Thesis (Ph. D.)--Illinois State University, 1978. / Title from title page screen, viewed Jan. 25, 2005. Dissertation Committee: John McCarthy (chair), Vernon A. Adams, Ronald S. Halinski, James A. Hallam, J.H. McGrath. Includes bibliographical references (leaves 173-177) and abstract. Also available in print.

Magnetic nanoparticles (NPs) with sizes ranging from 2 to 20 nm in diameter represent an important class of artificial nanostructured materials, since the NP size is comparable to the size of a magnetic domain. They have potential applications in data storage, catalysis, permanent magnetic nanocomposites, and biomedicine. To begin with, a brief overview on the background of Fe-based bimetallic NPs and their applications for data-storage and catalysis was presented in Chapter 1. In Chapter 2, L10-ordered FePt NPs with high coercivity were directly prepared from a novel bimetallic acetylenic alternating copolymer P3 by a one-step pyrolysis method without post-thermal annealing. The chemical ordering, morphology and magnetic properties were studied. Magnetic measurements showed that a record coercivity of 3.6 T (1 T = 10 kOe) was obtained in FePt NPs. By comparison of the resultant FePt NPs synthesized under Ar and Ar/H2, the characterization proved that the incorporation of H2 would affect the nucleation and promote the growth of FePt NPs. The L10 FePt NPs were also successfully patterned on Si substrate by nanoimprinting lihthography (NIL). The highly ordered ferromagnetic arrays on a desired substrate for bit-patterned media (BPM) were studied and promised bright prospects for the progress of data-storage. Furthermore, we also reported a new FePt-containing metallopolymer P4 as the single-source precursor for metal alloy NPs synthesis, where the metal fractions were on the side chain and the ratio could be easily controlled. This polymer was synthesized from random copolymer poly(styrene-4-ethynylstyrene) PES-PS and bimetallic precursor TPy-FePt ([Pt(4’-ferrocenyl-(N^N^N))Cl]Cl) by Sonogashira coupling reaction. After pyrolysis of P4, the stoichiometry of Fe and Pt atoms in the synthesized NPs (NPs) is nearly close to 1:1, which is more precise than using TPy-FePt as precursor. Polymer P4 was also more favorable for patterning by high throughout NIL as compared to TPy-FePt. Ferromagnetic nanolines, potentially as bit-patterned magnetic recording media, were successfully fabricated from P4 and fully characterized. In Chapter 3, a novel organometallic compound TPy-FePd-1 [4’-ferrocenyl-(N^N^N)PdOCOCH3] was synthesized and structurally characterized, whose crystal structure showed a coplanar Pd center and Pd-Pd distance (3.17 Å). Two metals Fe and Pd were evenly embedded in the molecular dimension and remained tightly coupled between each other benefiting to the metalmetal (Pd-Pd) and ligand ππ stacking interactions, all of which made it facilitate the nucleation without sintering during preparing the FePd NPs. Ferromagnetic FePd NPs of ca. 16.2 nm in diameter were synthesized by one-pot pyrolysis of the single-source precursor TPy-FePd-1 under getter gas with metal-ion reduction and minimal nanoparticle coalescence, which have a nearly equal atomic ratio (Fe/Pd = 49/51) and exhibited coercivity of 4.9 kOe at 300 K. By imprinting the mixed chloroform solution of TPy-FePd-1 and polystyrene (PS) on Si, reproducible patterning of nanochains was formed due to the excellent self-assembly properties and the incompatibility between TPy-FePd-1 and PS under the slow evaporation of the solvents. The FePd nanochains with average length of ca. 260 nm were evenly dispersed around the PS nanosphere by self-assembly of TPy-FePd-1. In addition, the orientation of the FePd nanochains could also be controlled by tuning the morphology of PS, and the length was shorter in confined space of PS. Orgnic skeleton in TPy-FePd-1 and PS were carbonized and removed by pyrolysis under Ar/H2 (5 wt%) and only magnetic FePd alloy nanochains with domain structure were left. Besides, a bimetallic complex TPy-FePd-2 was prepared and used as a single-source precursor to synthesize ferromagnetic FePd NPs by one-pot pyrolysis. The resultant FePd NPs have a mean size of 19.8 nm and show the coercivity of 1.02 kOe. In addition, the functional group (-NCMe) in TPy-FePd-2 was easily substituted by a pyridyl group. A random copolymer PS-P4VP was used to coordinate with TPy-FePd-2, and the as-synthesized polymer made the metal fraction disperse evenly along the flexible chain. Fabrication of FePd NPs from the polymers was also investigated, and the size could be easily controlled by tuning the metal fraction in polymer. FePd NPs with the mean size of 10.9, 14.2 and 17.9 nm were prepared from the metallopolymer with 5 wt%, 10 wt% and 20wt% of metal fractions, respectively. In Chapter 4, molybdenum disulfide (MoS2) monolayers decorated with ferromagnetic FeCo NPs on the edges were synthesized through a one-step pyrolysis of precursor molecules in an argon atmosphere. The FeCo precursor was spin coated on the MoS2 monolayer grown on Si/SiO2 substrate. Highly-ordered body-centered cubic (bcc) FeCo NPs were revealed under optimized pyrolysis conditions, possessing coercivity up to 1000 Oe at room temperature. The FeCo NPs were well-positioned along the edge sites of MoS2 monolayers. The vibration modes of Mo and S atoms were confined after FeCo NPs decoration, as characterized by Raman shift spectroscopy. These MoS2 monolayers decorated with ferromagnetic FeCo NPs can be used for novel catalytic materials with magnetic recycling capabilities. The sizes of NPs grown on MoS2 monolayers are more uniform than from other preparation routines. Finally, the optimized pyrolysis temperature and conditions provide receipts for decorating related noble catalytic materials. Finally, Chapters 5 and 6 present the concluding remarks and the experimental details of the work described in Chapters 2-4.

