An Integrated IGBT Active Gate Driver with Fast Feed-Forward Variable Current

The Insulated-Gate Bipolar Transistor (IGBT) is a hybrid of bipolar and MOSFET transistors. As a consequence, IGBTs can handle higher current typical of bipolar transistors with the ease of control typical of MOSFETs. These characteristics make IGBTs desirable for high power Switch Mode Power Supplies (SMPS). In high power systems such as these, devices must be very reliable, as device failures may result in safety hazards such as fires in addition to the failure of the system. Conventional Gate Driver (CGD) circuits typically design for reliability in these systems by including a resistor between the gate driver and gate of the IGBT. This slows the switching waveforms, reducing stress on the IGBT while sacrificing efficiency. This solution is suboptimal, however, and as such Active Gate Drivers (AGD) have been designed to control voltage and current slopes through the IGBT by modulating the gate signal. AGD circuits found on the market today consist of a combination of an CGD with external components to implement the variable current necessary for protection. This requires a large amount of area on a Printed Circuit Board (PCB), and thus can be costly. Therefore, it can be desirable to integrate the AGD functionality into an on-chip system. In this thesis, an AGD is designed, fabricated and analyzed to show that IGBT gate voltage can be controlled in a manner capable of reducing overvoltage, as well as slowed when desired using an on-chip system. The current provided by this gate driver is controlled by feedback signals indicating the switching state of the device, as well as input bits that determine total output current

Executive attention, task selection and attention-based learning in a neurally controlled simulated robot

We describe the design and implementation of an integrated neural architecture, modelled on human executive attention, which is used to control both automatic (reactive) and willed action selection in a simulated robot. The model, based upon Norman and Shallice's supervisory attention system, incorporates important features of human attentional control: selection of an intended task over a more salient automatic task; priming of future tasks that are anticipated; and appropriate levels of persistence of focus of attention. Recognising that attention-based learning, mediated by the limbic system, and the hippocampus in particular, plays an important role in adaptive learning, we extend the Norman and Shallice model, introducing an intrinsic, attention-based learning mechanism that enhances the automaticity of willed actions and reduces future need for attentional effort. These enhanced features support a new level of attentional autonomy in the operation of the simulated robot. Some properties of the model are explored using lesion studies, leading to the identification of a correspondence between the behavioural pathologies of the simulated robot and those seen in human patients suffering dysfunction of executive attention. We discuss briefly the question of how executive attention may have arisen due to selective pressure

Genetic Architecture of Soybean Yield and Agronomic Traits

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding

Optimising UK urban road verge contributions to biodiversity and ecosystem services with cost-effective management

Urban road verges can contain significant biodiversity, contribute to structural connectivity between other urban greenspaces, and due to their proximity to road traffic are well placed to provide ecosystem services. Using the UK as a case study we review and critically evaluate a broad range of evidence to assess how this considerable potential can be enhanced despite financial, contractual and public opinion constraints. Reduced mowing frequency and other alterations would enhance biodiversity, aesthetics and pollination services, whilst delivering costs savings and potentially being publically acceptable. Retaining mature trees and planting additional ones is favourable to residents and would enhance biodiversity, pollution and climate regulation, carbon storage, and stormwater management. Optimising these services requires improved selection of tree species, and creating a more diverse tree stock. Due to establishment costs additional tree planting and maintenance could benefit from payment for ecosystem service schemes. Verges could also provide areas for cultivation of biofuels and possibly food production. Maximising the contribution of verges to urban biodiversity and ecosystem services is economical and becoming an increasingly urgent priority as the road network expands and other urban greenspace is lost, requiring enhancement of existing greenspace to facilitate sustainable urban development

Genetic Architecture of Soybean Yield and Agronomic Traits

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding

Pool boiling of Novec 7300 and DI water on nano-textured heater covered with supersonically-blown or electrospun polymer nanofibers

In this work we study pool boiling of Novec 7300 and DI water on bare copper surface and copper surface covered with supersonically-blown or electrospun polymer nanofibers. In distinction from the previous works nanofibers were not metal-plated. The elimination of the electroplating makes nano-texturing process extremely simple and applicable to a wide variety of surfaces. On the other hand, it comes with the price of a lower heat removal rate compared to that on metal-plated nanofibers, albeit the present experiments revealed that the reduction is not that drastic as it would be expected. It is also demonstrated that the supersonically-blown polymer nanofibers also outperformed the electrospun nanofiber-coated surface. Supersonically-blown nanofibers provide a large number of nucleation sites than electrospun nanofibers or bare copper surface, and thus, facilitate nucleate boiling much stronger. The ultrafine supersonically-blown polymer nanofibers are very robust and did not delaminate from the heater surface either in Novec 7300 or DI water after prolonged vigorous boiling process. Overall, the enhancement of heat removal due to the ultrafine supersonically-blown polymer nanofibers on the heater surface in Novec 7300 is more significant than in DI water, which is associated with the smaller bubble size in the former case