Helium ATOM Scattering Studies of Single Uncorrelated and Correlated Defects on Surfaces

Abstract

Helium atom scattering (HAS) from crystal surfaces is unique among all surface science probes in that it is sensitive to only the outermost surface layer, entirely non-destructive and applicable to all types of surfaces: insulators, semiconductors, and metals. With the recent advent of improved energy resolution (1%) and sensitivity (dynamic range of 106) HAS is becoming increasingly useful in the study of defects on surfaces as well as for studying growth processes.First the basic HAS techniques are reviewed and compared with LEED. Then several examples of high resolution studies of disordered surface structures will be presented. Recent work has concentrated on studying randomly distributed point or linearly extended defects of low concentration. The large angle diffuse (incoherent) elastic scattering from isolated step edge defects on otherwise smooth surfaces, e.g. metallic fcc(001) and (111) planes, yields information on the concentration, orientation and structure of single steps (Pt(lll), Al(111), Cu(111) and Ni(001)). In accord with the unique sensitivity of HAS to step edges the diffraction patterns from periodically stepped surfaces show a rich structure. A careful kinematic analysis of the stepped (332) aluminum surface reveals extensive facetting. The temperature induced changes in step concentration, roughening and facetting have also been studied.Finally very recent results on the epitaxial growth of Pb on Cu(111) have revealed an unexpected intensity nodulation indicating oscillations in the stability of the layers related to a quantum size effect. Further improvements in sensitivity and resolution will make even more detailed studies of the structure and growth on insulators, semi-conductors and metal surfaces possible.KeywordsAngular DistributionHelium AtomStep EdgeIncident Wave VectorSpecular BeamThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.