Traditional planning and scheduling techniques have played an important role is system analysis over the last three decades. They provide construction planners with mathematical models to simulate the construction process as an aid in planning and control of complex projects. Although these techniques have been widely used by the construction industry, they possess many limitations. Researchers and practitioners in the construction industry have followed two directions to overcome most of the limitations of current planning techniques. The first direction has been concentrated on the utilization of state-of-the-art Computer Aided Design (CAD) and 3D computer modeling technology. The objective of their work is to interactively generate and visually simulate the construction process on graphics display. The second direction has been influenced by the potential capabilities of Artificial Intelligence (AI) technology to accomplish “Automated Planning”. This group has utilized knowledge-based and expert systems to automatically generate construction plans. The research proposed here presents a geometric-based reasoning system called KNOW-PLAN. The system integrates CAD and 3D computer modeling technology with AI technology to automatically generate and simulate construction plans. The system, therefore, can be classified as a third alternative in approaching the planning problem. The research seeks to utilize geometric data to provide a dynamic sequencing for project planning. The research utilizes object location and object interaction with other objects as the primary source of reasoning for the project plan. The interaction of objects is based on a classification of objects with relation to connection types among them, the zones in which the objects are located, and relationships between the classes with which the objects are associated. To accomplish the objectives of the research, an overall model called the KNOW-PLAN model has been formulated. This model is formulated to demonstrate theoretically the feasibility of implementing such a model in real-life. The implementation effort has been concentrated on the development of the crucial components of the KNOW-PLAN model using advanced computer applications. The implementation at this level is referred to as the KNOW-PLAN prototype system. / Ph. D.

Since metal-oxide-semiconductor (MOS) devices have been adopted into integrated circuits, the endless demands for higher performance and lower power consumption have been a primary challenge and a technology-driver in the semiconductor electronics. The invention of complementary MOS (CMOS) technology in the 1980s, and the introduction of voltage and physical dimension scaling in the 1990s would be good examples to keep up with the everlasting demands. In the 2000s, technology continuously evolves and seeks for more power efficiency ways such as high-k dielectrics, metal gate electrodes, strained substrates, and high mobility channel materials. As a gate dielectric, silicon dioxide (SiO₂), most widely used in CMOS integrated circuits, has many prominent advantages, including a high quality interface (e.g. Dit ~ low 1010 cm-2eV-1), a good thermal stability in contact with silicon (Si), a large energy bandgap and the large energy band offsets in reference to Si, and a high quality dielectric itself. As the thickness of SiO₂ keeps shrinking, however, SiO₂ is facing its physical limitations from the viewpoint of gate dielectric leakage currents and reliability requirements. High-k dielectric materials have attracted extensive attention in the last decade due to their great potential for maintaining further down-scaling in equivalent oxide thickness (EOT) and a low dielectric leakage current. HfO₂ has been considered as one of the most promising candidates because of a high dielectric constant (k ~ 20-25), a large energy band gap (~ 6 eV) and the large band offsets (> 1.5 eV), and a good thermal stability. To enhance carrier mobility, strained substrates and high mobility channel materials have attracted a great deal of attention, thus III-V compound semiconductor substrates have emerged as one of possible candidates, in spite of several technical barriers, being believed as barriers so far. The absence of high quality and thermodynamically stable native oxide, like SiO₂ on Si, has been one such hurdle to implement MOS systems on III-V substrates. However, recently, there have been a number of remarkable improvements on MOS applications on them, inspiring more vigorous research activities. In this research, HfO2-based MOS capacitors and metal-oxidesemiconductor field