3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function

A. Sheidaei, M. Baniassadi, M. Banu, P. Askeland, M. Pahlavanpour, Nick Kuuttila, F. Pourboghrat, L. T. Drzal, H. Garmestani

    Research output: Contribution to journalArticle

    • 23 Citations

    Abstract

    3-D reconstruction of Halloysite nanotube (HNT) polypropylene composite has been performed using two different methods. In the first method, several slices of the composite material were obtained using focused ion beam (FIB), and scanning electron microscopy (SEM). A representative volume element (RVE) of the real material's micro/nanostructures was then constructed by stacking these morphological images using VCAT® software. In the second method, SEM images of the nano-composite were used to extract statistical two-point correlation function (TPCF), for reconstruction of an RVE of the nano-composite.The resulting RVEs obtained from both methods were meshed for finite element (FE) simulation of deformation under tension and shear loadings. The FE results were then used to compute the stiffness tensor of the nano-composite.In the statistical approach, the TPCF was obtained from a none-Eigen microstructure which can partially reflect statistical information of the microstructure. The mechanical constants obtained from statistical RVEs using FEM approach shows a 5.7% error compared with those obtained from real RVE, which could be attributed to the approximation using TPCF [1].It is concluded that the statistical method using TPCF alone can produce an approximate microstructure that should be modified using other statistical descriptor such as two-point cluster function and lineal path function to have better reconstruction of heterogeneous nano-composites [2].

    Original languageEnglish (US)
    Pages (from-to)47-54
    Number of pages8
    JournalComposites Science and Technology
    Volume80
    DOIs
    StatePublished - May 7 2013

    Profile

    Composite materials
    Microstructure
    Scanning electron microscopy
    Malignant Hypertension
    Focused ion beams
    Carbamyl Phosphate
    Abdominal Injuries
    Traffic Accidents
    Cholera
    Tensors
    Nanostructures
    Statistical methods
    Stiffness
    Nanotubes
    Polypropylenes
    Finite element method
    Polymers

    Keywords

    • A. Nanocomposites
    • A. Polymer-matrix composites (PMCs)
    • B. Mechanical properties
    • C. Modeling
    • D. Scanning electron microscopy (SEM)

    ASJC Scopus subject areas

    • Engineering(all)
    • Ceramics and Composites

    Cite this

    Sheidaei, A., Baniassadi, M., Banu, M., Askeland, P., Pahlavanpour, M., Kuuttila, N., ... Garmestani, H. (2013). 3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function. Composites Science and Technology, 80, 47-54. DOI: 10.1016/j.compscitech.2013.03.001

    3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function. / Sheidaei, A.; Baniassadi, M.; Banu, M.; Askeland, P.; Pahlavanpour, M.; Kuuttila, Nick; Pourboghrat, F.; Drzal, L. T.; Garmestani, H.

    In: Composites Science and Technology, Vol. 80, 07.05.2013, p. 47-54.

    Research output: Contribution to journalArticle

    Sheidaei A, Baniassadi M, Banu M, Askeland P, Pahlavanpour M, Kuuttila N et al. 3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function. Composites Science and Technology. 2013 May 7;80:47-54. Available from, DOI: 10.1016/j.compscitech.2013.03.001

    Sheidaei, A.; Baniassadi, M.; Banu, M.; Askeland, P.; Pahlavanpour, M.; Kuuttila, Nick; Pourboghrat, F.; Drzal, L. T.; Garmestani, H. / 3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function.

    In: Composites Science and Technology, Vol. 80, 07.05.2013, p. 47-54.

