Multiscale Computational Modeling of CNT- Based Composite ...€¦ · Outline • Introduction:...

Multiscale Computational Modeling of CNT-Based Composite Materials

Greg Odegard

Richard and Elizabeth Henes Professor of Computational Mechanics Director, NASA STRI for Ultra-Strong Composites by Computational Design

Michigan Technological University

Workshop on Multiscale Modeling of Carbon Materials August 20-21, 2018

Outline

•  Introduction: Institute for Ultra-Strong Composites by Computational Design (US-COMP)

•  Project example 1: MD Modeling of CNT/Epoxy Composites

•  Project example 2: Multiscale modeling of PEEK

•  Validation vs material exploration dilemma

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Current carbon fiber composites lack strength/toughness (per unit mass) for

manned missions to deep space

acpsales.com

www.nasa.gov

MaterialsDevelopmentExperimental development and characterization of composites •  High material and labor costs •  Difficulty in testing under extreme conditions

(deformation, temperature, pressure) •  Lack of methods to fully probe molecular-scale

behavior •  Trial and error approach (Edisonian method)

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“I have not failed. I've just found 10,000 ways that won't work.”

- Thomas A. Edison

ComputationalModeling

Computational modeling can •  Provide efficient means to explore design space •  Predict material behavior under a wide range of

conditions •  Provide physical insight into observed behavior

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Z1 – 1936 (computerhope.com)

IBM PC – 1981 (vintage-computer.com)

SUPERIOR HPC – 2013

MaterialsGenomeInitiative(MGI)

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www.datanami.com

NASASTRIsolicitationrequirements•  Next generation composite materials with

–  Three-fold increase in tensile properties •  Quasi-isotropic Specific Tensile Strength: 3 GPa/(g/

cm3) •  Quasi-isotropic Specific Tensile Modulus: 150 GPa/(g/

cm3) –  50% increase in fracture toughness •  Interlaminar Fracture Toughness (GIC): 0.3 N/mm

•  Panel level testing •  MGI-based approach •  Workforce training to design, fabricate, and test these

materials •  University/industry/government collaborative

environment 7

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•  Institute for Ultra-Strong Composites by Computational Design

•  First generation of NASA Space Technology Research Institutes (STRIs)

•  Total funding: $15M over 5 years (starting summer 2017) •  Partners

–  11 universities (Michigan Tech is lead, Prof. Odegard PI) –  NASA (multiple centers) –  Air Force Research Laboratory –  2 materials manufacturers (Nanocomp, Solvay) –  3 aerospace companies (Boeing, Lockheed Martin, Orbital

ATK)

Universityparticipants

•  Michigan Tech, PI: Greg Odegard •  Florida State University, PI: Richard Liang •  MIT, PI: John Hart •  University of Utah, PI: Mike Czabaj •  Georgia Tech, PI: Satish Kumar •  Johns Hopkins, PI: Jamie Guest •  University of Minnesota, PI: Traian Dumitrica •  University of Colorado, PI: Hendrik Heinz •  Virginia Commonwealth University, PI: Ibrahim Guven •  Florida A&M University, PI: Tarik Dickens •  Penn State, PI: Adri van Duin

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Experimentaltools•  Mul$scalecharacteriza$on•  Panel-levelmechanicaltests

Computa1onaltools•  Mul$scalesimula$on

•  Topologyop$miza$on

Digitaldatafordesign•  Structure-propertyrela$onships• Mechanicalpropertydatabase

MGI

Project1–MDModelingofCNT/EpoxyComposites•  Motivation

–  Aerospace industry wants to know how to incorporate carbon nanotubes (CNTs) into structural composites

–  Different types of epoxy resin are available for CNT/epoxy composites

•  Objectives –  Predict properties for different epoxies reinforced with CNTs

and carbon fiber (CF) –  Determine with epoxy functionality provides the most efficient

load transfer •  Sponsor: Air Force Office of Scientific Research •  Collaborators: Matt Radue, Greg Odegard

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Epoxytypes

Epoxy Resin Hardener

Di - Functional

BFDGE EPON 862

DETDA

Tri - Functional

TGAP Araldite MY 0510

Tetra - Functional

TGDDM Araldite MY 721

MDmodelingdetails•  5 independent samples for

each epoxy type – total of 15 models

•  400 CNT atoms and about 5200 epoxy atoms per model

•  ReaxFF used •  Unfunctionalized, zigzag (10,0)

CNT •  CNT diameter ~ 8 Å

EPOXY CNT MASS FRACTION

CROSSLINK DENSITY

DENSITY g/cm3

Di- 0.117 0.74 ± 0.04 1.257 ± 0.006 Tri- 0.122 0.79 ± 0.02 1.261 ± 0.006

Tetra- 0.123 0.74 ± 0.02 1.232 ± 0.008

InteractionEnergy

•  Interaction energy between the CNT and matrix was calculated as

•  Di and Tri models yield similar interaction energies •  Majority of Tetra samples demonstrate relatively weak

interaction after crosslinking

Einteraction = ECNT/epoxy – ECNT - Eepoxy

Micromechanicsmodeling

•  MAC/GMC software used (NASA Glenn Research Center) •  MD mechanical properties used as input •  Random CNT/epoxy properties predicted •  Carbon Fiber (CF)/CNT/epoxy properties predicted

ExperimentComparison•  Predictions obtained using the Di epoxy (Epon 862) were

compared with experimental results •  Normalized Modulus = Composite Modulus ÷ Matrix

Modulus… somewhat evades the strain rate effect

Sun et al, Carbon (2008) 46(2): pp. 320 Wang et al, Nanotechnology (2006) 17(6): pp. 1551 Wang et al, Polymer composites (2009) 30(8): pp. 1050 Gojny et al, Composites Science and Technology (2005) 65(15): pp. 2300

Bulk-levelComparison

Designmap

Project2–MultiscalemodelingofPEEK•  Motivation

–  PEEK polymers are used for internal structures in aircraft –  PEEK is a multiscaled material –  Improvement of PEEK composites requires a multiscale

modeling strategy •  Objectives: Predict bulk mechanical properties of PEEK

using molecular-and micro-structure •  Sponsor: NSF I/UCRC for Novel High Temperature/Voltage

Materials and Structures •  Collaborators: Will Pisani, Evan Pineda (NASA GRC), Brett

Bednarcyk (NASA GRC), Greg Odegard

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PEEKmicrostructure

Wang et al, RSC Advances, 2016

Molecularmodeling

Amorphous phase Crystal phase

•  LAMMPS MD software •  ReaxFF force field used •  Multiple samples simulated for statistical evaluation

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Results

Predicted Experiment (vendor data)

Young’s modulus (GPa) 3.98 ± 1.12 4.00 Poisson’s ratio 0.40 ± 0.10 0.38

•  Predicted results agree well with experiment •  Apparent lack of strain rate effect •  Relatively large amounts of crystalline

phase •  May be obscured by variance

Validationvsmaterialexploration

•  Most journals (e.g. Composites Science and Technology) require experimental validation of modeling based papers

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How can we publish our material exploration research if the designed

materials cannot yet be fabricated for validation?

•  One purpose of computational modeling is to efficiently explore new material designs with desired properties that have not been made (or cannot be made) in the laboratory

Acknowledgements

U.S. Air Force Office of Scientific Research Low Density Materials Program (Grant FA9550-13-1-0030)

SUPERIOR computing cluster Michigan Tech

National Aeronautics and Space Administration Aeronautical Sciences Program (Grant NNX11AI72A)

National Science Foundation I/UCRC program (Grant IIP-1362040)

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Thank you!