Using Computation to Enhance LEDs

Why it Matters: The use of aluminum-, gallium-, or indium-nitride materials is common in commercially-available Light Emitting Diodes (LEDs) but various physical issues associated with using the "bulk" form of those materials negatively affects their efficiency.  Such LEDs are important as semiconductors and other kinds of technologically-advanced opto-electronic devices.  This study looked at using nano-structured forms of these materials to overcome such inefficiencies.  The same kind of physical interactions that limit their efficiency are also at play in materials being developed to harvest light energy from the Sun.

Key Challenges:  studying the electronic and optical properties of small-diameter InN nanowires using first-principles calculations requires manybody perturbation theory that in turn, depends on state-of-the-art methods, computer codes, and HPC systems.  The challenge is in modeling the excited state properties of the materials, meaning the precise description of the interaction of light with the electrons in the semiconductor. 

Accomplishments: Simulations done at NERSC suggest that nanostructures half the breadth of a DNA strand could improve LED efficiency, especially in the “green gap,” a portion of the spectrum where LED efficiency plunges.  The study showed how nanoscale wires exhibit a “quantum confinement” effect that causes emission of green light at high efficiency.  Also, just by varying their sizes, these nanostructures could be tailored to emit different colors of light, which could lead to more natural-looking white lighting while avoiding some of the efficiency loss today’s LEDs experience at high power.

NERSC Contribution: This work required the BerkeleyGW software provided by NERSC consultant Jack Deslippe.  The GW method is at the leading edge of computational materials science research because it can accurately model how light interacts with matter in semiconductors, solar photovoltaic collectors, power amplifiers, and other devices.  BerkeleyGW extends the reach of the method because its scalability on parallel computers such as those at NERSC allows larger and more complex materials to be studied.  

More Information: NERSC Principal Investigator: Emmanouil Kioupakis (University of Michigan); NERSC Project Title: Electronic and optical properties of novel photovoltaic and thermoelectric materials from first-principles; NERSC Resources Used: Edison;  paper to be published in Nano Letters; NERSC news story