    Research output: Contribution to journalArticle

    @article{fefee29b54a04622b4b942e20b7dd3b4,
    title = "3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function",
    abstract = "3-D reconstruction of Halloysite nanotube (HNT) polypropylene composite has been performed using two different methods. In the first method, several slices of the composite material were obtained using focused ion beam (FIB), and scanning electron microscopy (SEM). A representative volume element (RVE) of the real material's micro/nanostructures was then constructed by stacking these morphological images using VCAT® software. In the second method, SEM images of the nano-composite were used to extract statistical two-point correlation function (TPCF), for reconstruction of an RVE of the nano-composite.The resulting RVEs obtained from both methods were meshed for finite element (FE) simulation of deformation under tension and shear loadings. The FE results were then used to compute the stiffness tensor of the nano-composite.In the statistical approach, the TPCF was obtained from a none-Eigen microstructure which can partially reflect statistical information of the microstructure. The mechanical constants obtained from statistical RVEs using FEM approach shows a 5.7% error compared with those obtained from real RVE, which could be attributed to the approximation using TPCF [1].It is concluded that the statistical method using TPCF alone can produce an approximate microstructure that should be modified using other statistical descriptor such as two-point cluster function and lineal path function to have better reconstruction of heterogeneous nano-composites [2].",
    keywords = "A. Nanocomposites, A. Polymer-matrix composites (PMCs), B. Mechanical properties, C. Modeling, D. Scanning electron microscopy (SEM)",
    author = "A. Sheidaei and M. Baniassadi and M. Banu and P. Askeland and M. Pahlavanpour and Nick Kuuttila and F. Pourboghrat and Drzal, {L. T.} and H. Garmestani",
    year = "2013",
    month = "5",
    doi = "10.1016/j.compscitech.2013.03.001",
    volume = "80",
    pages = "47--54",
    journal = "Composites Science and Technology",
    issn = "0266-3538",
    publisher = "Elsevier BV",

    }

    TY - JOUR

    T1 - 3-D microstructure reconstruction of polymer nano-composite using FIB-SEM and statistical correlation function

    AU - Sheidaei,A.

    AU - Baniassadi,M.

    AU - Banu,M.

    AU - Askeland,P.

    AU - Pahlavanpour,M.

    AU - Kuuttila,Nick

    AU - Pourboghrat,F.

    AU - Drzal,L. T.

    AU - Garmestani,H.

    PY - 2013/5/7

    Y1 - 2013/5/7

    N2 - 3-D reconstruction of Halloysite nanotube (HNT) polypropylene composite has been performed using two different methods. In the first method, several slices of the composite material were obtained using focused ion beam (FIB), and scanning electron microscopy (SEM). A representative volume element (RVE) of the real material's micro/nanostructures was then constructed by stacking these morphological images using VCAT® software. In the second method, SEM images of the nano-composite were used to extract statistical two-point correlation function (TPCF), for reconstruction of an RVE of the nano-composite.The resulting RVEs obtained from both methods were meshed for finite element (FE) simulation of deformation under tension and shear loadings. The FE results were then used to compute the stiffness tensor of the nano-composite.In the statistical approach, the TPCF was obtained from a none-Eigen microstructure which can partially reflect statistical information of the microstructure. The mechanical constants obtained from statistical RVEs using FEM approach shows a 5.7% error compared with those obtained from real RVE, which could be attributed to the approximation using TPCF [1].It is concluded that the statistical method using TPCF alone can produce an approximate microstructure that should be modified using other statistical descriptor such as two-point cluster function and lineal path function to have better reconstruction of heterogeneous nano-composites [2].

    AB - 3-D reconstruction of Halloysite nanotube (HNT) polypropylene composite has been performed using two different methods. In the first method, several slices of the composite material were obtained using focused ion beam (FIB), and scanning electron microscopy (SEM). A representative volume element (RVE) of the real material's micro/nanostructures was then constructed by stacking these morphological images using VCAT® software. In the second method, SEM images of the nano-composite were used to extract statistical two-point correlation function (TPCF), for reconstruction of an RVE of the nano-composite.The resulting RVEs obtained from both methods were meshed for finite element (FE) simulation of deformation under tension and shear loadings. The FE results were then used to compute the stiffness tensor of the nano-composite.In the statistical approach, the TPCF was obtained from a none-Eigen microstructure which can partially reflect statistical information of the microstructure. The mechanical constants obtained from statistical RVEs using FEM approach shows a 5.7% error compared with those obtained from real RVE, which could be attributed to the approximation using TPCF [1].It is concluded that the statistical method using TPCF alone can produce an approximate microstructure that should be modified using other statistical descriptor such as two-point cluster function and lineal path function to have better reconstruction of heterogeneous nano-composites [2].

    KW - A. Nanocomposites

    KW - A. Polymer-matrix composites (PMCs)

    KW - B. Mechanical properties

    KW - C. Modeling

    KW - D. Scanning electron microscopy (SEM)

    UR - http://www.scopus.com/inward/record.url?scp=84875827317&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84875827317&partnerID=8YFLogxK

    U2 - 10.1016/j.compscitech.2013.03.001

    DO - 10.1016/j.compscitech.2013.03.001

    M3 - Article

    VL - 80

    SP - 47

    EP - 54

    JO - Composites Science and Technology

    T2 - Composites Science and Technology

    JF - Composites Science and Technology

    SN - 0266-3538

    ER -