High-temperature Na2SO4 interaction with air plasma sprayed Yb2Si2O7 + Si EBC system: Topcoat behavior

The high-temperature interaction between ~2.5 mg/cm² of Na₂SO₄ and an atmospheric plasma sprayed (APS) Yb₂Si₂O₇ topcoat–Si bond coat system on SiC CMC substrates was studied for times up to 240 h at 1000°C–1316°C in a 0.1% SO₂–O₂ gaseous environment. Yb₂Si₂O₇ reacted with Na₂SO₄ to form Yb₂SiO₅ and an intergranular amorphous Na-silicate phase. Below 1200°C, the reaction was sluggish, needing days to cause morphological changes to the “splat microstructure” associated with APS coatings. The reaction was rapid at 1200°C and above, needing only a few hours for the entire topcoat to transform into a granulated microstructure consisting of Yb₂SiO₅ and Yb₂Si₂O₇ phases. Na₂SO₄ deposits infiltrated the Yb₂Si₂O₇ topcoat and transformed into an amorphous Na-silicate in less than 1 h at all exposure temperatures. Quantitative assessment of the Yb₂SiO₅ area fraction in the topcoat showed a linear decrease over time at 1316°C, attributed to reaction with the SiO₂ thermally grown oxide (TGO) formed on the Si bond coat and rapid transport through the interpenetrating amorphous Na-silicate grain boundary phase. It was predicted that nearly 2 weeks is needed for complete removal of Yb₂SiO₅ from the topcoat at 1316°C for a single applied loading of Na₂SO₄.     

Na2SO4 deposit-induced hot corrosion of SiC fibers relevant for SiC CMCs

Hi Nicalon, Hi Nicalon S, Sylramic, and Sylramic iBN SiC fibers were exposed to ~60 μg/cm² of Na₂SO₄ in a 0.1% SO₂/O₂ gaseous environment for times between 0.75 and 24 h at 1000°C. After exposure, the corrosion products were characterized using SEM, EDS, ICP-OES, TEM, and EFTEM to determine their high-temperature resistance to Na₂SO₄ and key reaction mechanisms. All SiC fiber types tested in this work exhibited little resistance to Na₂SO₄ deposit-induced attack relative to their behavior in dry O₂ environments. It was found that Hi-Nicalon displayed the least resistance to Na₂SO₄ deposit-induced attack due to excess carbon content resulting in the formation of a highly porous crystalline oxide and promotion of basic corrosion conditions. All fiber types formed a crystalline SiO₂ reaction product, either cristobalite or tridymite. Sylramic and Sylramic iBN formed a crystalline SiO₂ reaction layer containing TiO₂ needles due oxidation of TiB₂ particles. Additionally, Na₂SO₄ deposits resulted in pitting of all fiber surfaces.     

Covalent surface functionalization of nonwoven fabrics with controlled hydrophobicity,water absorption,and pH regulation properties

A modular method for functionalization of nonwoven fabrics was developed using a two-step process. In the first step, the fabrics were grafted with a linker molecule, 10-undecenoyl chloride, via esterification, followed by attachment of a functional material under UV irradiation. Perfluorodecanethiol and 3-mercaptopropionic acid (MPA) were connected to the linker-modified fabrics using thiol-ene click chemistry. Perfluorodecanethiol modified fabrics exhibited hydrophobicity with water contact angle of about 140° while MPA-modified fabrics were able to lower the pH of a solution by about 1.6. We additionally demonstrated the possibility to connect functional polymers to the linker-modified fabrics by radical graft polymerization of acrylic acid; this produced a thin layer of the polymer on the surface of the fabric. Fabrics modified with poly(acrylic acid) exhibited increased hydrophilicity with water contact angle of 0° for both cotton and viscose-polyester fabrics, while the water absorption capability for polypropylene fabrics increased from about 50 to 1200%.     

Polystyrene and poly(methyl methacrylate) interfaces reinforced with diblock carbon nanotubes

An asymmetric double cantilever beam test was used to determine the ability of carbon nanotubes with varying chemistry along their lengths, that is, diblock nanotubes, to compatibilize the polystyrene/poly(methyl methacrylate) (PS/PMMA) interface. PS molecules were grafted primarily to one of the blocks to cause that block to migrate to the PS phase since otherwise both blocks would prefer to reside in PMMA. Fracture toughnesses increased monotonically with increasing diblock carbon nanotube concentration and maximum values were like those for block copolymer-reinforced interfaces while single-chemistry nanotubes showed no reinforcing effect. However, the abrupt increase in fracture toughness with added compatibilizer indicative of a transition to crazing was not found consistent with nanotubes suppressing crazing in homopolymers. Scanning electron microscopy images of the fractured surfaces show agglomerates of carbon nanotubes present which are likely limiting the efficacy of carbon nanotubes at toughening the interface.     

