Effect of dispersity on the Tll (>Tg) transition in polystyrene

The presence of a high temperature (>T_g) relaxation in amorphous polystyrene has been investigated further. In the previous work,¹ the techniques of differential thermal analysis (DTA) and torsional braid analysis (TBA) were employed to study polystyrene as a function of “monodisperse” molecular weight. The occurrence of the T_ll transition appeared to be associated with the attainment of a critical viscosity level with also corresponded with a free volume level. An entanglement network developed at a critical value of molecular weight, M_c, giving a break in the T_ll-versus-M plots. The present work deals with the influence of dispersity on the T_ll transition, below and above M_c. A series of binary blends of “monodisperse” anionically polymerized polystyrenes with systematic changes in M?_n and heterogeneity index (M?_w/M?_n) was tested by TBA. The results show that when both components have molecular weights below M_c, single and average values of T_g and T_ll are observed which are linearly related to M?_n^?1, as predicted by free volume arguments. Although a single T_g is observed when one component has a molecular weight above and the other has a molecular weight below M_c, the components appear to undergo the T_ll relaxation independently. The results indicate that both the glass transition and the T_ll transition are basically governed by the same type of molecular motion but at different length ranges.     

Polyaniline‐modified cellulose nanofibrils as reinforcement of a smart polyurethane

Segmented polyurethanes exhibiting shape memory properties were modified by the addition of polyaniline (PANI)‐coated cellulose nanofibrils (CNFs). The two‐phase structure of the polymer is responsible for the material's ability to ‘remember’ and autonomously recover its original shape after being deformed in response to an external thermal stimulus. PANI was grown on the surface of the CNFs via in situ polymerization. Modified nanocrystals were added to the segmented polyurethane in concentrations ranging from 0 to 15 wt%. The changes in the material properties associated with the percolation of the coated fibrils appear at higher concentrations than previously observed for non‐modified CNFs, which suggests that fibril agglomeration is occurring due to the PANI coating. The shape memory behavior of the composites is maintained at about the same level as that of the unfilled polyurethane only up to 4 wt% of fibrils. At higher concentrations, the rigidity of the nanofibrils as well as their interaction with the hard‐segment phase and the increasing difficulty of dispersing them in the polymer collaborate to produce early breakage of the specimens when stretched at temperatures above the melting point of the soft segments. Copyright © 2010 Society of Chemical Industry     

Purification and crystallization of complexes modeling the active state of the fragile histidine triad protein

Fragile histidine triad protein (Fhit) is a diadenosine triphosphate (ApppA) hydrolase encoded at the human chromosome 3 fragile site which is frequently disrupted in tumors. Reintroduction of FHIT coding sequences to cancer cell lines with FHIT deletions suppressed the ability of these cell lines to form tumors in nude mice even when the reintroduced FHIT gene had been mutated to allow ApppA binding but not hydrolysis. Because this suggested that the tumor suppressor activity of Fhit protein depends on substrate-dependent signaling rather than ApppA catabolism, we prepared two crystalline forms of Fhit protein that are expected to model its biologically active, substrate-bound state. Wild-type and the His96Asn forms of Fhit were overexpressed in Escherichia coli, purified to homogeneity and crystallized in the presence and absence of ApppA and an ApppA analog. Single crystals obtained by vapor diffusion against ammonium sulfate diffracted X-rays to beyond 2.75 A resolution. High quality native synchrotron X-ray data were collected for an orthorhombic and a hexagonal crystal form.      

Evolution and stability of 2-mercaptobenzimidazole inhibitor film upon Al alloy 6061

Journal of Applied Electrochemistry - Organic corrosion inhibitors have become competent alternatives to hazardous chrome conversion coatings due to their rapid adsorption over metal surfaces in...     

Microstructural characteristics of tungsten-base nanocomposites produced from micropowders by high-pressure torsion

Micropowder mixtures of W–50% Al, W–50% Ti and W–50% Ni were subjected to severe plastic deformation at 573 K using high-pressure torsion (HPT). The powder mixtures were consolidated and nanocomposites of W/Ti, W/Ti and W/Ni, with average grain sizes as small as ～9, ～15 and ～12 nm, respectively, were formed by imposing large shear strains. The nanocomposites exhibited Vickers microhardness as high as ～900 Hv, a level that has rarely been reported for metal–matrix composites. X-ray diffraction analyses together with high-resolution transmission electron microscopy showed that in addition to grain refinement, an increase in the fraction of grain boundaries up to 20%, the dissolution of elements in each other up to ～15 mol.%, an increase in the lattice strain up to 0.6%, and an increase in density of edge dislocations up to 10¹⁶ m^?2 occurred by HPT. The current study introduces the HPT process as an effective route for the production of ultrahigh-strength W-base nanocomposites, fabrication of which is not generally easy when processing at high temperatures because of interfacial reaction and formation of brittle intermetallics.     

