Heteroepitaxy and Defect Formation in Nanopillars: An Experimental and Theoretical Study
May 16, 2013
from 12:00 PM to 02:00 PM
|Where||Engr. IV Bldg. Tesla Rm. 53-125|
|Contact Name||Joshua Shapiro|
|Add event to calendar||
Advisor: Professor Diana Huffaker
Nanopillars are a next generation platform for building high-performance opto-electronic devices. The uniform arrays of III-V semiconductor pillars are microns long, vertically oriented, and have sub 100 nm diameters. The small volumes and crystalline surfaces make them excellent candidates for low noise detectors, and with their well-controlled periodic geometry they can be engineered into novel photonic devices. This work demonstrates new growth capabilities that will improve and enhance the performance of nanopillar opto-electronic devices. Using a combined experimental and theoretical approach I demonstrate control and understanding of three-dimensional hetero-epitaxy in the GaAs and InP material systems, and control of a prevalent defect in GaAs nanopillars called a stacking fault. First-principles density-functional-theory calculations of adatom binding energy and mobility reveal the atomistic processes that determine the direction of growth during hetero-epitaxy. The hetero-epitaxial capability in GaAs/InGaAs has already been critical in the realization of nanopillar based lasers and LEDs. Further improvements in device performance can be achieved by leveraging the newly developed capability to grow GaAs with fewer stacking faults, and the hetero-epitaxial techniques demonstrated with InP/InAsP can be used to access wavelengths not possible with GaAs/InGaAs nanopillars.
Joshua Shapiro received the B.A. degree in Astronomy and Astrophysics from the University of California at Berkeley In 1999, and the M.S. degree from the New Mexico Institute of Mining and Technology in 2008. He is currently a Ph.D. candidate in the Electrical Engineering Department at UCLA. His research interests include novel epitaxial platforms for electronic devices, and theoretical modeling of epitaxial growth and electrical transport using high performance parallel computing clusters.