Diss. Uppsala : Univ., 2003.

Thesis (Ph. D.)--University of Washington, 1992. / Vita. Includes bibliographical references (leaves [150]-155).

This investigation was undertaken to develop plastic design aids to be used in the direct design of optimum frames. It uses the concept of minimum weight of plastically designed steel frames, and the concept of linear programming to obtain general solutions. Among the special characteristics of this study are: A. The integration of both gravity and combined loading conditions into one linear programming problem. B. The application of the revised simplex method to the dual of a parametric original problem. C. The application of A and B above in the development of design aids for the optimum design of symmetrical single-bay, single-story portal frame. Specifically, design graphs for different height to span ratios and different vertical load to lateral load ratios are developed. The use of these graphs does not require the knowledge of linear programming or computers on the part of the designer.

As in many other fields, biology is faced with enormous amounts ofdata that contains valuable information that is yet to be extracted. The field of proteomics, the study of proteins, has the luxury of having large repositories containing data from tandem mass-spectrometry experiments, readily accessible for everyone who is interested. At the same time, there is still a lot to discover about proteins as the main actors in cell processes and cell signaling. In this thesis, we explore several methods to extract more information from the available data using methods from statistics and machine learning. In particular, we introduce MaRaCluster, a new method for clustering mass spectra on large-scale datasets. This method uses statistical methods to assess similarity between mass spectra, followed by the conservative complete-linkage clustering algorithm.The combination of these two resulted in up to 40% more peptide identifications on its consensus spectra compared to the state of the art method. Second, we attempt to clarify and promote protein-level false discovery rates (FDRs). Frequently, studies fail to report protein-level FDRs even though the proteins are actually the entities of interest. We provided a framework in which to discuss protein-level FDRs in a systematic manner to open up the discussion and take away potential hesitance. We also benchmarked some scalable protein inference methods and included the best one in the Percolator package. Furthermore, we added functionality to the Percolator package to accommodate the analysis of studies in which many runs are aggregated. This reduced the run time for a recent study regarding a draft human proteome from almost a full day to just 10 minutes on a commodity computer, resulting in a list of proteins together with their corresponding protein-level FDRs. / <p>QC 20160412</p>

Indiana University-Purdue University Indianapolis (IUPUI) / Asynchronous JavaScript and XML (AJAX) is the primary method for enabling asynchronous communication over the Web. Although AJAX is providing warranted real-time capabilities to the Web, it requires unconventional programming methods at the expense of extensive resource usage. WebSockets, which is an emerging protocol, has the potential to address many challenges with implementing asynchronous communication over the Web. There, however, has been no in-depth study that quantitatively compares AJAX and WebSockets. This thesis therefore provides two contributions to Web development. First, it provides an experience report for adding real-time monitoring support over the Web to the Open-source Architecture of Software Instrumentation of Systems(OASIS), which is open-source real-time instrumentation middleware for distributed real-time and embedded (DRE) systems. Secondly, it quantitatively compares using AJAX and WebSockets to stream collected instrumentation data over the Web in real-time. Results from quantitative comparison between WebSockets and AJAX show that a WebSockets server consumes 50% less network bandwidth than an AJAX server; a WebSockets client consumes memory at constant rate, not at an increasing rate; and WebSockets can send up to 215.44% more data samples when consuming the same amount network bandwidth as AJAX.