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Multiscale Simulations of Electronic and Fluidic Nanoscale Systems - - PowerPoint PPT Presentation

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Multiscale Simulations of Electronic and Fluidic Nanoscale Systems Amir Taqieddin , Mohammad Heiranian, and Narayana Aluru Beckman Institute for Advance Science & Technology Mechanical Science & Engineering Department University of

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Multiscale Simulations of Electronic and Fluidic Nanoscale Systems

Amir Taqieddin, Mohammad Heiranian, and Narayana Aluru Beckman Institute for Advance Science & Technology Mechanical Science & Engineering Department University of Illinois at Urbana-Champaign

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SLIDE 2

Beckman Institute for Advanced Science and Technology

Acknowledgment

  • We use Blue Waters in performing multiscale simulations and to

study multi-physics systems.

  • M. Heiranian et al., THE JOURNAL OF

CHEMICAL PHYSICS 147, 104706 (2017)

  • A. Moradzadeh & N.R. Aluru, The

Journal of Physical Chemistry Letters 2019, 10 (6), pp 1242–1250

  • Y. Jing et al., Chemistry of Materials

2018, 30 (138-144)

  • A. Farimani et al., Npj 2d Materials

and Applications 2, 1-9 (2018) M.T. Hwang et al., submitted to publication in April 2019

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Beckman Institute for Advanced Science and Technology

Acknowledgment

  • Blue Waters allowed us to use different software with high

computational performance.

  • We were able to obtain ~28

times scaling compared to 1 node (32 cores).

  • The code performs up to 90% of

the ideal performance.

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Beckman Institute for Advanced Science and Technology

Outline

  • New Power Scaling in the Concentration - Ionic Conductance

Relation in CNT.

  • Thickness Dependent Nanofluidic Transport in Nanopores

and Nanochannels.

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Beckman Institute for Advanced Science and Technology

Ionic Conductance

R.H. Tunuguntla et al. Science 357.6353 (2017): 792-796.

  • M. Heiranian et al . Nature

communications 6 (2015): 8616.

  • J. Feng et al. Nature 536.7615

(2016): 197.

  • M. Manghi et al. Physical Review

E 98.1 (2018): 012605.

  • Ionic transport in nanofluidic systems is associated with multi-physics

phenomena: 1) Diffusion and migration of ions. 2) Electro-osmotic flow. 3) Surface charge regulation. 4) Confinement. 𝐻 ∝ 𝑑$; 𝛽 = 1, 0, 1/3,1/2, and 2/3

  • The ionic conductance in CNTs shows a power law

relation.

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Beckman Institute for Advanced Science and Technology

Ionic Conductance

  • Continuum simulations allow us to investigate the contribution of each

component (diffusion, migration, and convection).

  • We couple Poisson-Nernst-Planck (PNP) with Navier-Stokes (NS):

CNT Reservoir Reservoir Symmetry axis

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Beckman Institute for Advanced Science and Technology

Ionic Conductance

  • Observed 2/3 power scaling.
  • Used molecular dynamics to correct the

continuum model and estimate the experimental surface charge.

  • Selectivity coefficient (𝐽./0123/𝐽/3123) of ~3.7.

𝑒 = 14 π‘œπ‘› 𝑀 = 10 π‘œπ‘› 𝑒 = 1.5 π‘œπ‘› 𝑀 = 10 π‘œπ‘›

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Beckman Institute for Advanced Science and Technology

Ionic Conductance

  • Studied the effect of surface charge on the molecular transport.

Surface charge (mC/m<) 𝑣water(m/s) 𝑣KE (m/s)

  • 27

2.9Β±0.29 2.31

  • 54

3.01Β± 0.28 2.45

  • 114

1.98Β±0.42 2.15

  • Computed average velocity of water

and potassium ions in (11,11) CNT with L= 10 nm at a concentration of 1 M using molecular dynamics simulations.

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Beckman Institute for Advanced Science and Technology

Outline

ΓΌ New Power Scaling in the Concentration - Ionic Conductance Relation in CNT.

  • Thickness Dependent Nanofluidic Transport in Nanopores

and Nanochannels.

