Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-14T06:12:27.729Z Has data issue: false hasContentIssue false
  • English
  • Français

μCT-Based Analysis of the Solid Phase in Foams: Cell Wall Corrugation and other Microscopic Features

Published online by Cambridge University Press:  20 August 2015

Samuel Pardo-Alonso ,
Eusebio Solórzano Open the ORCID record for Eusebio Solórzano [Opens in a new window] ,
Jerome Vicente ,
Loes Brabant ,
Manuel L. Dierick ,
Ingo Manke ,
Andr Hilger ,
Ester Laguna  and
Miguel Angel Rodriguez-Perez
Samuel Pardo-Alonso*
Affiliation:
CellMat Laboratory, Condensed Matter Physics Department, University of Valladolid, Paseo de Belén 7, 47011 Valladolid, Spain
Eusebio Solórzano
Affiliation:
CellMat Laboratory, Condensed Matter Physics Department, University of Valladolid, Paseo de Belén 7, 47011 Valladolid, Spain
Jerome Vicente
Affiliation:
Laboratoire IUSTI, CNRS UMR 7343, Aix Marseille Université, Marseille, France
Loes Brabant
Affiliation:
UGCT-Department of Physics and Astronomy, Faculty of Sciences, Proeftuinstraat, 86 9000 Ghent, Belgium
Manuel L. Dierick
Affiliation:
UGCT-Department of Physics and Astronomy, Faculty of Sciences, Proeftuinstraat, 86 9000 Ghent, Belgium
Ingo Manke
Affiliation:
Institute of Applied Materials, Helmholtz Centre Berlin for Materials and Energy (HZB) Hahn-Meitner-Platz 1, 14109 Berlin, Germany
Andr Hilger
Affiliation:
Institute of Applied Materials, Helmholtz Centre Berlin for Materials and Energy (HZB) Hahn-Meitner-Platz 1, 14109 Berlin, Germany
Ester Laguna
Affiliation:
CellMat Laboratory, Condensed Matter Physics Department, University of Valladolid, Paseo de Belén 7, 47011 Valladolid, Spain
Miguel Angel Rodriguez-Perez
Affiliation:
CellMat Laboratory, Condensed Matter Physics Department, University of Valladolid, Paseo de Belén 7, 47011 Valladolid, Spain
*
*Corresponding author.esolo@fmc.uva.es
Get access

Abstract

This work presents a series of three-dimensional computational methods with the objective of analyzing and quantifying some important structural characteristics in a collection of low-density polyolefin-based foams. First, the solid phase tortuosity, local thickness, and surface curvature, have been determined over the solid phase of the foam. These parameters were used to quantify the presence of wrinkles located at the cell walls of the foams under study. In addition, a novel segmentation technique has been applied to the continuous solid phase. This novel method allows performing a separate analysis of the constituting elements of this phase, that is, cell struts and cell walls. The methodology is based on a solid classification algorithm and evaluates the local topological dissimilarities existing between these elements. Thanks to this method it was possible to perform a separate analysis of curvature, local thickness, and corrugation ratio in the solid constituents that reveals additional differences that were not detected in the first analysis of the continuous structure. The methods developed in this work are applicable to other types of porous materials in fields such as geoscience or biomedicine.

