Rice researchers automate defect detection in diamond, other advanced semiconductors

Rice University researchers have automated defect detection in diamond and other advanced semiconductor materials, aiming to improve reliability in electronic and quantum devices. The work, dated June 25, 2026, introduces a Python-based software workflow that analyzes high-resolution X-ray diffraction data to measure microscopic flaws inside crystals. According to the study in Advanced Materials, the method identifies dislocations and irregularities in atomic lattices and calculates their density. Lead authors and researchers say dislocations can affect how charge and heat move, influencing efficiency, reliability, and manufacturability at scale. The framework is described as especially suited to diamond and wide-bandgap semiconductors, which can handle more heat and electrical stress than silicon. To validate the approach, the team examined four commercially available single-crystal diamond grades, finding electronic-grade diamond with the lowest defect density and most uniform quality. Rice also highlighted that diamond’s performance depends strongly on crystal quality.