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
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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!