Si(100) versus Ge(100): Watching the interface formation for the growth of III-V-based solar cells on abundant substrates

We investigated the atomic surface properties of differently prepared silicon and germanium (100) surfaces during metal-organic vapour phase epitaxy/chemical vapour deposition (MOVPE/MOCVD), in particular the impact of the MOVPE ambient, and applied reflectance anisotropy/difference spectroscopy (RAS/RDS) in our MOVPE reactor to in-situ watch and control the preparation on the atomic length scale for subsequent III-V-nucleation. The technological interest in the predominant opto-electronic properties of III-V-compounds drives the research for their heteroepitaxial integration on more abundant and cheaper standard substrates such as Si(100) or Ge(100). In these cases, a general task must be accomplished successfully, i.e. the growth of polar materials on non-polar substrates and, beyond that, very specific variations such as the individual interface formation and the atomic step structure, have to be controlled. Above all, the method of choice to grow industrial relevant high-performance device structures is MOVPE, not normally compatible with surface and interface sensitive characterization tools, which are commonly based on ultrahigh vacuum (UHV) ambients. A dedicated sample transfer system from MOVPE environment to UHV enabled us to benchmark the optical in-situ spectra with results from various surfaces science instruments without considering disruptive contaminants. X-ray photoelectron spectroscopy (XPS) provided direct observation of different terminations such as arsenic and phosphorous and verified oxide removal under various specific process parameters. Absorption lines in Fourier-transform infrared (FTIR) spectra were used to identify specific stretch modes of coupled hydrides and the polarization dependence of the anti-symmetric stretch modes distinguished different dimer orientations. Scanning tunnelling microscopy (STM) studied the atomic arrangement of dimers and steps and tip-induced H-desorption proved the saturation of dangling bonds after preparati- n. In-situ RAS was employed to display details transiently such as the presence of H on the surface at lower temperatures (T <; 800°C) and the absence of Si-H bonds at elevated annealing temperature and also surface terminations. Ge buffer growth by the use of GeH4 enables the preparation of smooth surfaces and leads to a more pronounced amplitude of the features in the spectra which indicates improvements of the surface quality.

Massively parallelizable list-mode reconstruction using a Monte Carlo-based elliptical Gaussian model

Purpose: A fully three-dimensional (3D) massively parallelizable list-mode ordered-subsets expectation-maximization (LM-OSEM) reconstruction algorithm has been developed for high-resolution PET cameras. System response probabilities are calculated online from a set of parameters derived from Monte Carlo simulations. The shape of a system response for a given line of response (LOR) has been shown to be asymmetrical around the LOR. This work has been focused on the development of efficient region-search techniques to sample the system response probabilities, which are suitable for asymmetric kernel models, including elliptical Gaussian models that allow for high accuracy and high parallelization efficiency. The novel region-search scheme using variable kernel models is applied in the proposed PET reconstruction algorithm. Methods: A novel region-search technique has been used to sample the probability density function in correspondence with a small dynamic subset of the field of view that constitutes the region of response (ROR). The ROR is identified around the LOR by searching for any voxel within a dynamically calculated contour. The contour condition is currently defined as a fixed threshold over the posterior probability, and arbitrary kernel models can be applied using a numerical approach. The processing of the LORs is distributed in batches among the available computing devices, then, individual LORs are processed within different processing units. In this way, both multicore and multiple many-core processing units can be efficiently exploited. Tests have been conducted with probability models that take into account the noncolinearity, positron range, and crystal penetration effects, that produced tubes of response with varying elliptical sections whose axes were a function of the crystal's thickness and angle of incidence of the given LOR. The algorithm treats the probability model as a 3D scalar field defined within a reference system aligned with the ideal LOR. Results: This new technique provides superior image quality in terms of signal-to-noise ratio as compared with the histogram-mode method based on precomputed system matrices available for a commercial small animal scanner. Reconstruction times can be kept low with the use of multicore, many-core architectures, including multiple graphic processing units. Conclusions: A highly parallelizable LM reconstruction method has been proposed based on Monte Carlo simulations and new parallelization techniques aimed at improving the reconstruction speed and the image signal-to-noise of a given OSEM algorithm. The method has been validated using simulated and real phantoms. A special advantage of the new method is the possibility of defining dynamically the cut-off threshold over the calculated probabilities thus allowing for a direct control on the trade-off between speed and quality during the reconstruction.