Light Emitting Diodes (LEDs) are used in everything from household lighting and mobile phones to large display screens. Improving their efficiency could reduce energy use and enhance performance across a wide range of technologies.
A new study, involving researchers from the University of Liverpool and the University of Strathclyde, has demonstrated a powerful new way to identify tiny crystal defects that can reduce the efficiency of LED materials. The advance could help scientists better understand how these defects form and ultimately support the development of more efficient electronic and optoelectronic devices.
LEDs are commonly made from gallium nitride, a crystalline material whose properties depend on the arrangement of atoms within it. During crystal growth, small imperfections known as dislocations can form. These line-like defects disturb the otherwise regular atomic structure of the crystal and can reduce the efficiency with which electrical energy is converted into light.
Understanding the abundance and distribution of dislocations is therefore important for improving the performance of LED materials. However, identifying them has traditionally been challenging.
Researchers have typically relied on Transmission Electron Microscopy (TEM), a technique that requires the preparation of extremely thin samples and examines only very small areas of material. While highly detailed, the approach can be time-consuming and may not always provide a representative picture of the crystal as a whole.
In the new study, published in Acta Materialia, the team used a range of Scanning Electron Microscopy techniques that enable much larger areas to be examined more easily. In particular, they applied Electron Backscatter Diffraction (EBSD), which measures subtle variations in crystal orientation at the microscopic scale.
By combining EBSD with a calculation method developed by University of Liverpool geoscientist Professor John Wheeler, the researchers were able to identify individual dislocations and distinguish between different types, including edge, screw and mixed dislocations.
The study represents an important step forward because previous EBSD-based approaches could detect distortions caused by large numbers of dislocations but were not sufficiently detailed to identify individual defects directly. The researchers believe this is the first time such imaging has been achieved using this approach in gallium nitride.
