h=10 nm

Can tailor surfaces for specific application

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Definitions

•AIAA G-077-1998 Guide for the Verification d V lid ti f C t ti l Fl id D i

•W. L. Oberkampf and C. J. Roy, ``Verification And Validation in Scientific Computing’’, Cambridge, 2010


and Validation of Computational Fluid DynamicsSimulations

Verification

• Reduce the spatial grid size and time step• Manufactured solutions• Unchanged when continuum simulations are performed at the nanoscale


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Validationis the term given to the process ofis the term given to the process of

determining whether the simulation accurately represents the physical problem

of interest. Validation answers the question: Is the computational model an accurate physical representation of the


p y pactual real-world problem?

Validation

• Compare with experimental data• But, profiles can’t be measured in nanoscale channels• Compare integrated quantities• Or use an Alternative Plausible


Model

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Alternative Plausible Model

N t ll i d lid ti b t• Not really viewed as validation, but is a measure of predictive capability• APM provides information on the sensitivity of the problem to entirely different model constructions


different model constructions

Adjust ionic concentration:

Dimensional Analysis

jNanoscale computations

can be validated usingmicroscale experiments


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Alternative Plausible Model

C t t i d d t

APM example: nuclear waste

Create two or more independent models of the same phenomenon


burial (time scale)

Oberkampf and Roy 2010

Alternative Plausible ModelMolecular Dynamics Model of

Electroosmotic Flow in aElectroosmotic Flow in aNanochannel

Zhu, Singer, Zheng and Conlisk, Phys. Rev. E, vol. 71, 2005


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• Ions are charged Lennard-Jones particles

• Uniform negative wall charge

• Lennard-Jones solvent with large ion-solvent

Molecular dynamics simulation

• Lennard-Jones solvent, with large ion-solvent attractions mimics solvation in a polar solvent

• Objective: Compare MD with existing continuum theory -Does continuum theory apply at the nanometer scale?

• 31 cations (.22M), 12 anions (.085M), 7757 solvent (*=0.8)


Does continuum theory apply at the nanometer scale?

• Verified for Poiseuille Flow (pressure driven)

Zhu, Singer, Zheng and Conlisk, Phys. Rev. E(2005)

Electroosmotic flow

Charged walls create charge

Walls are negatively charged.

Charged walls create charge imbalance in the fluid

+ cations

direction of electric field and flow


Electrolyte flows in response to electric field

anions

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cation

anion

solvent

• The fluid is layered near the walls.

MD simulation of electroosmotic flow

y

• Anions are in the center.

• Cations move most rapidly to the right, faster than the solvent.

• Anions net motion is to the right, but slower than cations or solvent.

O i ll ti d i ill


• Occasionally a cation and ion will form a temporary bound pair.

Velocity (mobility) profile =5

When y=1, velocity profile calculated from modified PB theory best agrees with simulation; no continuum breakdown

Travis and Giddens (2000): breakdown for ~5 mol diameters

Move lots of excess chargefrom the wall!

2e

y = 1

y = 2

e


e

e

y = 0

(unmodified PB)

y

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Alternative Plausible ModelMolecular Dynamics Simulations

of a Silica Surface with Discontinuous Charged Patches

in a Chloride-Water FilmZambrano, Pinti, Prakash and Conlisk

To be submitted


charged patches

electric field

free surface

Electroosmotic Flow: SPC/E water

Periodic boundary conditions in

X and Y directions

charged patches

Amorphous silicasubstrate

b c d

h

X

Y

ZEOF


Silica slab: 22.8nm x 3.2nm x 2.32nm (17300 atoms)Water molecules: 14000

Cl ions: 150 (0.55 M), Debye length is 0.41nmTotal atoms = 59450

a = 3.5 nmb = 3.5 nmc = 8.0 nmd = 7.8 nmh = ~6.0nm

electrolyte solution

a b c d

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System with and without charged patches with external EF of 0.05 V/nm

no patches σpatches/σ = -0.5EF EF

a b

σpatches/σ = -1 EF EF

EOF

σpatches/σ = -2


c d

System with and without charged patches with external EF of 0.3 V/nm no patches σpatches/σ = -0.5EF EF

a b

σpatches/σ = -1 EF EF

EOF

σpatches/σ = -2


c d

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Chloride packing density along Z- direction calculated between the electrodes

Copyright @ A. T. Conlisk 2011EF = 0.1V/nmoutermost atom

layer

Chlorides are in bulk between electrodes

Chloride packing density along Z-direction on the largest electrode

EF = 0.1V/nm


a boutermost wall atom layer

Chlorides collect on electrodes

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Water packing density along Z-direction on the largest electrode


EF = 0.1V/nm

Layering at surface

Water axial velocity profiles for systems with patches

σp/σ = -1.0 σp/σ = -0.5


Inflection pt in velocity due to roughness

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Water velocity profiles for the system without patches

Center of first layer of immobile waters

region where molecular structure, water

orientation and surface roughness are not

of immobile waters

Copyright @ A. T. Conlisk 2011MD and Continuum Approach enforcing

Stick Boundary Condition

roughness are not negligible

Conclusions

• Verification procedures are unchanged for ti l l ti t th lcontinuum calculations at the nanoscale.

• Nanoscale computations can be validated by microscale experiments• MD simulations and the continuum analysis can be used as an Alternative


Plausible Model to estimate the sensitivity of electroosmotic flow in a nanochannel to different model paradigms.

acknowledgements - university of notre damepowers/vv.presentations/conlisk.pdfserum albumin in...

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