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Damena Agonafer
University of Maryland, USA
Dr. Damena Agonafer is the Clark Faculty Fellow and an Associate Professor at the University of Maryland, College Park, where he directs the Nanoscale Energy and Interfacial Transport Lab (NEITLab). Additionally, he is the site director of the EARTH research center at the University of Maryland, which is focused on developing novel, Earth-friendly refrigerants and HVACR technologies. Agonafer earned his PhD at the University of Illinois Urbana-Champaign, where he was supported by the Alfred P. Sloan fellowship, Graduate Engineering Minority Fellowship, and NSF Center of Advanced Materials for Purification of Water with Systems (WaterCAMPWS). After his PhD, Damena joined Professor Ken Goodson’s Nanoheat lab as a Stanford University Postdoctoral Scholar in the Mechanical Engineering Department. Before joining the University of Maryland, Damena was an Assistant Professor in the Department of Mechanical Engineering at Washington University in Saint Louis. He is a recipient of the Google Research Award, Sloan Research Fellowship Award, Cisco Research Award, NSF CAREER Award, ASME Early Career Award, and ASME K-16 Outstanding Early Faculty Career in Thermal Management Award. He was also one of 85 early-career engineers in the US selected to attend the 2021 National Academy of Engineering’s 26th annual US Frontiers of Engineering symposium.
Dr. Agonafer’s research interest is at the intersection of thermal-fluid sciences, interfacial transport phenomena, and renewable energy. He is focused on developing novel materials and systems for the thermal management of power and microelectronic systems, HVACR applications, and thermal energy storage for utility-scale applications. He aims to achieve transformational technological changes by tuning and controlling solid-liquid-vapor interactions at micro-/nano length scales. Specific focus areas include developing novel micro-/nanostructures for two-phase heat transfer for efficient data center IT compute cooling and improved refrigeration processes, high capacitance dielectric slurries for enhanced thermal management of defense applications, and phase change materials for transient/diurnal thermal loads. Additionally, his research group is tapping the vast potential of machine learning to facilitate faster modeling and design of thermal technologies for different applications.