Multifunctional Materials Group


                                 Participants
 
Faculty Leader
Ralph Smith
Postdoctoral Fellows
Michael Stuebner
Graduate Students
Lisa Downen
Xiang Fan
Stephen May
Francesca Reale-Levis
Donovan Shickley
Heather Wilson
Undergraduate Students
David Pate


Picture of
Myself Lisa Downen Stephen May Francesca Reale-Levis Charles Shickley Heather Wilson
Ralph Smith
Michael Stuebner
Lisa Downen
Xiang Fan
Stephen May
Francesca Reale-Levis
Donovan Shickley
Heather Wilson
David Pate



                                      Research Highlights

The Multifunctional Materials Group focuses on model development, full and reduced-order simulation techniques, parameter estimation, and control design for a range of materials including PZT, various ferromagnetic compounds, shape memory alloys, polymers and composites, and carbon nanotube-infused polymers.


1.  Model Development for Shape Memory Polymers


Shape memory polymers (SMP) are similar to shape memory alloys (SMA) in the sense that they exhibit the shape memory effect and capability to generate and recover from large strains.  However, they differ in the sense that these effects in SMP are due to complementary components at the molecular level including cross-links that determine permanent shape and switching segments that specify temporary configurations.

Shape memory polymers and composites provide the advantage of being lightweight, flexible, cost-effective, capable of generating larger deformations than SMA, and they can be tailored to meet specific control criteria.  Due to the molecular basis for the shape memory effect in SMP, they can be controlled by light or chemicals as well as by heating.  This provides the possibility for employing light as an input for deployment or shape control.  It also makes the compounds viable candidates for use as biological or chemical sensors.

Ryan Siskind's dissertation research focused on the development and numerical simulation of constitutive and system models for shape memory polymers employed for high performance actuation. This involved experimental validation using data collected in collaboration with Chris Yakacki, MedShape Solutions, Inc.

Shape Memory Polymer



2. Model Development for Carbon Nanotube-Infused Polyimides

Polyimides are a class of polymers that are thermally and chemically stable, radiation resistant, and highly flexible.  The inclusion or carbon nanotubes introduces conductivity and provides the compounds with the capability of becoming active structures.  Hence they are being considered for a range of aerospace applications including gossamer mirrors and antennas.  Heather Wilson is developing fundamental constitutive and system models for nanotube-infused polyimides and structures employing these compounds.  The models are being validated using data collected by Sumanth Banda and Zoubeida Ounaies at Texas A&M University.


3.  PZT-Based Actuators and Sensors

Actuators and sensors employing the ferroelectric material lead zirconate titanate (PZT) are being widely investigated for applications requiring high set point accuracy, large input forces, and broadband capabilities.  These properties make PZT transducers advantageous in applications ranging from laser positioning to vibration isolation platforms.  However, due to its ceramic nature, initial PZT devices proved brittle and were not easily molded to underlying surfaces.  This has recently been addressed through the development of actuators such as THUNDER (THin layer UNimorph Driver and sEnsoR), piezoceramic fiber composites (PFC) and Macro-Fiber Composites (MFC).

Michael Stuebner is investigating the development of models and simulation packages for MFC for subsequent control design.  These models are being validated using experimental data collected by Dan Inman and his colleagues at VA Tech.  David Pate is investigating similarities and differences between the Homogenized Energy Model (HEM) and Prandtl-Ishlinskii models for these compounds.


THUNDER and MFC



4. Model Development, Parameter Estimation and Control Design for Terfenol-D Transducers

Terfenol-D actuators and sensors are presently being considered for a range of applications including sonar transduction, high speed milling, torque sensing, and high fidelity loudspeakers.  For all of these applications, however, it is necessary to characterize the inherent material nonlinearities and hysteresis in a manner that facilitates design and real-time control implementation.

Lisa Downen is investigating the development of numerical techniques to reduce implementation times for algorithms.  She is presently focusing on algorithms for ferroelectric and ferromagnetic materials but due to the universal nature of the modeling framework, resulting techniques will also likely apply to shape memory alloys.

Michael Stuebner and Jayasimha Atulasimha (VCU) are investigating the development and implementation of homogenized energy models (HEM) in collaboration with Billy Oates (FSU).  They are also investigating the development of control algorithms that are being tested at Etrema Products, Inc.  Xiang Fan's dissertation research focuses on the development and implementation of adaptive control algorithms for magnetic and ferroelectric actuators.


5. Development of Statistical Emulators and Metamodels

The homogenized energy model (HEM), used to characterize the nonlinear dynamics and hysteresis inherent to ferroic materials is based on energy analysis at the lattice level in combination with stochastic homogenization techniques that incorporate material and field nonhomogeneities.  Due to its energy basis, it incorporates a range of input behavior including stress, temperature and frequency dependencies.  However, its incorporation on a range of underlying physics gives it a level of complexity that presently precludes real-time implementation at for very high speed applications (e.g., 10 Khz or above).

Graduate student Francesca Reale-Levis is investigating the development of Bayesian and Gaussian emulators that incorporate fundamental physics, are highly efficient to implement, and statistically quantify the uncertainty associated with the resulting reduced-order models.


6. Model Development, Simulation and Analysis of Metamaterials

Metamaterials are often defined as those that engineered to have properties not naturally occurring in nature.  Examples include "left-handed" materials having negative indices of refraction.  Applications under investigation include super lenses that surpass existing diffraction limits, stealth technology, magnetic resonance imaging, and improved antenna capabilities including the potential for arbitrarily small cell phones.  Donovan Shickley is presently investigating model development for active metamaterial structures to improve the dynamic frequency response and bandwidth.  An overview of some of these issues can be found in his AMGSS presentation.