Professor Torquato

Salvatore Torquato

Professor of Chemistry, and Princeton Institute for the Science and Technology of Materials

B.S., Mechanical Engineering, Syracuse
       University, 1975
M.S., Mechanical Engineering, State University
       of New York at Stony Brook, 1975
Ph.D., State University of New York at
       Stony Brook, 1981

Room: 123B, Frick Laboratory
Phone: (609) 258-3341
E-mail: torquato@electron.princeton.edu

Honors and Awards

Concurrent University Appointments

Publications

Research Interests

Heterogeneous materials. Research on heterogeneous materials (e.g., composites, colloids, polymer blends, bone, wood, and blood) dates back to the work of Maxwell and Einstein, and has important ramifications in the physical and biological sciences. We have developed a unified methodology to characterize quantitatively the microstructure of disordered heterogeneous materials using statistical-mechanical theoretical and computer-simulation techniques. Combining this microstructural information with structure/property relations, we have predicted accurately a variety of transport, electromagnetic and mechanical properties. This unified approach has enabled us to relate seemingly disparate physical properties to one another, e.g., diffusion parameters have been linked to the fluid permeability or to the elastic moduli.

Optimal design of composites. The optimization methodology that we have developed provides a means of optimally designing multifunctional composite microstructures, which subsequently can be fabricated. For example, we have discovered composite structures that have novel properties, such as negative thermal expansion and negative Poisson's ratios. We have shown how the competition between two different performance demands (simultaneous heat and electrical conduction) results in unexpected microstructures, namely, minimal surfaces. This work suggests that it may be fruitful to explore the origins of biological structures from a rigorous optimization viewpoint.

Liquids, amorphous solids, and colloids. Our basic interest here is to understand the fundamental microscopic nature of the structure and thermodynamic properties of liquids, glasses, and colloids. Contrary to conventional wisdom, we showed via a molecular dynamics study of a model system that there is no evidence for a thermodynamic glass transition. Another area of research involves the search for quantitative measures of "randomness" in condensed-phase systems via scalar "order metrics." We have applied order metrics to understand the structure of simple liquids, water, and random hard-sphere packings. An interesting inverse problem considers backing out complete configurations of many-particle systems and/or interaction potentials from low-order structural information.

Tomography and image science. We have been at the forefront in the utilization of X-ray tomographic techniques to obtain three-dimensional digitized images of composite and porous media. By storing the digitized images on a computer workstation, we have analyzed the microstructure and subsequently estimated the macroscopic properties of interest using the aforementioned unified methodology. This work has enabled us to extract important topological information that otherwise cannot be obtained from standard techniques that yield two-dimensional images of cross sections of the material.

Modeling cancer growth. We have developed a novel cellular automata model, which simulates the three-dimensional proliferative growth of a brain tumor. This model predicts important clinical data over time in agreement with published clinical and experimental data for a tumor growing over three orders of magnitude in radius. Further research has modeled tumors comprised of two separate subpopulations. The likelihood of a small subpopulation emerging from a larger one has been quantified. In addition, the importance of understanding clonal composition in forming medical prognosis has been underscored. Other work is underway to model the dynamics of invasive tumor growth.