effect transistors (MOSFETs) with a thin germanium (Ge) interfacial passivation layer (IPL) on III-V compound substrates were investigated. It was found that a thin Ge IPL could effectively passivate the surface of III-V substrate, consequently providing a high quality interface and an excellent gate oxide scalability. N-channel MOSFETs on GaAs, InGaAs, and InP substrates were successfully demonstrated and a minimum EOT of ~ 9 Å from MOS capacitors was achieved. This research has begun with GaAs substrate, and then expanded to InGaAs, InP, InAs, and InSb substrates, which eventually helped to understand the role of a Ge IPL and to guide future research direction. Overall, MOS devices on III-V substrates with an HfO₂ gate dielectric and a Ge IPL have demonstrated feasibility and potential for further investigations. / text

Copper interconnect requires liner materials that function as a diffusion barrier, a seed layer for electroplating, and an adhesion promoting layer. Ruthenium has been considered as a promising liner material, however it has been reported that Ru itself is not an effective Cu diffusion barrier due to its microstructure, which is polycrystalline with columnar grains. The screening study of Ru precursors revealed that all Ru films were polycrystalline with columnar structure, and, due to its strong 3D growth mode, a conformal and ultrathin Ru film was difficult to form, especially on high aspect ratio features. The microstructure of Ru films can be modified by incorporating P. Amorphous Ru(P) films are formed by chemical vapor deposition at 575 K using a single source precursor, cis-RuH₂(P(CH₃)₃)₄, or dual sources, Ru₃(CO)₁₂ and P(CH₃)₃ or P(C6H5)₃ The films contain Ru and P, which are in zero-valent states, and C as an impurity. Phosphorus dominantly affects the film microstructure, and incorporating > 13% P resulted in amorphous Ru(P) films. Metastable Ru(P) remains amorphous after annealing at 675 K for 3 hr, and starts recrystallization at ~775 K. The density of states analysis of the amorphous Ru(P) alloy illustrates metallic character of the films, and hybridization between Ru 4d and P 3p orbitals, which contributes to stabilizing the amorphous structure. Co-dosing P(CH)₃ with Ru₃(CO)₁₂ improves film step coverage, and the most conformal Ru(P) film is obtained with cis-RuH2(P(CH₃)₃)₄; a fully continuous 5 nm Ru(P) film is formed within 1 µm deep, 8:1 aspect ratio trenches. First principles density functional theory calculations illustrate degraded Cu/Ru adhesion by the presence of P at the interface, however, due to the strong Ru-Cu bonds, amorphous Ru(P) forms a stronger interface with Cu than Ta and TaN do. Cu diffusion studies at 575 K suggests improved barrier property of amorphous Ru(P) films over polycrystalline PVD Ru.

Thesis (MScEng)--University of Stellenbosch, 2002 / ENGLISH ABSTRACT: A Representative Unit Cell (RUC) model for flow through two-dimensional porous media is presented and applied to two industrial related problems. The first application is to that of cross-flow in tube banks. Both staggered and square (inline) configurations are investigated and the model results are compared to experimental data. The second application is to flow through a stack in a timber-drying kiln. The RUC model is applied to the anisotropic timber stack ends and the centre part is modelled with a standard duct flow solution. The results of the models applied to a timber stack are compared to experimental data obtained from model tests undertaken in a wind tunnel. The results of the RUC and duct flow models are found to be in excellent agreement with the data of the experimental models. These models may be used to optimize kiln designs. / AFRIKAANSE OPSOMMING: 'n Verteenwoordigende Eenheid Sel (VES) model vir vloei deur twee-dimensionele poreuse media word weergegee en toegepas op twee industriële toepassings. Die eerste toepassing is op dwarsvloei deur banke van buise. Beide gestapelde en inlyn konfigurasies word ondersoek waarvan die model resulte met eksperimentele data vergelyk word. Die tweede toepassing is op vloei deur 'n stapel in 'n hout-droogoond. Die VES model word toegepas op die anisotropiese ente van houtstapels en die middelste seksie word gemodelleer deur 'n standaard kanaalvloei oplossing. Die resultate van die modelle toegepas op n 'houtstapel word vergelyk met eksperimentele data verkry uit model toetse wat in 'n wind-tonnel uitgevoer is. Die VES en kanaalvloei modelle se resultate stem uitstekend ooreen met die data van die eksperimentele modelle. Hierdie modelle kan gebruik word om die ontwerp van droogoonde te optimeer.

