Atoms to Devices—Evolution of Heterostructure Degradation in High Energy Environments

The modernization of electronic technologies operating in high radiative environments is necessary for a variety of applications to advance including: the commercialization of space, the goal of manned missions to Mars and increasing the analytical reach of unmanned spacecraft, defense applications, or even more holistic understanding of Low Earth Orbit (LEO) spaces. Current state-of-the-art rad-hard devices significantly lag behind conventional technologies in both size and processing power. In order to speed development of rad-hard structures and materials, we must understand the effects of these high intensity environments on not only the full device, but also the effects on the microstructure and chemistry of the component materials and, perhaps most importantly, interfaces.

While understanding the effects of space irradiating environment is important, sending materials to orbit for exposure is expensive. Simulating the high radiation environment of space on-ground gives a first order approximation for examining material evolution under irradiation and better experimental control. Here we examine the effects of irradiation on interfaces in a commercially obtained GaN device grown on Si under heavy ion and proton damage. As GaN growth directly on Si contains extensive defects, such as dislocations, the device has a few microns of buffer layer, allowing for the additional examination how existing defects may affect the evolution of material and interfaces under irradiation.

To simulate the space environment, 4 MeV Cu ion and 1 MeV proton irradiations are performed at University of Tennessee Knoxville’s TIBML (Tennessee Ion Beam Materials Laboratory) and are used to induce structural damage and electronic damage respectively in independent and overlapping regions. As GaN is considered already relatively radiation tolerant, doses covering 3 orders of magnitude (1E15, 1E16, and 1E17 Cu ions/cm²) are examined. Correlative microscopy including Scanning Transmission Electron Microscopy (STEM) imaging, Energy Dispersive X-ray Spectroscopy (EDS), Atom Probe Tomography (APT), and Conductive Force Microscopy (CFM), are combined into multi-modal data sets to examine defect structures and changes to chemistry and properties at interfaces on the atomic to nano scale. AI/ML is used to assist in labelling the multi-modal microscopy data and defects to form a statistical categorical understanding. Cross-sectional regions of pre- and post-irradiation samples are extracted by focused ion beam (FIB) for examination and comparison by STEM, APT, and CFM.