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Beckman Institute for Advanced Science and Technology

Thickness Dependent Nanofluidic Transport

  • In fluid dynamics, the flow rate of pressure driven fluid is generally described by

Hagen-Poiseuille equation, in a circular pipe: 𝑅 = πœŒΞ”π‘„π‘ L 8πœˆβ„Ž

  • Carbon nanotubes are shown to have several orders of magnitude higher

permeation rate than that of existing membranes. Holt et al. Science (2006). Experimentally, CNT is shown to very high flow rates (enhancement

  • ver

no slip classical theory of ~1000). Joseph et al. Nano Lett. (2008). Fast water transport is also

  • bserved

computationally due to highly frictionless walls of CNTs.

h

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Beckman Institute for Advanced Science and Technology

Thickness Dependent Nanofluidic Transport

0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.01 0.1 1 10 100 1000 (10,10) CNTs & GRP

1/h (nm

  • 1)

Permeation coefficient (10-25 m3/Pa s)

HP with Β΅ Β΅ and l variations NEMD HP with Β΅Β₯ and lΒ₯ HP with no slip Dagan et al.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.1 1 10 100 1000 (14,14) CNTs & GRP

1/h (nm

  • 1)

Permeation coefficient (10 -25m3/Pa s)

HP with Β΅ Β΅ and l variations NEMD HP with Β΅Β₯ and lΒ₯ HP with no slip Dagan et al.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.1 1 10 100 1000

Permeation coefficient (10-25 m3/Pa s) 1/h (nm-1)

HP with Β΅ Β΅ and l variations NEMD HP with Β΅Β₯ and lΒ₯ HP with no slip Dagan et al.

(18,18) CNTs & GRP

  • We compared our corrected HP with:

HP with no slip Dagan model for finite-length tubes HP with bulk properties HP with MD simulations

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Beckman Institute for Advanced Science and Technology

Thickness Dependent Nanofluidic Transport

  • In experiments, transport rates have been shown to be enhanced by several
  • rders of magnitudes over the rates predicted by the no-slip HP theory.
  • When the enhancement factors were reassessed using the corrected HP theory,

they approach unity.

0.1 1 10 100 1000 10000 100000 0.01 0.1 1 10 100 1000

Graphene Short CNTs

Q EXP/QHP, Holt et al.

QEXP/QCHP, Holt et al. QEXP/QHP, Qin et al. QEXP/QCHP, Qin et al. QEXP/QHP, Kim et al. QEXP/QCHP, Kim et al. QEXP/QHP, O'Hern et al. QEXP/QCHP, O'Hern et al. QEXP/QHP, Surwade et al. QEXP/QCHP, Surwade et al.

Q NEMD/QHP, Walther et al. Q NEMD/QCHP, Walther et al. Q NEMD/QHP, Suk et al. Q NEMD/QCHP, Suk et al. Q EXP/QHP, Majumder et al. Q EXP/QCHP, Majumder et al.

QEXP/QHP, Secchi et al. QEXP/QCHP, Secchi et al.

Q NEMD/QHP, This work Q NEMD/QCHP, This work

Enhancement Factor h/r

Long CNTs

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Beckman Institute for Advanced Science and Technology

Conclusion

  • We performed continuum and molecular dynamics simulations to obtain a new

power-law scaling relation between the concentration and the conductance of ionic transport.

  • The continuum model was corrected using molecular dynamics inputs to predict

quantities for length scales less than 10 nm.

  • We studied the effect of surface charge density in CNT on the electroosmotic

velocity and selectivity of ions.

  • We corrected the classical Hagen-Poiseuille equation to describe fluid flow rates in

nanoscale systems.

  • The enhancement factor of flow rates approaches unity with the corrected Hagen-

Poiseuille theory.

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Beckman Institute for Advanced Science and Technology

Acknowledgment

Professor Aleksandr Noy

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Beckman Institute for Advanced Science and Technology

Acknowledgment

  • M. Heiranian et al., THE JOURNAL OF

CHEMICAL PHYSICS 147, 104706 (2017)

  • A. Moradzadeh & N.R. Aluru, The

Journal of Physical Chemistry Letters 2019, 10 (6), pp 1242–1250

  • Y. Jing et al., Chemistry of Materials

2018, 30 (138-144)

  • A. Farimani et al., Npj 2d Materials and

Applications 2, 1-9 (2018) M.T. Hwang et al., submitted to publication in April 2019

  • This year we have used till now almost 70 K in two

different allocations.

  • Blue Waters support is highly appreciated.
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Beckman Institute for Advanced Science and Technology

Thank you!