This thesis seeks to advance the field of microrobotics by leveraging Bayesian principles and computational tools to design system parameters for information gain and microrobot propulsion. Inspired by living cells, the development of mobile robots on the micron scale (microrobots) promises new capabilities for advancing human health, renewable energy, and environmental sustainability. To help pave the way towards this goal we develop practical recipes for applying computational and analytical tools to physics-based dynamical models of our microrobot experiments. We apply methods of criticism and validation to identify robust models for the motion of magnetic particles at curved interfaces, and identify optimal conditions for propulsion in our model system. We then develop tools for identifying optimal experimental conditions for most efficiently learning model parameters. By studying microscale actuation in depth, we seek to provide a roadmap of how to apply these computational tools to other microrobot design challenges, accelerating the scientific process. In Chapter 1, we focus on the actuation of magnetic particles adsorbed at curved liquid interfaces by external fields, a phenomenon that can be utilized for applications such as droplet mixing or propulsion. To optimize these behaviors, the development and validation of predictive models are essential. We employ Bayesian data analysis as a principled approach to infer model parameters from experimental observations, assess the capabilities of candidate models, and select the most plausible among them. Specifically, we identify and validate a dynamical model which accounts for the effects of gravity and tilting of the particle, a Janus sphere, at the interface. We show how this favored model can predict complex particle trajectories with micron-level accuracy across the range of driving fields considered. Chapter 2 builds on this modeling to develop the optimal properties of a mobile liquid droplet, driven by an adsorbed magnetic particle. This configuration enables the design of responsive emulsions, which can be actuated by a magnetic field. This work develops the properties of such a swimmer and validates our findings with an experimental realization of a ferromagnetic ellipsoid adsorbed onto a stationary water droplet in decane. Accounting for geometric differences, the model developed in the previous chapter is demonstrated to be accurate for this new system. We find that the configuration of the magnetic moment of our ellipsoid prohibits swimming of the assembly, but if it can be modified during fabrication, propulsion is possible. In Chapter 3 we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize another microscale propulsion system, the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only a few automated experiments. This work demonstrates how Bayesian methods can learn the parameters of nonlinear hierarchical models used to describe video microscopy data of active colloids. Finally, the forward-looking perspective in Chapter 4 illustrates how best to leverage these techniques and models to provide a path forward for self-guided microrobots. Existing microrobots based on field-driven particles rely on knowledge of the particle position and the target destination to control particle motion through fluid environments. These external control strategies are challenged by limited information and global actuation, where a common field directs multiple robots with unknown positions. We discuss how time-varying magnetic fields can be used to encode self-guided behaviors of magnetic particles conditioned on local environmental cues. Programming these behaviors is framed as a design problem: we seek to identify the design variables (e.g. particle shape, magnetization, elasticity, stimuli-response) that achieve the desired performance in a given environment. We discuss strategies for accelerating the design process using the methods developed in this thesis—including automated experiments, computational models, and statistical inference—as well as other approaches such as machine learning. Based on the current understanding of field-driven particle dynamics and existing capabilities for particle fabrication and actuation, we argue that self-guided microrobots with potentially transformative capabilities are close at hand. This research offers a unique contribution by demonstrating the practicality and efficiency of Bayesian computational methods in microrobot design, and provides a template that is applicable anywhere that physics-based dynamical models can be used to guide experimental effort.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Call number: LD2668 .T4 1979 L64 / Master of Science

