On the mechanisms of spontaneous growth of III-nitride nanocolumns by plasma-assisted molecular beam epitaxy

A study of the GaN nanocolumns nucleation and growth by molecular beam epitaxy on Si(1 1 1) is presented. Ga droplets with different diameters (340–90 nm) were deposited on the substrate, prior to growth, to determine any effect on the nanocolumns size and distribution. Results indicate that there is no difference in nanocolumnar size and density whether Ga droplets are used or not, meaning that Ga droplets do not act as catalysts for the nanocolumns nucleation. In addition, Ga droplets were never observed on the nanocolumn tips upon growth termination. These findings rule out the vapor–liquid–solid mechanism. Instead, driven by a strong lattice mismatch nanocolumnar nucleation occurs spontaneously by Volmer–Weber growth mechanism, whereas nitrogen excess prevents the nucleation sites coalescence. Further nanocolumnar growth proceeds by direct Ga incorporation on the nanocolumns top and by Ga diffusion along the nanocolumns sidewalls up to their apex. Related to this diffusion mechanism, we found that Ga droplets, when used, may act as reservoirs to feed Ga atoms to the neighboring nanocolumns. Nanocolumns preserve a constant diameter if growth conditions are not modified because of a strong metal ad-atom diffusion length along their sidewalls. The effect of using AlN buffer layers on the nanocolumnar growth and morphology is also addressed

A bank of unscented Kalman filters for multimodal human perception with mobile service robots

A new generation of mobile service robots could be ready soon to operate in human environments if they can robustly estimate position and identity of surrounding people. Researchers in this field face a number of challenging problems, among which sensor uncertainties and real-time constraints. In this paper, we propose a novel and efficient solution for simultaneous tracking and recognition of people within the observation range of a mobile robot. Multisensor techniques for legs and face detection are fused in a robust probabilistic framework to height, clothes and face recognition algorithms. The system is based on an efficient bank of Unscented Kalman Filters that keeps a multi-hypothesis estimate of the person being tracked, including the case where the latter is unknown to the robot. Several experiments with real mobile robots are presented to validate the proposed approach. They show that our solutions can improve the robot's perception and recognition of humans, providing a useful contribution for the future application of service robotics

A method for performance diagnosis and evaluation of video trackers

Several measures for evaluating multi-target video trackers exist that generally aim at providing ‘end performance.’ End performance is important particularly for ranking and comparing trackers. However, for a deeper insight into trackers’ performance it would also be desirable to analyze key contributory factors (false positives, false negatives, ID changes) that (implicitly or explicitly) lead to the attainment of a certain end performance. Specifically, this paper proposes a new approach to enable a diagnosis of the performance of multi-target trackers as well as providing a means to determine the end performance to still enable their comparison in a video sequence. Diagnosis involves analyzing probability density functions of false positives, false negatives and ID changes of trackers in a sequence. End performance is obtained in terms of the extracted performance scores related to false positives, false negatives and ID changes. In the experiments, we used four state-of-the-art trackers on challenging real-world public datasets to show the effectiveness of the proposed approach

Development of a modular test system for the silicon sensor R&D of the ATLAS Upgrade

High Voltage CMOS sensors are a promising technology for tracking detectors in collider experiments. Extensive R&D studies are being carried out by the ATLAS Collaboration for a possible use of HV-CMOS in the High Luminosity LHC upgrade of the Inner Tracker detector. CaRIBOu (Control and Readout Itk BOard) is a modular test system developed to test Silicon based detectors. It currently includes five custom designed boards, a Xilinx ZC706 development board, FELIX (Front-End LInk eXchange) PCIe card and a host computer. A software program has been developed in Python to control the CaRIBOu hardware. CaRIBOu has been used in the testbeam of the HV-CMOS sensor AMS180v4 at CERN. Preliminary results have shown that the test system is very versatile. Further development is ongoing to adapt to different sensors, and to make it available to various lab test stands

HV/HR-CMOS sensors for the ATLAS upgrade—concepts and test chip results

In order to extend its discovery potential, the Large Hadron Collider (LHC) will have a major upgrade (Phase II Upgrade) scheduled for 2022. The LHC after the upgrade, called High-Luminosity LHC (HL-LHC), will operate at a nominal leveled instantaneous luminosity of 5× 1034 cm−2 s−1, more than twice the expected Phase I . The new Inner Tracker needs to cope with this extremely high luminosity. Therefore it requires higher granularity, reduced material budget and increased radiation hardness of all components. A new pixel detector based on High Voltage CMOS (HVCMOS) technology targeting the upgraded ATLAS pixel detector is under study. The main advantages of the HVCMOS technology are its potential for low material budget, use of possible cheaper interconnection technologies, reduced pixel size and lower cost with respect to traditional hybrid pixel detector. Several first prototypes were produced and characterized within ATLAS upgrade R&D effort, to explore the performance and radiation hardness of this technology. In this paper, an overview of the HVCMOS sensor concepts is given. Laboratory tests and irradiation tests of two technologies, HVCMOS AMS and HVCMOS GF, are also given

Radiation-hard active pixel sensors for HL-LHC detector upgrades based on HV-CMOS technology

Luminosity upgrades are discussed for the LHC (HL-LHC) which would make updates to the detectors necessary, requiring in particular new, even more radiation-hard and granular, sensors for the inner detector region. A proposal for the next generation of inner detectors is based on HV-CMOS: a new family of silicon sensors based on commercial high-voltage CMOS technology, which enables the fabrication of part of the pixel electronics inside the silicon substrate itself. The main advantages of this technology with respect to the standard silicon sensor technology are: low material budget, fast charge collection time, high radiation tolerance, low cost and operation at room temperature. A traditional readout chip is still needed to receive and organize the data from the active sensor and to handle high-level functionality such as trigger management. HV-CMOS has been designed to be compatible with both pixel and strip readout. In this paper an overview of HV2FEI4, a HV-CMOS prototype in 180 nm AMS technology, will be given. Preliminary results after neutron and X-ray irradiation are shown

Micro-Electro-Mechanical-Systems (MEMS) and Fluid Flows

The micromachining technology that emerged in the late 1980s can provide micron-sized sensors and actuators. These micro transducers are able to be integrated with signal conditioning and processing circuitry to form micro-electro-mechanical-systems (MEMS) that can perform real-time distributed control. This capability opens up a new territory for flow control research. On the other hand, surface effects dominate the fluid flowing through these miniature mechanical devices because of the large surface-to-volume ratio in micron-scale configurations. We need to reexamine the surface forces in the momentum equation. Owing to their smallness, gas flows experience large Knudsen numbers, and therefore boundary conditions need to be modified. Besides being an enabling technology, MEMS also provide many challenges for fundamental flow-science research