Molecular Beam Epitaxial Growth of III-V Semiconductor Nanostructures on Silicon Substrates

The main focus and concerns of this PhD thesis is the growth of III-V semiconductor nanostructures (Quantum dots (QDs) and quantum dashes) on silicon substrates using molecular beam epitaxy (MBE) technique. The investigation of influence of the major growth parameters on their basic properties (density, geometry, composition, size etc.) and the systematic characterization of their structural and optical properties are the core of the research work. The monolithic integration of III-V optoelectronic devices with silicon electronic circuits could bring enormous prospect for the existing semiconductor technology. Our challenging approach is to combine the superior passive optical properties of silicon with the superior optical emission properties of III-V material by reducing the amount of III-V materials to the very limit of the active region. Different heteroepitaxial integration approaches have been investigated to overcome the materials issues between III-V and Si. However, this include the self-assembled growth of InAs and InGaAs QDs in silicon and GaAx matrices directly on flat silicon substrate, sitecontrolled growth of (GaAs/In0,15Ga0,85As/GaAs) QDs on pre-patterned Si substrate and the direct growth of GaP on Si using migration enhanced epitaxy (MEE) and MBE growth modes. An efficient ex-situ-buffered HF (BHF) and in-situ surface cleaning sequence based on atomic hydrogen (AH) cleaning at 500 °C combined with thermal oxide desorption within a temperature range of 700-900 °C has been established. The removal of oxide desorption was confirmed by semicircular streaky reflection high energy electron diffraction (RHEED) patterns indicating a 2D smooth surface construction prior to the MBE growth. The evolution of size, density and shape of the QDs are ex-situ characterized by atomic-force microscopy (AFM) and transmission electron microscopy (TEM). The InAs QDs density is strongly increased from 108 to 1011 cm-2 at V/III ratios in the range of 15-35 (beam equivalent pressure values). InAs QD formations are not observed at temperatures of 500 °C and above. Growth experiments on (111) substrates show orientation dependent QD formation behaviour. A significant shape and size transition with elongated InAs quantum dots and dashes has been observed on (111) orientation and at higher Indium-growth rate of 0.3 ML/s. The 2D strain mapping derived from high-resolution TEM of InAs QDs embedded in silicon matrix confirmed semi-coherent and fully relaxed QDs embedded in defectfree silicon matrix. The strain relaxation is released by dislocation loops exclusively localized along the InAs/Si interfaces and partial dislocations with stacking faults inside the InAs clusters. The site controlled growth of GaAs/In0,15Ga0,85As/GaAs nanostructures has been demonstrated for the first time with 1 μm spacing and very low nominal deposition thicknesses, directly on pre-patterned Si without the use of SiO2 mask. Thin planar GaP layer was successfully grown through migration enhanced epitaxy (MEE) to initiate a planar GaP wetting layer at the polar/non-polar interface, which work as a virtual GaP substrate, for the GaP-MBE subsequently growth on the GaP-MEE layer with total thickness of 50 nm. The best root mean square (RMS) roughness value was as good as 1.3 nm. However, these results are highly encouraging for the realization of III-V optical devices on silicon for potential applications.

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.