Future Directions for Selected Topics in Mechanical and Civil ...

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cost-effective and competitive manufacturing enterprises. In addition, such adaptive
manufacturing systems can be controlled through cloud computing so that the latest and
most advanced manufacturing strategy can be easily deployed to many workstations.
4.7.1. Interface engineering
Heterogeneous materials represent an important class of practical feedstocks in
a variety of emerging technological applications such as nanoelectronics, photovoltaics,
thermoelectrics, electrochemical energy storage, and fuel storage with solid-state
materials. Nanostructuring and surface functionalization,
in particular, are expected to enable rapid advances in
the performance of materials for such applications.
Transport of charge, mass, and/or energy is often
essential to the successful performance of these
materials in addition to their mechanical behavior, but a
theoretical foundation for understanding the influence of
microscopic constituent attributes and processing conditions on transport and
mechanics is lacking.
The theoretical study of heterogeneous material properties was pioneered more
than a century ago, by considering systems of inclusions of simple shapes embedded in
a host. Most notably, effective medium approximations of various types have been
developed to model material properties based on simplified micromechanical contact
models between particles. Despite these advances, only partial understanding has been
gained regarding the effects of realistic inclusion shape, microstructure, and particularly
subcontinuum processes on the overall properties of heterogeneous media. Additionally,
the change of properties of materials near interfaces remains difficult to quantify, yet
essential to understanding and designing new materials. New methods that capture the
geometric complexity of such composites while also rigorously incorporating the
interfacial physics of heterogeneous interactions are needed to exploit the full potential
of this emerging field. Such advances will require the combination of large-scale
computing, predictive process simulation, and hierarchical stochastic modeling, along