Contact: Prof.
C.T. Avedisian
Email: cta2@cornell.edu
Phone: 255-5105
Office: 193 Grumman Hall
Thermal Properties of Nano-structured
Materials: Superlattices and thin films
Nanotechnology is an
exciting field that has great promise for benefiting society. We have a project
in this area that is ‘basic science’ in nature yet has practical value. We want
to measure the thermal properties of nano-structured
materials with characteristic length scales of about 10-9 m. The interest
in this venture is that properties on the nanoscale
can be vastly different (lower) than ‘bulk’ properties because of the way heat
is transported at the nanoscale. We can’t use conventional measurement
techniques designed for bulk systems, such as thermocouples, on nanoscale materials so we are forced to develop new methods
to probe on this scale. We are doing that in our research and the opportunities
for significant advances are exciting.
Our current work targets a particular class of integrated nanomaterials—superlattices—for measurement. Superlattices are a class of integrated nanomaterials with repeated thin films of two or more different crystalline materials. They are used in a wide variety of electronic devices and offer great promise for advancing the state of nanotechnology. However, little is known about their thermal properties. Their thermal properties can be significantly different from values predicted from the constituent alloys’ values and mixing rules based on some form of weighted averaging of the alloys. This fact makes it important to accurately measure the thermal properties of nano-structured materials in general, and in particular for superlattices to probe details of individual layers.
The tasks for the project could
include any of the following activities: nanofabrication of superlattices
and other samples in Cornell’s facilities (appropriate training is required for
this), working with the lasers and an automatic measurement apparatus
(including electronics and optomechanics), engaging
in theoretical modeling of the microscale heat
transfer, studying optimal parameters to enhance experimental data quality
(‘design of experiments’), and performing numerical analysis of data using multiparameter algorithms.
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