Alkali treatments of lyocell in continuous processes. I. Effects of temperature and alkali concentration on the treatments of plain woven fabrics

Experiments were conducted that were designed to study the influence of various process parameters on the properties of lyocell fabrics treated with NaOH solutions in a continuous process. The process parameters of interest were the fabric type (plain, twill, or sateen woven), alkali concentration, tension on the fabric, temperature, and duration of the treatment. In this article, we present the first set of results from these experiments and examine the effect of NaOH concentration, temperature, and tension in the continuous alkali treatments of plain woven lyocell fabrics. Alkali treatments caused fiber swelling in the fabrics to extents governed by the alkali concentration and temperature of the treatment liquors. Fiber swelling caused fabric shrinkage, which resulted in changes to the fabric macroscopic structure and properties. Changes were observed in the flexural rigidity, water retention, crease recovery, strength, and abrasion resistance of the fabrics to extents governed predominantly by swelling‐related changes to the fabric structure. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Speciation and localization of arsenic in white and brown rice grains

Synchrotron-based X-ray fluorescence (S-XRF) was utilized to locate arsenic (As) in polished (white) and unpolished (brown) rice grains from the United States, China, and Bangladesh. In white rice As was generally dispersed throughout the grain, the bulk of which constitutes the endosperm. In brown rice As was found to be preferentially localized at the surface, in the region corresponding to the pericarp and aleurone layer. Copper, iron, manganese, and zinc localization followed that of arsenic in brown rice, while the location for cadmium and nickel was distinctly different, showing relatively even distribution throughout the endosperm. The localization of As in the outer grain of brown rice was confirmed by laser ablation ICP-MS. Arsenic speciation of all grains using spatially resolved X-ray absorption near edge structure (micro-XANES) and bulk extraction followed by anion exchange HPLC-ICP-MS revealed the presence of mainly inorganic As and dimethylarsinic acid (DMA). However, the two techniques indicated different proportions of inorganic:organic As species. A wider survey of whole grain speciation of white (n=39) and brown (n=45) rice samples from numerous sources (field collected, supermarket survey, and pot trials) showed that brown rice had a higher proportion of inorganic arsenic present than white rice. Furthermore, the percentage of DMA present in the grain increased along with total grain arsenic.     

Action- and workflow-driven augmented reality for computer-aided medical procedures.

During the past three years, we've tried to develop integrated AR solutions in the context of minimally invasive surgery. We have therefore focused on four main issues: recovery and monitoring of surgical workflow, integrating preoperative and intraoperative anatomic and functional data, improving visual perception in a mixed environment, and developing new user interaction paradigms for taking full advantage of the virtual data, while overlaid onto the real scene. Each of these issues is the subject of many existing and future publications. Here, we provide a brief overview of our activities and current results in regard to each of these issues.     

Adaptive processing of historical spatial range queries in peer-to-peer sensor networks

We investigate the problem of processing historical queries on a sensor network. Since data is considered to have been already collected at the sensor nodes, the main issue is exploring the spatial component of the query in order to minimize its cost represented by the energy consumption. We assume queries can be issued at any network node, i.e., there is no central base station and all nodes have only local knowledge of the network. On the one hand, a globally optimum query processing plan is desirable but its construction is not possible due to the lack of global knowledge of the network. On the other hand, while a simple network flooding is feasible, it is not a practical choice from a cost perspective. To address this problem we propose a two-phase query processing strategy, where in the first phase a path from the query originator to the query region is found and in the second phase the query is processed within the query region itself. This strategy is supported by analytical models that are used to dynamically select the best processing strategy depending on the query specifics. Our extensive analytical and experimental results show that our analytical models are accurate and that the two-phase strategy is better suited for small to medium sized queries, being up to 10 times more cost effective than a typical network flooding. In addition, the dynamic selection of a query processing technique proved itself capable of always delivering at least as good performance as the most energy efficient strategy for all query sizes. Research supported in part by NSERC Canada.     

Amphiphilic network as nanoreactor for enzymes in organic solvents

Enzymes are powerful biocatalysts that work naturally in water but are also active in organic solvents. Here, we present a nanophase-separated amphiphilic network, where an enzyme is entrapped into its hydrophilic domains. A substrate that diffuses into the other, hydrophobic, phase of such a network can access the biocatalyst via the extremely large interface. Entrapped horseradish peroxidase and chloroperoxidase showed dramatically increased activity and operational stability compared to the native enzymes.     

Metallized Organoclays as New Intermediates for Aqueous Nanohybrid Dispersions,Nanohybrid Catalysts and Antimicrobial Polymer Hybrid Nanocomposites

Summary: The chemical metallization of aqueous bentonite dispersions afforded stable aqueous hybrid nanoparticle dispersions containing simultaneously dispersed sodium bentonite nanoplatelets together with bentonite supported silver, palladium, or copper nanoparticles with average metal nanoparticle diameters varying between 14 and 40 nm. Such aqueous bentonite/metal hybrid nanoparticle dispersions were blended with cationic PMMA latex to produce PMMA hybrid nanocomposites containing exfoliated polymer‐grafted organoclay together with bentonite supported metal nanoparticles. This dispersion blend formation was investigated with respect to the role of nanostructure formation and mechanical properties. Palladium/bentonite hybrid dispersions were used as catalysts for hydrogenation reactions and the electroless plating of copper. In contrast to the conventional organoclay nanocomposites, the PMMA hybrid nanocomposites, containing simultaneously dispersed organoclay nanoplatelets together with organoclay supported silver nanoparticles, exhibited high antimicrobial activity against the ubiquitous bacterium Staphylococcus aureus, even at low silver content.

Preparation of a polymer hybrid nanocomposite.     

Microstructure and Elastic Constants of Transition Metal Dichalcogenide Monolayers from Friction and Shear Force Microscopy

Optical and electrical properties of 2D transition metal dichalcogenides (TMDCs) grown by chemical vapor deposition (CVD) are strongly determined by their microstructure. Consequently, the visualization of spatial structural variations is of paramount importance for future applications. This study demonstrates how grain boundaries, crystal orientation, and strain fields can unambiguously be identified with combined lateral force microscopy and transverse shear microscopy (TSM) for CVD‐grown tungsten disulfide (WS₂) monolayers, on length scales that are relevant for optoelectronic applications. Further, angle‐dependent TSM measurements enable the fourth‐order elastic constants of monolayer WS₂ to be acquired experimentally. The results facilitate high‐throughput and nondestructive microstructure visualization of monolayer TMDCs and insights into their elastic properties, thus providing an accessible tool to support the development of advanced optoelectronic devices based on such 2D semiconductors.     

Virtual lifeline: Multimodal sensor data fusion for robust navigation in unknown environments

We present a novel, multimodal indoor navigation technique that combines pedestrian dead reckoning (PDR) with relative position information from wireless sensor nodes. It is motivated by emergency response scenarios where no fixed or pre-deployed global positioning infrastructure is available and where typical motion patterns defeat standard PDR systems. We use RF and ultrasound beacons to periodically re-align the PDR system and reduce the impact of incremental error accumulation. Unlike previous work on multimodal positioning, we allow the beacons to be dynamically deployed (dropped by the user) at previously unknown locations. A key contribution of this paper is to show that despite the fact that the beacon locations are not known (in terms of absolute coordinates), they significantly improve the performance of the system. This effect is especially relevant when a user re-traces (parts of) the path he or she had previously travelled or lingers and moves around in an irregular pattern at single locations for extended periods of time. Both situations are common and relevant for emergency response scenarios. We describe the system architecture, the fusion algorithms and provide an in depth evaluation in a large scale, realistic experiment.