Submitted in complete fulfillment of the requirements for the Degree of Doctor of Technology: Biotechnology, Durban University of Technology, Durban, South Africa. 2014. / The global demand for green technology has created a need to search for microbes that can play an active role in advancing a greener and cleaner future. Microbial enzymes are nature’s keys to life and their efficiency, specificity and environmental-friendliness has lead to their increased use in industrial processes. Thermomyces lanuginosus is a thermophilic fungus that can degrade plant biomass and produces a variety of enzymes that have industrial application. The fungus T. lanuginosus SSBP has been reported in literature to produce the highest level of xylanase among other Thermomyces strains and some of its enzyme s viz., amylase and lipase are already being used. Because of this ability, it has been identified as one of the organisms that can have various industrial applications. Although a few proteins from this fungus have been cloned and used commercially, the vast majority are still unknown. In order to identify new protein candidates and understand their biochemical interactions, the T. lanuginosus genome (DNA) and the transcriptome (mRNA) were sequenced using 454 Roche and Solexa sequencing platforms. Genome and transcriptome data was assembled using Newbler software forming a genome size of 23.3 Mb contained 30 scaffolds. Protein prediction identified 5105 candidates as protein-coding genes and these gene models were supported by expressed sequence tag and transcriptomic data. The annotated data was assembled into metabolic pathways in order to identify functional pathways and validate the accuracy of the annotation process. T. lanuginosus is usually found in composting plant material thus protein related to plant hydrolysis were analysed. The total number of plant biomass-degrading and related proteins that fall into the carbohydrate-active enzyme (CAZy) family was 224. Most of these proteins were similar to proteins found in other filamentous fungi. Surprisingly, T. lanuginosus contained a single gene coding for xylanase which hydrolyses xylan although this organism is well known for being among the highest producers of this enzyme. An important subset of the above group of proteins is the cellulose degrading-proteins as this can be used in biofuel production. Eight candidates belonging to this group were identified, making this fungus significant in the biofuels. Among the eight cellulase candidates, phylogenetic analysis revealed that three of them were closely related to Trichoderma reesei, a well known industrial cellulase-producer. Utilization of cellulase-related compounds was validated by phenotypic microarray experiments, with cellobiose having inducing biomass in T. lanuginosus. Proteins that are involved in high temperature survival are vital for the survival. of this thermophilic fungus. Interestingly, T. lanuginosus contains 19 heat shocking proteins which are responsible for thermostability. Another adaptation identified in this fungus is the accumulation of trehalose to combat heat stress. Furthermore, T. lanuginosus contains the highest reported number methyltransferases, which have been linked to producing thermostable proteins and higher energy production. Also because of this organism’s ability to grow on composting environments, the assimilation and ability to produce biomass on different carbon sources were analysed using phenotypic microarray technique. The results showed that xylose was the best compound to induce biomass followed by trehalose, maltose and maltotriose. The genomic sequencing of this fungus has provided valuable information that can be used for various biotechnological applications, as well as providing greater insights into its thermostability. Understanding the metabolic pathways involved may allow for manipulation to increase production of these enzymes or cloning into other hosts. This can have an impact in the field of biofuel production and other plant biomass-related processes.

Thesis (M.Tech.: Biotechnology)-Dept. of Biotechnology, Durban University of Technology, 2007 vi, 92 leaves / Interest in xylanases from different microbial sources has increased markedly in the past decade, in part because of the application of these enzymes in a number of industries, the main area being the pulp and paper industry. While conventional methods will continue to be applied to enzyme production from micro-organisms, the application of recombinant DNA techniques is beginning to reveal important information on the molecular basis and this knowledge is now being applied both in the laboratory and commercially. In this study, a directed evolution strategy was used to select an enzyme variant with high thermostability. This study describes the use of error-prone PCR to modify the xylanase gene from Thermomyces lanuginosus DSM 5826, rendering it tolerant to temperatures in excess of 80°C. Mutagenesis comprised of different concentrations of nucleotides and manganese ions. The variants were generated in iterative steps and subsequent screening for the best mutant was evaluated using RBB-xylan agar plates. The optimum temperature for the activity of xylanases amongst all the enzyme variants was 72°C whilst the temperature optimum for the wild type enzyme was 70°C. Long term thermostability screening was therefore carried out at 80°C and 90°C. The screen yielded a variant which had a 38% improvement in thermostability compared to the wild type xylanase from pX3 (the unmutated gene). Successive rounds of error-prone PCR were carried out and in each round the progeny mutant displayed better thermostability than the parent. The most stable variant exhibited 71% residual activity after 90 minutes at 80˚C. Sequence analysis revealed four single amino acid residue changes that possibly enhanced their thermostabilities. This in vitro enzyme evolution technique therefore served as an effective tool in improving the thermostable property of this xylanase which is an important requirement in industry and has considerable potential for many industrial applications.