Overview of multiscale modeling approach
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Overview of Multiscale Modeling Approach. Dion Vlachos Univ. of Delaware. Mathematical and computational methods developed Bottom-up modeling Process design Coarse-graining Top-down modeling Catalyst design. Bottom-up and Top-down Modeling: Process Design and Catalyst Screening.

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Overview of Multiscale Modeling Approach

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Overview of multiscale modeling approach

Overview of Multiscale Modeling Approach

Dion Vlachos

Univ. of Delaware


Bottom up and top down modeling process design and catalyst screening

Mathematical and computational methods developed

Bottom-up modeling

Process design

Coarse-graining

Top-down modeling

Catalyst design

Bottom-up and Top-down Modeling:Process Design and Catalyst Screening

Reviews: Chem. Eng. J. 90, 3 (2002); Chem. Eng. Sci. 59, 5559 (2004); Adv. Chem. Eng. 30, 1 (2005)


The 30 000 miles airview

The 30,000 Miles Airview

Much less work has been done at the systems’ level

Significant progress made on method development and testing

Field is maturing

Focus has been on prototype problems

Complex systems have by-and-large not been studied

Perspecive: Vlachos, AIChE J. 58(5), 1314 (2012)


Hierarchy enables rapid s creening of chemistry fuels and catalysts

Hierarchy Enables Rapid Screening of Chemistry, Fuels, and Catalysts

Length

Accuracy, cost

Reactor scale:

Performance

Ideal:

PFR, CSTR, etc.

Computational Fluid Dynamics (CFD)

Pseudo-homogeneous:

Transport correlations

Catalyst scale:

Reaction rate

Continuum:

MF-ODEs

Mesoscopic:

PDEs

Discrete:

CG-KMC

Discrete:

KMC

Reaction network builder

Uncertainty quantification

Electronic scale:

Parameter estimation

Quantum-based correlations:

BEPs, GA, LSRs

Quantum:

ab initio, DFT, TST, CPMD, QM/MM MD

Hierarchy adds a new dimension to multiscaling: at each scale, more than one model can be run

Review: Salciccioli et al., Chem. Eng. Sci. 66, 4319 (2011)


Toward high throughput computing metal and metal like catalysis

Toward High-throughput Computing:Metal and Metal-like Catalysis

Thermochemistry via GA & LSRs

Reaction barriers and pre-exps via BEPs

Perform MKM

DFT-based, semi-empirical, or hierarchical (screen with semi-empirical and refine via DFT)

Error analysis; Assessment of model predictions

  • Linear Scaling Relations (LSRs)

Group Additivity (GA)

  • Brønsted Evans Polanyi (BEP)

Microkinetic Model

(MKM)

Salciccioli et al., J. Phys. Chem. C , 114, 20155 (2010); J. Phys. Chem. C, 116, 1873 (2012)

Sutton and Vlachos, ACS Catal.2, 1624 (2012); J. Catal. 297, 202 (2013)


The kinetic monte carlo approach

The Kinetic Monte Carlo Approach

Metal surface

products

transition

state

Potential Energy Surface

reactants

CO(gas) + OH COOH

Stamatakis and Vlachos, J. Chem. Phys. 134, 214115 (2011);

http://www.dion.che.udel.edu/downloads.php

Instead of simulating dynamics, KMC focuses on rare events

Simulates reactions much faster than Molecular Dynamics

Incorporates spatial information contrary to micro-kinetic models


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