Semiconductors are used in lasers, camera imagers, and computer chips that go into just about anything, so it’s important for manufacturers to be able to classify the materials. Manufacturers add impurities to semiconductor materials to control their electrical properties so they can be customized for different applications. The challenge is to make sure the material is completely uniform so that it will perform properly. “Non-uniform semiconductors lead to computer chips that fail, lasers that burn out, and imagers with dark spots,” explains Matthew Grayson, a Northwestern Engineering researcher.
Grayson’s team has developed a technique that helps measure these inconsistencies. Their new mathematical method makes semiconductor characterization more efficient, more precise, and simpler. By flipping the magnetic field and repeating one measurement, Grayson can tell if a semiconductor material is high quality be determining if the electrical conductivity is uniform across the entire material.
“Up until now, everyone would take separate pieces of the material, measure each piece, and compare differences to quantify non-uniformity,” Grayson said, in a Northwestern release. “That means you need more time to make several different measurements and extra material dedicated for diagnostics. We have figured out how to measure a single piece of material in a magnetic field while flipping the polarity to deduce the average variation in the density of electrons across the sample.”
The new method can be used to analyze samples ranging in size from a 10-micron flake to a 12-inch wafer. This wide range is especially useful for 2-D materials, such as graphene, which are too small for traditional methods. Grayson has applied for a patent and described the technique in a paper published in the journal Physical Review Letters.
Source: Northwestern University
