Model for nucleation in GaAs homoepitaxy derived from first principles

The initial steps of MBE growth of GaAs on beta 2-reconstructed GaAs(001) are investigated by performing total energy and electronic structure calculations using density functional theory and a repeated slab model of the surface. We study the interaction and clustering of adsorbed Ga atoms and the adsorption of As_2 molecules onto Ga atom clusters adsorbed on the surface. The stable nuclei consist of bound pairs of Ga adatoms, which originate either from dimerization or from an indirect interaction mediated through the substrate reconstruction. As_2 adsorption is found to be strongly exothermic on sites with a square array of four Ga dangling bonds. Comparing two scenarios where the first As_2 gets incorporated in the incomplete surface layer, or alternatively in a new added layer, we find the first scenario to be preferable. In summary, the calculations suggest that nucleation of a new atomic layer is most likely on top of those surface regions where a partial filling of trenches in the surface has occurred before.Comment: 8 pages, 14 figures, Submitted to Phys. Rev. B (December 15, 1998). Other related publications can be found at http://www.fhi-berlin.mpg.de/th/paper.htm

Diagnosis and management of bone fragility in diabetes: an emerging challenge

Fragility fractures are increasingly recognized as a complication of both type 1 and type 2 diabetes, with fracture risk that increases with disease duration and poor glycemic control. Yet the identification and management of fracture risk in these patients remains challenging. This review explores the clinical characteristics of bone fragility in adults with diabetes and highlights recent studies that have evaluated bone mineral density (BMD), bone microstructure and material properties, biochemical markers, and fracture prediction algorithms (i.e., FRAX) in these patients. It further reviews the impact of diabetes drugs on bone as well as the efficacy of osteoporosis treatments in this population. We finally propose an algorithm for the identification and management of diabetic patients at increased fracture risk