Physics and technologies of silicon LDMOSFET for radio frequency applications

This thesis is devoted to the investigation of devices and technologies of Lateral Double-Diffused- Metal-Oxide-Semiconductor-Field-Effect-Transistor for Radio Frequency (RP) applications. Theoretical analysis and extensive 2-D process and device simulation results are presented. Theoretical analysis and simulations are carried out on RESURF LDMOS in both bulk and SOI substrate in terms of breakdown characteristics, transconductance, on resistance and CV characteristics. Quasi-saturation is a common phenomenon in DMOS devices. In this work, the dependence of quasi-saturation current on device physical and geometrical parameters is investigated in SOI RP LDMOS. Physical insight is gained into quasi-saturation on SOI RP LDMOS with different top silicon thickness and the same drift dose. It reveals that the difference in thick and thin film SOI lies in the different potential drop in the drift region. The influence of RESURF effect on quasi-saturation is also presented. It is shown that quasi-saturation current level can be affected by RESURF due to its influence on the drift dose. The mechanism of self-heating is presented and the influence of top silicon thickness, buried oxide thickness, voltage bias is studied through simulations. The change of peak temperature and its location with bias is due to the shift of electric field with voltage bias. A back-etch structure and fabrication process have been proposed to achieve a superior thermal performance. The negative differential conductance is not present in the non-isothermal IV curves. The temperature rise in the back-etch structure is less than 114 of that in the bulk structure. An RP LDMOS with a step drift doping profile on SIMOX substrate is evaluated. The fabrication process for the drift formation is proposed. The presented results demonstrate that step drift device has higher breakdown voltage than the conventional uniformly doped (UD) device, which provides the possibility to integrate LDMOS with low voltage CMOS for 28V base station application. This structure also has the advantage of suppressed kink effect due to the reduced electric field within the drift region. The step drift structure also features lower capacitance, improved drain current saturation behaviour and reduced self-heating at class AB bias point. For the first time, a novel sandwich structure for lateral RF MOSFET has been analysed based on silicon-on-nothing (SON) technology. The influence of device parameters on BV, CV and thermal performance has been investigated. Partial SON structure is found preferable in terms of heat conduct ability. Comparison on the electrical and thermal performance is made between SON LDMOSFET and conventional SOI alternative with BV of 40V. It is found that SON structure shows improvement in output capacitance and substrate loss. However, the temperature rise in SON device is higher compared to SOI alternative. The performance of the proposed sandwich SON structure has also been investigated in 28V base station applications, which requires breakdown voltage of 80V

Promoting the survival, migration and integration of Schwann cells by over-expression of polysialic acid

PhDThe poor survival and migration of transplanted Schwann cells (SCs) are major drawbacks for their clinical application in cell therapy for neurotrauma. To overcome such drawbacks we genetically modified SCs to over-express polysialic acid (PSA) by lentiviral vectors-mediated expression of polysialyltransferase ST8SiaIV (PST), to study whether over-expression of PSA could enhance their survival, migration, and integration when transplanted into the spinal cord. It was found that more PSA-expressing SCs (PST/SCs) survived than GFP-expressing SCs (GFP/SCs) after transplantation. In vitro expression of PSA on SCs can partially rescue SCs from cell death induced by serum and growth factor withdrawal. In addition, we found high concentration of ATP (>3 mM) could induce SCs death via P2X7 receptor (P2X7R) activation. Blockade of P2X7Rs with an antagonist completely abolished ATP induced SCs death in vitro and also enhance the survival of grafted SCs in vivo. Interestingly, expression of PSA on SCs was found to partially protect SCs from ATP induced cell death in vitro. PSA expression on SCs did not enhance the motility of transplanted SCs in intact spinal cord. However, in a spinal cord crush injury model PST/SCs transplanted 2.5 mm caudal to the lesion site showed that more cells migrated toward the injury site compared with that of GFP/SCs. Induced expression of PSA in spinal cord further facilitated the infiltration of PST/SCs into the lesion cavity. PST/SCs were also shown to intermingle with the host spinal cells while GFP/SCs formed boundaries with the host tissue. This was confirmed by an in vitro confrontation assay. Furthermore, PST/SCs induced much less expression of GFAP and CSPGs in the surrounding host tissues than GFP/SCs, indicating that expression of PSA on SCs do not cause significant stress response of astrocytes. These results demonstrate that over-expression of PSA on SCs significantly changes their biological properties and makes them more feasible for cell therapy after neurotrauma.Nathalie Rose Barr PhD Studentship NRB094. International Spinal Research Trus

Fast, Robust, and Versatile Event Detection through HMM Belief State Gradient Measures

