Dr. Garg Receives NSF CAREER Grant

On February 7, Assistant Professor Jivtesh Garg was awarded the CAREER grant from the National Science Foundation. He will be working on the investigation of strain and superior functionalization schemes for large enhancement of thermal conductivity in polymer-graphene nanocomposites and binary semiconductors. The NSF grant award for this project is a total of $500,000.

The NSF CAREER project targets large enhancement in thermal conductivity of polymer-graphene nanocomposites and group III-V semiconductors. Such high thermal conductivity polymers and semiconductors will significantly improve thermal management in electronics, automotive, aerospace, power generation, and energy harvesting applications. The approach involves simultaneously aligning the most thermally conductive paths in polymer and graphene particles and also covalently bonding the two to enhance thermal conductance at the polymer-graphene interface. Promising results have been achieved by our group in preliminary work. The thermal conductivity of semiconductor materials will be enhanced through phonon lifetime engineering.

The project also aims to enhance the participation of high school students through a summer camp program. To stimulate fascination with thermal transport, high school students will measure thermal response through colorful visualization of temperatures maps using infra-red imaging. Simultaneously the program will aim to enhance diversity by engaging American Indian students from various colleges in Oklahoma. The participants will develop an understanding of both atomistic simulations and perform experimental characterization of thermal transport.

Within polymers, thermal conductivity is highest along the polymer chain axis. Similarly, graphene nanoplatelets have dramatically higher in-plane compared to through-plane thermal conductivity. Simultaneous alignment of polymer chains and planar direction of nanoplatelets is achieved in this project through strain. Alignment is characterized through microscopy and imaging. As a second aspect, non-equilibrium Green’s function computations are used to achieve understanding of covalent bonding schemes enabling superior interfacial thermal conductance between polymer and graphene. Functionalized polymer composites will be prepared through such efficient schemes and thermally characterized in this work both experimentally and via atomistic simulations.

Finally, energy gap in the vibrational spectra of certain group III-V semiconductors has been shown to dramatically suppress scattering of low energy phonons, leading to large enhancement in phonon lifetimes, thus increasing overall material thermal conductivity. We have demonstrated this effect in ideal short-period superlattices and more recently in Gallium Nitride. This project will computationally explore strain engineering to further increase energy gap, resulting in higher phonon lifetimes. Strain effects will be quantified accurately through a first-principles approach based on deriving interatomic force interactions from density-functional theory and using them in an exact solution of the phonon Boltzmann transport equation.

Dr. Garg says that he is very thankful to National Science Foundation (NSF) for awarding him this grant. It will allow him to significantly enhance research, in his group, related to thermal transport at the atomistic scale for design of advanced materials for thermal management and energy conversion applications.

Congratulations Dr. Garg!

Dr. Song Receives Multiple Awards for Current Research

Dr. Li Song, an associate professor at AME, received three awards for her current research projects. Two awards are from the Department of Energy, and the third award is from Battelle – Pacific Northwest National Laboratory.

Song is the lead PI for the development and validation of a home comfort system for total performance deficiency/fault detection and optimal control project, which received a DOE fund of $993,149. The research team will develop and validate a smart thermostat-integrated low-cost home energy management system, including a data connection framework; a computationally efficient, self-learning home thermal model; automatic fault detection and analysis algorithms; and home energy management information and controls based on in-situ measured efficiencies of heating and cooling equipment, the air distribution system, and the building envelope.

The second DOE fund is $551,566 for the performance demonstration of an occupancy sensor-enabled integrated solution for commercial buildings project. The research team will validate the performance and savings of three HVAC control (fan, cooling coil valve, outside air) algorithms integrated with occupancy sensing data to optimize ventilation delivery.

A $50,000 award was given to Song from Battelle – Pacific Northwest National Laboratory for her Transactive-Control Based Connected Home Solution for Existing Residential Units and Communities project.

This is a summary of Song’s research proposal sent to Battelle: To obtain the overall project aims, the development of machine learning techniques to calibrate the initial physical model that estimates and predicts energy use of a house and its response to control signals is extremely important. An effective home thermal model, that can predict the indoor air temperature dynamics under different weather, HVAC output and internal gains from appliances and occupants, is essential for the development.

BEEL initiated the development of a self-learning home thermal model two years ago. The BEEL home model, currently limited for a house with an A/C and gas-furnace heater, can automatically identify the model parameters with minimum data needed and precisely predict the space temperature and home HVAC energy uses for a house. To enhance the connectivity and compatibility of the platform proposed by PNNL, BEEL is committed to expand the home thermal model for a heat pump system and test enhanced home model using two houses located in Oklahoma through the partnership with OG&E. The challenge of modeling the heat pump is that the heating output from a heat pump is no longer constant as is for a gas furnace heater. A correlation of the heating output of a heat pump and outdoor air temperature needs to be formulated and similarly, a correlation between cooling output of a heat pump and weather might be needed for cooling season as well.

Congratulations Dr. Song!