Keywords

tomography3D analysiscorrugationtortuositycellular structure
Type
Materials Applications
Information
Microscopy and Microanalysis , Volume 21 , Issue 5 , October 2015 , pp. 1361 - 1371
Copyright
© Microscopy Society of America 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alkemper, J. & Vorhees, P.W. (2001). Three-dimensional characterization of dendritic microstructures. Acta Mater 49, 897–902.CrossRefGoogle Scholar
Almanza, O., Masso-Moreu, Y., Mills, N.J. & Rodriguez-Perez, M.A. (2004). Thermal expansion coefficient and bulk modulus of polyethylene closed-cell foams. J Polym Sci B Polym Phys 42, 3741–3749.CrossRefGoogle Scholar
Almanza, O., Rodriguez-Perez, M.A. & De Saja, J.A. (1999). The thermal conductivity of polyethylene foams manufactured by a nitrogen solution process. Cell Polym 18(6), 385–401.Google Scholar
Almanza, O., Rodriguez-Perez, M.A. & De Saja, J.A. (2000). Prediction of the radiation term in the thermal conductivity of crosslined closed cell polyolefin foams. J Polym Sci B Polym Phys 38, 993–1004.3.0.CO;2-J>CrossRefGoogle Scholar
Almanza, O., Rodiguez-Perez, M.A. & De Saja, J.A. (2001). The microstructure of polyethylene foams produced by a nitrogen solution process. Polym 42, 7117–7126.CrossRefGoogle Scholar
Álvarez-Láinez, M., Rodriguez-Perez, M.A. & De Saja, J.A. (2014). Acoustic absorption coefficient of open-cell polyolefin-based foams. Mater Lett 121, 26–30.CrossRefGoogle Scholar
Alvarez-Lainez, M.A., Rodriguez-Perez, M.A. & De Saja, J.A. (2008). Thermal conductivity of open cell polyolefin foams. J Polym Sci B Polym Phys 46(2), 212–221.CrossRefGoogle Scholar
Andrews, E., Sanders, W. & Gibson, L.J. (1999). Compressive and tensile behaviour of aluminum foams. Mater Sci Eng 270(2), 113–124.CrossRefGoogle Scholar
Brabant, L., Vlassenbroeck, J., De Witte, Y., Cnudde, V., Boone, M., Dewanckele, J. & Van Hoorebeke, L. (2011). Three-dimensional analysis of high-resolution X-ray computed tomography data with Morpho+. Microsc Microanal 17(2), 252–263.CrossRefGoogle ScholarPubMed
Brun, E., Vicente, J., Topin, F. & Occelli, R. (2008). Characterization of the full thermal conductivity tensor of anisotropic metal foams – Influence of the fluid phase. In Metfoam 2007: Porous Metals and Metallic Foams. Proceedings of the Fifth International Conference on Porous Metals and Metallic Foams, Lefebvre, L.P., Banhart, J. & Dunand, D.C., pp. 513–516 Lancaster, DEStech Publications.Google Scholar
Brun, E., Vicente, J. (2010). Volumetric segmentation of trabecular bone into rods and plates: a new method based on local shape classification. In Proceedings of SPIE Medical Imaging 2010: Image processing, Dawant, B.M. & Haynor, D.R. (Eds.), doi: 10.1117/12.843804.CrossRefGoogle Scholar
Bullitt, E., Gerig, G., Pize, S., Lin, W. & Aylward, S.R. (2003). Measuring tortuosity of the intracerebral vasculature from MRA images. IEEE Trans Med Imaging 22(9), 1163–1171.CrossRefGoogle ScholarPubMed
Eaves, D. (2004). Handbook of Polymer Foams. UK: Rapra Technology.Google Scholar
Gibson, L.J. & Ashby, M.F. (1997). Cellular Solids – Structure and Properties. UK: Cambridge University Press.CrossRefGoogle Scholar
Glicksman, L.R. (1994). Low Density Cellular Plastics. UK: Chapman & Hall.Google Scholar
Gommes, C.J., Bons, A.J., Blacher, S., Dunsmuir, J.H. & Tsou, A.H. (2009). Practical methods for measuring the tortuosity of porous materials from binary or gray-tone tomographic reconstructions. AIChE J 55(8), 2000–2012.CrossRefGoogle Scholar
Grenestedt, J.L. (1998). Influence of wavy imperfections in cell walls on elastic stiffness of cellular solids. J Mech Phys Solids 46(1), 29–50.CrossRefGoogle Scholar
Hildebrand, T. & Rüesegger, P. (1997). A new method for the model-independent assessment of thickness in three-dimensional images. J Micros 185(1), 67–75.CrossRefGoogle Scholar
Jinnai, H., Koga, T., Nishikawa, Y., Hashimoto, T. & Hyde, S.T. (1997). Curvature determination of spinodal interface in a condensed matter system. Phys Rev Lett 78, 2248–2251.CrossRefGoogle Scholar
Kammer, D. & Vorhees, P.W. (2006). The morphological evolution of dendritic microstructures during coarsening. Acta Mater 54, 1549–1558.CrossRefGoogle Scholar
Kuhn, J.J., Ebert, H.P., Arduini-Schuster, M.C., Buttner, D. & Fricke, J. (1992). Thermal transport in polystyrene and polyurethane foam insulations. Int J Heat Mass Trans 35(7), 1795–1801.CrossRefGoogle Scholar
Lorensen, W.E. & Cline, H.E. (1987). Marching Cubes: A high resolution 3-D surface construction algorithm. ACM Siggraph Comput Graph 21, 163–169.CrossRefGoogle Scholar
Lu, T.J., Stone, H.A. & Ashby, M.F. (1998). Heat transfer in open-cell metal foams. Acta Mater 46(10), 3619–3635.CrossRefGoogle Scholar
Ma, Y., Pyrz, R., Rodriguez-Perez, M.A., Escudero, J., Rauhe, J.C. & Su, X. (2011). X-ray microtomographic study of nanoclay-polypropylene foams. Cell Polym 30(3), 95–110.CrossRefGoogle Scholar
Mader, K., Mokso, R., Raufaste, C., Dollet, B., Santucci, S., Lambert, J. & Stampanoni, M. (2012). Quantitative 3D characterization of cellular materials: Segmentation and morphology of foam. Colloids Surf A 12(415), 230–238.CrossRefGoogle Scholar
Martinez-Diez, J.A., Rodriguez-Perez, M.A., De Saja, J.A., Arcos Y Rabago, L.O. & Almanza, O. (2001). The thermal conductivity of a polyethylene foam block produced by a compression molding process. J Cell Plast 37, 21–42.CrossRefGoogle Scholar
Meagher, A.J., Mukherjee, M., Weaire, D., Hutzler, S., Banhart, J. & Garcia Moreno, F. (2011). Analysis of the internal structure of monodisperse liquid foams by X-ray tomography. Soft Matter 7, 9881–9885.CrossRefGoogle Scholar
Pardo-Alonso, S., Solórzano, E., Brabant, L., Vanderniepen, P., Dierick, M., Van Hoorebeke, L. & Rodriguez-Perez, M.A. (2013). 3D analysis of the progressive modification of the cellular architecture in polyurethane nanocomposite foams via X-ray microtomography. Eur Polym J 49, 999–1006.CrossRefGoogle Scholar
Pinto, J., Solórzano, E., Rodíguez-Pérez, M.A. & De Saja, J.A. (2013). Characterization of the cellular structure based on user-interactive image analysis procedures. J Cell Plast 49(6), 554– 574.CrossRefGoogle Scholar
Rasband, W.S. (2012). ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA. Available at http://imagej.nih.gov/ij/.Google Scholar
Rodriguez-Perez, M.A. (2005). Crosslinked polyolefin foams: Production, structure, properties and applications. Adv Polym Sci 184, 97–126.CrossRefGoogle Scholar
Rodriguez-Perez, M.A., Almanza, O., Ruiz-Herrero, J.L. & de Saja, J.A. (2008). The effect of processing on the structure and properties of crosslinked closed cell polyethylene foams. Cell Polym 27, 179–200.CrossRefGoogle Scholar
Russ, J.C. (2007). Image Processing Handbook. USA: CRC Editors.Google Scholar
Schindelin, J., Arganda-Carreras, I., Frise, E., Kanyg, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., Tivenez, J.Y., White, D.J., Hartestein, V., Elceiri, K., Tomacank, P. & Cardona, A. (2012). Fiji: An open-source platform for biological-image analysis. Nat Methods 9(7), 676–682.CrossRefGoogle ScholarPubMed
Simone, A.E. & Gibson, L.J. (1998). Effects of solid distribution on the stiffness and strength of metallic foams. Acta Mater 46(6), 2139–2150.CrossRefGoogle Scholar
Solórzano, E., Pardo-Alonso, S., Brabant, L., Vicente, J., Van Hoorebeke, L. & Rodriguez-Perez, M.A. (2013). Computational approaches for tortuosity determination in 3D structures. In Tomography of Materials and Structures: Book of Abstracts: Talks, Presented at the 1st International Conference on Tomography of Materials and Structures (ICTMS 2013), Cnudde, V. (Ed.), pp.71–74, Ghent, University of Ghent.Google Scholar
Toyofumi, S. & Jun-Ichiro, T. (1994). New algorithms for euclidean distance transformation of an n-dimensional digitized picture with applications pattern. Recognition 27(11), 1551–1565.Google Scholar
Vincent, L. & Soille, P. (1991). Watersheds in digital spaces – An efficient algorithm based on immersion simulation. IEEE Trans Pattern Anal Mach Intell 13(6), 583–598.CrossRefGoogle Scholar
Vlassenbroeck, J., Dierick, M., Masschaele, B., Cnudde, V., Van Hoorebeke, L. & Jacobs, P. (2007). Software tools for quantification of X-ray microtomography. Nucl Instrum Methods Phys Res Sect 580(1), 442–445.CrossRefGoogle Scholar
Weaire, D. & Hutzler, S. (1999). The Physics of Foams. UK: Oxford University Press.Google Scholar