Event detection is a critical feature in data-driven systems as it assists with the identification of nominal and anomalous behavior. Event detection is increasingly relevant in robotics as robots operate with greater autonomy in increasingly unstructured environments. In this work, we present an accurate, robust, fast, and versatile measure for skill and anomaly identification. A theoretical proof establishes the link between the derivative of the log-likelihood of the HMM filtered belief state and the latest emission probabilities. The key insight is the inverse relationship in which gradient analysis is used for skill and anomaly identification. Our measure showed better performance across all metrics than related state-of-the art works. The result is broadly applicable to domains that use HMMs for event detection.Comment: 8 pages, 7 figures, double col, ieee conference forma

Recovering from External Disturbances in Online Manipulation through State-Dependent Revertive Recovery Policies

Robots are increasingly entering uncertain and unstructured environments. Within these, robots are bound to face unexpected external disturbances like accidental human or tool collisions. Robots must develop the capacity to respond to unexpected events. That is not only identifying the sudden anomaly, but also deciding how to handle it. In this work, we contribute a recovery policy that allows a robot to recovery from various anomalous scenarios across different tasks and conditions in a consistent and robust fashion. The system organizes tasks as a sequence of nodes composed of internal modules such as motion generation and introspection. When an introspection module flags an anomaly, the recovery strategy is triggered and reverts the task execution by selecting a target node as a function of a state dependency chart. The new skill allows the robot to overcome the effects of the external disturbance and conclude the task. Our system recovers from accidental human and tool collisions in a number of tasks. Of particular importance is the fact that we test the robustness of the recovery system by triggering anomalies at each node in the task graph showing robust recovery everywhere in the task. We also trigger multiple and repeated anomalies at each of the nodes of the task showing that the recovery system can consistently recover anywhere in the presence of strong and pervasive anomalous conditions. Robust recovery systems will be key enablers for long-term autonomy in robot systems. Supplemental info including code, data, graphs, and result analysis can be found at [1].Comment: 8 pages, 8 figures, 1 tabl

The localization of single pulse in VLBI observation

In our previous work, we propose a cross spectrum based method to extract single pulse signals from RFI contaminated data, which is originated from geodetic VLBI postprocessing. This method fully utilizes fringe phase information of the cross spectrum and hence maximizes signal power, however the localization was not discussed in that work yet. As the continuation of that work, in this paper, we further study how to localize single pulses using astrometric solving method. Assuming that the burst is a point source, we derive the burst position by solving a set of linear equations given the relation between residual delay and offset to a priori position. We find that the single pulse localization results given by both astrometric solving and radio imaging are consistent within 3 sigma level. Therefore we claim that it is possible to derive the position of a single pulse with reasonable precision based on only 3 or even 2 baselines with 4 milliseconds integration. The combination of cross spectrum based detection and the localization proposed in this work then provide a thorough solution for searching single pulse in VLBI observation. According to our calculation, our pipeline gives comparable accuracy as radio imaging pipeline. Moreover, the computational cost of our pipeline is much smaller, which makes it more practical for FRB search in regular VLBI observation. The pipeline is now publicly available and we name it as "VOLKS", which is the acronym of "VLBI Observation for frb Localization Keen Searcher".Comment: 11 pages, 4 figures, 3 tables, accepted for publication in A

Online Robot Introspection via Wrench-based Action Grammars

Robotic failure is all too common in unstructured robot tasks. Despite well-designed controllers, robots often fail due to unexpected events. How do robots measure unexpected events? Many do not. Most robots are driven by the sense-plan act paradigm, however more recently robots are undergoing a sense-plan-act-verify paradigm. In this work, we present a principled methodology to bootstrap online robot introspection for contact tasks. In effect, we are trying to enable the robot to answer the question: what did I do? Is my behavior as expected or not? To this end, we analyze noisy wrench data and postulate that the latter inherently contains patterns that can be effectively represented by a vocabulary. The vocabulary is generated by segmenting and encoding the data. When the wrench information represents a sequence of sub-tasks, we can think of the vocabulary forming a sentence (set of words with grammar rules) for a given sub-task; allowing the latter to be uniquely represented. The grammar, which can also include unexpected events, was classified in offline and online scenarios as well as for simulated and real robot experiments. Multiclass Support Vector Machines (SVMs) were used offline, while online probabilistic SVMs were are used to give temporal confidence to the introspection result. The contribution of our work is the presentation of a generalizable online semantic scheme that enables a robot to understand its high-level state whether nominal or abnormal. It is shown to work in offline and online scenarios for a particularly challenging contact task: snap assemblies. We perform the snap assembly in one-arm simulated and real one-arm experiments and a simulated two-arm experiment. This verification mechanism can be used by high-level planners or reasoning systems to enable intelligent failure recovery or determine the next most optima manipulation skill to be used.Comment: arXiv admin note: substantial text overlap with arXiv:1609.0494