multiscale computational modeling of cnt- based composite ...€¦ · outline • introduction:...
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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
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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
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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
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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
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MaterialsGenomeInitiative(MGI)
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www.datanami.com
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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: $15M over 5 years (starting summer 2017) • Partners
– 11 universities (Michigan Tech is lead, Prof. Odegard PI) – NASA (multiple centers) – Air Force Research Laboratory – 2 materials manufacturers (Nanocomp, Solvay) – 3 aerospace companies (Boeing, Lockheed Martin, Orbital
ATK)
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Universityparticipants
• Michigan Tech, PI: Greg Odegard • Florida State University, PI: Richard Liang • MIT, PI: John Hart • University of Utah, PI: Mike Czabaj • Georgia Tech, PI: Satish Kumar • Johns Hopkins, PI: Jamie Guest • University of Minnesota, PI: Traian Dumitrica • University of Colorado, PI: Hendrik Heinz • Virginia Commonwealth University, PI: Ibrahim Guven • Florida A&M University, PI: Tarik Dickens • Penn State, PI: Adri van Duin
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Experimentaltools• Mul$scalecharacteriza$on• Panel-levelmechanicaltests
Computa1onaltools• Mul$scalesimula$on
• Topologyop$miza$on
Digitaldatafordesign• Structure-propertyrela$onships• Mechanicalpropertydatabase
MGI
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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
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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
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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
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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
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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
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Bulk-levelComparison
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Designmap
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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
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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
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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
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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!