Collective Properties and Dynamics in Mesoscale Architectures
Opportunity (WHY?)
• How can we understand and predict the behavior
of mesoscale architectures?
• 3-D structures for energy conversion and storage
must be assembled in specific architectures (e.g.,
ordered for plasmonic PV, disordered for some
batteries)
• Dimensions and geometry must be determined
• Relevant functional behavior may be nonlinear
(plasmonics, ion transport)
• If disordered, porosity, tortuosity and more may
be critical to behavior, particularly if nonlinear
Timeliness (WHY NOW?)
• Functional mesoscale assemblies of nano or micro
structures play major role in current energy research
• Diversity of architectures seems boundless
• Theoretical/computational tools to assess and
predict behavior are largely missing, particularly for
disordered systems
From Gary Rubloff
Approaches (HOW?)
• Develop new characterization techniques to
characterize disorder, likely going beyond
porosity/tortuosity to provide new measures of local
geometry distributions important to nonlinear
behavior
• Develop modeling approaches for local behavior
• Integrate these models into larger-scale system
models
• Validate local models through experiments using
well-defined model test structures
• Generate disordered architectures in computational
models, using design ground rules and Monte Carlo
like approaches to create test architectures
Impact (SO WHAT?)
• New theoretical and computational tools to assess
and predict behavior of disordered and ordered
architectures
• Capability to deal with nonlinear responses
Submitted by Gary Rubloff
Affiliation University of Maryland