Metal Dusting of Fe–Cr and Fe–Ni–Cr Alloys Under Cyclic Conditions

Metal dusting is the disintegration of alloys into carbon and metal particles during high-temperature exposure to carbon-bearing gases. Model Fe–Cr and Fe–Ni–Cr alloys were studied to test the hypothesis that M₃C formation is necessary for metal dusting to occur. The alloys were exposed to a 68% CO–26% H₂–6% H₂O gas mixture at 680°C (a_c=2.9) under thermal cycling conditions. Equilibrium calculations predicted the formation of M₃C at the surface of Fe–25Cr, but not Fe–60Cr. All compositions were expressed in w/o, weight percent. Alloys of Fe–25Cr with 2.5, 5, 10, and 25 w/o nickel additions were also exposed to the same conditions to study the role of nickel in destabilizing the precipitation of M₃C and, hence, altering the resistance to metal dusting. Metal dusting was observed on all the alloys except Fe–60Cr. For Fe–25Cr, Fe–25Cr–2.5Ni, and Fe–25Cr–5Ni, the carbonization and dusting process was localized, and its incidence decreased in Fe–25Cr–2.5Ni, consistent with the increased destabilization of M₃C precipitation. However, Fe–25Cr–10Ni and Fe–25Cr–25Ni both underwent extensive dusting in the absence of protective Cr₂O₃ formation. The carbon deposits formed consisted of carbon filaments, which contained particles at their tips. These were shown by electron diffraction to be exclusively Fe₃C in Fe–25Cr, Fe–25Cr–2.5Ni, and Fe–25Cr–5Ni, and a mixture of austenite and (Fe,Ni)₃C in Fe–25Cr–10Ni and Fe–25Cr–25Ni.     

Training a reciprocal-sigmoid classifier by feature scaling-space

This paper presents a reciprocal-sigmoid model for pattern classification. This proposed classifier can be considered as a Φ-machine since it preserves the theoretical advantage of linear machines where the weight parameters can be estimated in a single step. The model can also be considered as an approximation to logistic regression under the framework of Generalized Linear Models. While inheriting the necessary classification capability from logistic regression, the problems of local minima and tedious recursive search no longer exist in the proposed formulation. To handle possible over-fitting when using high order models, the classifier is trained using multiple samples of uniformly scaled pattern features. Empirically, the classifier is evaluated using a benchmark synthetic data from random sampling runs for initial statistical evidence regarding its classification accuracy and computational efficiency. Additional experiments based on ten runs of 10-fold cross validations on 40 data sets further support the effectiveness of the reciprocal-sigmoid model, where its classification accuracy is seen to be comparable to several top classifiers in the literature. Main reasons for the good performance are attributed to effective use of reciprocal sigmoid for embedding nonlinearities and effective use of bundled feature sets for smoothing the training error hyper-surface. Editor: Risto Miikkulainen     

Face recognition with radial basis function (RBF) neural networks

A general and efficient design approach using a radial basis function (RBF) neural classifier to cope with small training sets of high dimension, which is a problem frequently encountered in face recognition, is presented. In order to avoid overfitting and reduce the computational burden, face features are first extracted by the principal component analysis (PCA) method. Then, the resulting features are further processed by the Fisher's linear discriminant (FLD) technique to acquire lower-dimensional discriminant patterns. A novel paradigm is proposed whereby data information is encapsulated in determining the structure and initial parameters of the RBF neural classifier before learning takes place. A hybrid learning algorithm is used to train the RBF neural networks so that the dimension of the search space is drastically reduced in the gradient paradigm. Simulation results conducted on the ORL database show that the system achieves excellent performance both in terms of error rates of classification and learning efficiency.     

Analysis of 59 cases of non-traumatic sudden death in various neurological diseases]

Sudden death is a common complication of myocardial infarction, necrotic pancreatitis and other diseases. Physicians usually neglect the possibility of neurological disorders. 59 cases of sudden death among 314 autopsied cases with neurological diseases were analyzed. The most frequent cause of neurological sudden death was cerebrovascular disease (CVD). It was present in 53 (89.9%) cases. 48 of them had hemorrhagic CVD. 37 of these 48 cases were due to hypothalamic lesions. In 37 cases general autopsy was performed; pathological abnormalities of heart, lungs, stomach etc, were found in 28 of them. In conclusion, the size and location of the lesion correlated with the prognosis of the disease. Concomitant multiple organ damage may deteriorate the lesion. Awareness of sudden death resulting from CVD may elevate the rate of correct diagnosis.     

The design and optimization of high-performance, double-polyself-aligned p-n-p technology

The device design and performance of double-poly self-aligned p-n-p technology, featuring a low-resistivity p⁺ subcollector, thin p-epi, and boron-doped poly-emitter are described. Device isolation is provided by deep and shallow trenches which reduce the collector-to-substrate capacitance while maintaining a high breakdown voltage (⩾40 V). By utilizing a shallow emitter process in conjunction with an optimized arsenic-base implant, devices with emitter-base junction depths as shallow as 20 nm and base widths of less than 100 nm were obtained. Cutoff frequencies of up to 27 GHz were obtained, and the AC performance was demonstrated by an NTL-gate delay of 36 ps and an active-pull-down (APD) ECL-gate delay of 20 ps. This high-performance p-n-p technology was developed to be compatible with existing double-poly n-p-n technologies. The matching speed of p-n-p devices opens up new opportunities for high-performance complementary bipolar circuits