A coherence maximisation process for solving normative inconsistencies

Norms can be used in multi-agent systems for defining patterns of behaviour in terms of permissions, prohibitions and obligations that are addressed to agents playing a specific role. Agents may play different roles during their execution and they may even play different roles simultaneously. As a consequence, agents may be affected by inconsistent norms; e.g., an agent may be simultaneously obliged and forbidden to reach a given state of affairs. Dealing with this type of inconsistency is one of the main challenges of normative reasoning. Existing approaches tackle this problem by using a static and predefined order that determines which norm should prevail in the case where two norms are inconsistent. One main drawback of these proposals is that they allow only pairwise comparison of norms; it is not clear how agents may use the predefined order to select a subset of norms to abide by from a set of norms containing multiple inconsistencies. Furthermore, in dynamic and non-deterministic environments it can be difficult or even impossible to specify an order that resolves inconsistencies satisfactorily in all potential situations. In response to these two problems, we propose a mechanism with which an agent can dynamically compute a preference order over subsets of its competing norms by considering the coherence of its cognitive and normative elements. Our approach allows flexible resolution of normative inconsistencies, tailored to the current circumstances of the agent. Moreover, our solution can be used to determine norm prevalence among a set of norms containing multiple inconsistencies.     

Optics clustered to output unique solutions: a multi-laser facility for combined single molecule and ensemble microscopy

Optics clustered to output unique solutions (OCTOPUS) is a microscopy platform that combines single molecule and ensemble imaging methodologies. A novel aspect of OCTOPUS is its laser excitation system, which consists of a central core of interlocked continuous wave and pulsed laser sources, launched into optical fibres and linked via laser combiners. Fibres are plugged into wall-mounted patch panels that reach microscopy end-stations in adjacent rooms. This allows multiple tailor-made combinations of laser colours and time characteristics to be shared by different end-stations minimising the need for laser duplications. This setup brings significant benefits in terms of cost effectiveness, ease of operation, and user safety. The modular nature of OCTOPUS also facilitates the addition of new techniques as required, allowing the use of existing lasers in new microscopes while retaining the ability to run the established parts of the facility. To date, techniques interlinked are multi-photon/multicolour confocal fluorescence lifetime imaging for several modalities of fluorescence resonance energy transfer (FRET) and time-resolved anisotropy, total internal reflection fluorescence, single molecule imaging of single pair FRET, single molecule fluorescence polarisation, particle tracking, and optical tweezers. Here, we use a well-studied system, the epidermal growth factor receptor network, to illustrate how OCTOPUS can aid in the investigation of complex biological phenomena.     

Autoregressive model-based fuzzy clustering and its application for detecting information redundancy in air pollution monitoring networks

Fuzzy clustering enables the simultaneous membership of objects in two or more clusters. This is particularly pertinent where time series are concerned, because very often patterns of time series change over time. Thus, a time series might belong to different clusters over different periods of time, in which case, crisp clustering is unable to capture this multi-cluster membership. In this paper, we adopt a Fuzzy C-Medoids approach to clustering time series based on autoregressive estimates of models fitted to the time series. We illustrate very good performance of this approach in a range of simulation studies. By means of two applications, we also show the usefulness of this clustering approach in the air pollution monitoring, by considering air pollution time series, i.e., CO time series, CO₂ time series and NO time series monitored on world and urban scales. In particular, we show that, by considering in the clustering process, the autoregressive representation of these air pollution time series, we are able to detect possible information redundancy in the monitoring networks and then, decreasing the number of monitoring stations, to reduce the monitoring costs and then to increase the monitoring efficiency of the networks.     

A prototype for cartographic human body analysis

A cartographic-oriented model uses algebraic map operations to perform spatial analysis of medical data relative to the human body. A prototype system uses 3D visualization techniques to deliver analysis results. A prototype implementation suggests the model might provide the basis for a medical application tool that introduces new information insight.     

Computing all efficient solutions of the biobjective minimum spanning tree problem

A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a “k-best” algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance.