The DOI matches its Crossref record.
Random Heterogeneous Materials: Microstructure and Macroscopic Properties
Abstract
7R3. Random Heterogeneous Materials: Microstructure and Macroscopic Properties. - S Torquato (Dept of Chem, Princeton Mat Inst, Princeton Univ, Princeton NJ 08544). Springer-Verlag, New York. 2002. 701 pp. ISBN 0-387-95167-9. $69.95.Reviewed by HW Haslach Jr (Dept of Mech Eng, Univ of Maryland, College Park MD 20742-3035).Random heterogeneous materials are those composed of randomly distributed phases or different material domains such as composites or materials with voids. The various domains forming the microstructure have macroscopic properties because they are larger than molecules. A major problem is to develop a rigorous method of characterizing the microstructure. Probability functions are used to describe the various microstructures, whether heterogeneous, homogeneous, isotropic, etc. A canonical n-point correlation function provides a unified means to describe arbitrary microstructures. The presentation is restricted to microstructures which are independent of time. Several idealized models of the microstructure are presented. In a hard sphere model, the ill-defined idea of randomly closed packed spheres is replaced by the well-defined idea of a maximally random jammed configuration. The degree of penetrability and the distribution of radii of the spheres are adjusted to represent different types of microstructure. Anisotropy is modeled with ellipsoidal or cylindrical inclusions. Some hierarchical laminates have optimal transport properties. Foams or some biological materials are better modeled by the space-filling cell structures described. Percolation is modeled using the idea of clusters, a connected group of the random elements. The Monte Carlo method is used to produce both equilibrium and non-equilibrium realizations of random media. The idea is to generate a random microstructure and then study its properties. An appendix lists a FORTRAN program to create an equilibrium configuration of uniform hard disks. The second part of the book studies the relation of the bulk effective properties to the microstructure of a random heterogeneous material. The probability characterizations of the microstructure given in the first part are used to compute the effective bulk properties in the four different areas of conduction, elasticity, trapping, and flow in porous media. The study is generally restricted to ergodic two-phase random media. In each case, a local linear constitutive model is assumed, as is local statistical homogeneity. The focus is on steady-state behavior. The resulting elasticity theory permits definition of linear viscoelasticity through the correspondence principle. Processes are represented by averaged, or homogenized, partial differential equations. The averaging requires two length scales, one for the microstructure and one for the bulk material. Generally, the response is composed of a slow component due to the global scale including the applied loads and a fast component due to the microstructure. The averaging is carried out subject to conservation relations. Variational principles are used to bound the values of the properties, which in general cannot be computed exactly. Exceptions are some periodic microstructures, the Hashin-Shtrikman isotropic dispersion of spheres, or the hierarchical laminates. Single inclusion problems are solved and used to estimate the dependence of effective properties on volume fraction and inclusion shape. Trial fields to determine bounds on the properties, using the variational principles, are developed for the four classes of example effective properties. The results of the first part of the book are used to compute the bounds in two-phase random heterogeneous materials. The book ends by examining the problem of determining one effective property from information about others. This book is part of an Applied Mathematics series, and it primarily concerns the mathematical analysis of random structures. This work can serve as a foundation for those who wish to design random heterogeneous structures with specified bulk properties. A major contribution of the book is to clearly and rigorously explain the statistical characterization of the microstructure of these materials as a foundation for an analysis of effective properties. This theory, at least to the extent developed in this book, only produces linear models for the bulk properties of solids; nonlinear behavior is not covered. The intended interdisciplinary audience is graduate students and researchers in fields such as applied mathematics, physics, chemistry, materials science, engineering, geology, and biology. The suggested prerequisites are the basics of probability, statistical mechanics, advanced calculus, and continuum mechanics. The author’s stated attempt to avoid technical jargon is largely successful. An extensive reference list is provided. Random Heterogeneous Materials: Microstructure and Macroscopic Properties should become a standard reference for those beginning a study of rand
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Diffusion in Brain Extracellular Space
Syková, E., & Nicholson, C. (2008) · Physiological Reviews · doi:10.1152/physrev.00027.2007 · Cited by 1,481
A density-independent rigidity transition in biological tissues
Bi, D., Lopez, J. H., Schwarz, J. M., & Manning, M. L. (2015) · Nature Physics · doi:10.1038/nphys3471 · Cited by 801
Zhu, Y., & Zabaras, N. (2018) · Journal of Computational Physics · doi:10.1016/j.jcp.2018.04.018 · Cited by 704
Motility-Driven Glass and Jamming Transitions in Biological Tissues
Bi, D., Yang, X., Marchetti, M. C., & Manning, M. L. (2016) · Physical Review X · doi:10.1103/physrevx.6.021011 · Cited by 677
Spectrin-Level Modeling of the Cytoskeleton and Optical Tweezers Stretching of the Erythrocyte
Li, J., Dao, M., Lim, C. T., & Suresh, S. (2005) · Biophysical Journal · doi:10.1529/biophysj.104.047332 · Cited by 426
Metadata
- Authors
- Haslach, H.
- Venue
- Applied Mechanics Reviews
- Publisher
- ASME International
- Published
- 2002-07-01
- Volume
- 55
- Issue
- 4
- Pages
- B62-B63
- ISSN
- 0003-6900 (ISSN-L)
- 2379-0407
- OpenAlex
- W4230327365
- Cited by
- 1,873
- References
- 0
- FWCI
- 45.24
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Random Heterogeneous Materials: Microstructure and Macroscopic Properties. https://app.cochat.ai/papers/10.1115/1.1483342
- The paper
- Haslach, H. (2002). Random Heterogeneous Materials: Microstructure and Macroscopic Properties. Applied Mechanics Reviews. https://doi.org/10.1115/1.1483342
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.