Researchers Create Better Predictions About GaN Behavior with Muli-part Simulation Model

Researchers from University College London (UCL) worked with teams at Daresbury Laboratory and the University of Bath to reveal the complex properties of gallium nitride using computer simulations. Accurate predictions of these properties can help make better blue LEDs and predict their output before actual fabrication.

LEDs  employ two layers of semiconductors: a conduction layer with electrons available and a  layer with positive charges or holes. When an electron and a hole meet, they emit a photon (light particle).A cristalline film of a particular material–GaN for blue LEDs–is grown and then doped. Dopants donate an extra positive or negative charge to the material. GaN, the key material for blue LEDs, has a large energy gap between electrons and holes (known as a wide bandgap). The wide bandgap is essential for tuning the emitted photons to produce blue light. Doping to donate mobile negative charges in the material proved to be easy. However, donating positive charges from GaN failed.  Doping GaN for positive charges required unexpectedly large amounts of magnesium, according to inventors of the blue LED who won the Nobel Prize in Physics last year.

The UCL researchers created a multi-part simulation model that makes much better predictions about GaN crystals with defects on an atomic level.  Instead of using a quantum mechanical model, which requires a super computer to make all the calculations, the team used hybrid quantum and molecular modeling, the subject of 2013’s Nobel prize in Chemistry. The new models simulate different parts of a complex chemical system with different levels of theory. The team published details of their findings in the journal Physical Review Letters.