Arizona State University (ASU) proposes a comprehensive project to advance fundamental knowledge in the selective area doping of GaN using selective regrowth of gallium nitride (GaN) materials. This will lead to the development of high-performance GaN vertical power transistors. The ASU team aims to develop a better mechanistic understanding of these fundamental materials issues, by focusing on three broad areas. First, they will use powerful characterization methods to study fundamental materials properties such as defects, surface states, and investigate possible materials degradation mechanisms. Next, they will develop innovative epitaxial growth and fabrication processes such as Atomic Layer Etching and novel surface passivations, to tackle the materials engineering challenges related to selective area doping for GaN p-n junctions. Finally, they will apply their research to demonstrate randomly placed, reliable, contactable p-n junctions for GaN vertical power devices. If successful, this project will provide a path towards high efficiency, high power, small form factor, and high thermal performance GaN vertical power devices.

Arizona State University (ASU) is developing a hybrid solar energy system that modifies a CSP trough design, replacing the curved mirror with solar cells that collect both direct and diffuse rays of a portion of sunlight while reflecting the rest of the direct sunlight to a thermal absorber to generate heat. Electricity from the solar cells can be used immediately while the heat can be stored for later use. Today's CSP systems offer low overall efficiency because they collect only direct sunlight, or the light that comes in a straight beam from the sun. ASU's technology could increase the amount of light that can be converted to electricity by collecting diffuse sunlight, or light that has been scattered by the atmosphere, clouds, and off the earth. By integrating curved solar cells into a hybrid trough system, ASU will effectively split the solar spectrum and use each portion of the spectrum in the most efficient way possible. Diffuse and some direct sunlight are converted into electricity in the solar cells, while the unused portion of the direct sunlight is reflected for conversion to heat.

Arizona State University (ASU) is developing a solar cell that can maintain efficient operation at temperatures above 400°C. Like many other electronics, solar panels work best in cooler environments. As the temperature of traditional solar cells increases beyond 100°C, the energy output decreases markedly and components are more prone to failure. ASU's technology adapts semiconducting materials used in today's light-emitting diode (LED) industry to enable efficient, long-term high-temperature operation. These materials could allow the cells to maintain operation at much higher temperatures than today's solar cells, so they can be integrated as the sunlight-absorbing surface of a thermal receiver in the next generation of hybrid solar collectors. The solar cell would provide electricity using a portion of the incoming sunlight, while the receiver collects usable heat at high temperature that can be stored and dispatched to generate electricity as needed.

Arizona State University (ASU) is engineering a type of photosynthetic bacteria that efficiently produce fatty acids--a fuel precursor for biofuels. This type of bacteria, called Synechocystis, is already good at converting solar energy and carbon dioxide (CO₂) into a type of fatty acid called lauric acid. ASU has modified the organism so it continuously converts sunlight and CO₂ into fatty acids--overriding its natural tendency to use solar energy solely for cell growth and maximizing the solar-to-fuel conversion process. ASU's approach is different because most biofuels research focuses on increasing cellular biomass and not on excreting fatty acids. The project has also identified a unique way to convert the harvested lauric acid into a fuel that can be easily blended with existing transportation fuels.

Arizona State University (ASU) will develop a stochastic optimal power flow (SOPF) framework, which would integrate uncertainty from renewable resources, load, distributed storage, and demand response technologies into bulk power system management in a holistic manner. The team will develop SOPF algorithms for the security-constrained economic dispatch (SCED) problem used to manage variability in the electric grid. The algorithms will be implemented in a software tool to provide system operators with real-time guidance to help coordinate between bulk generation and large numbers of DERs and demand response. ASU's project features unique data-analytics based short-term forecast for bulk and distributed wind and solar generation utilized by the advisory tool that generates real-time recommendations for market operators based on the SOPF algorithm outputs.