Segregation of alloy and dopant atoms at defects in nitride materials

Lead Research Organisation: University College London
Department Name: London Centre for Nanotechnology


Electronic and opto-electronic devices based on gallium nitride (GaN) form a multi-billion dollar industry across the world, including lighting (LEDs), power sources and communications (radar and 5G). One of the most challenging aspects of developing these devices commercially is the high density of defects - i.e. mistakes in the crystal's structure - found in most commercially grown GaN, such as dislocations and stacking faults. It is possible to grow GaN with fewer of these mistakes, but it is slow and expensive, and most devices therefore contain a high density of defects, which will affect device performance.

In particular, all devices will contain either alloying elements (aluminium gallium nitride, AlGaN, and indium gallium nitride, InGaN, are made by alloying Al and In with Ga during growth) and/or doping elements (magnesium, Mg, is added to change the conduction properties of GaN, for instance for making LEDs) and these elements will interact with the defects, which can prevent the extra elements from having the intended impact or change the local properties of the material being grown in undesirable ways.

We will study how alloying and doping elements interact with defects, in particular where larger or smaller numbers of these atoms are found relative to what is expected. We will seek to understand why these changes happen, and ultimately how they can be controlled, either to reduce the numbers of defects, or to reduce the harmful effects of the defects on the desired materials properties.

Our project will link state-of-the-art experimental techniques with cutting edge theory and modelling approaches. The experimental data will allow us to examine the positions of individual atoms with exquisite detail, while the modelling will address problems which involve large numbers of atoms, something which standard approaches cannot manage. This combination of techniques will enable us to understand and control the materials in ways that are not possible with each technique independently, and which will feed into industrial processes.


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