Self-Assembly of Bile Steroid Analogues: Molecules, Fibers, and Networks

Structural and rheological features of a series of molecular hydrogels formed by synthetic bile salt analogues have been scrutinized. Among seven gelators, two are neutral compounds, while the others are cationic systems among which one is a tripodal steroid derivative. Despite the fact that the chemical structures are closely related, the variety of physical characteristics is extremely large in the structures of the connected fibers (either plain cylinders or ribbons), in the dynamical modes for stress relaxation of the associated SAFINs, in the scaling laws of the shear elasticity (typical of either cellular solids or fractal floc-like assemblies), in the micron-scale texture and the distribution of ordered domains (spherulites, crystallites) embedded in a random mesh, in the type of nodal zones (either crystalline-like, fiber entanglements, or bundles), in the evolution of the distribution and morphology of fibers and nodes, and in the sensitivity to added salt. SANS appears to be a suitable technique to infer all geometrical parameters defining the fibers, their interaction modes, and the volume fraction of nodes in a SAFIN. The tripodal system is particularly singular in the series and exhibits viscosity overshoots at the startup of shear flows, an “umbrella-like” molecular packing mode involving three molecules per cross section of fiber, and scattering correlation peaks revealing the ordering and overlap of 1d self-assembled polyelectrolyte species.

Wrought aluminum-nickel alloys for high strength-high conductivity applications

Aluminum-Nickel alloys ranging from 0.06 pct to 6.1 pct (by wt) Ni have been developed for high strength-high conductivity applications. These alloys were produced by solidification in a permanent mold followed by homogenization, hot extrusion or hot rolling and cold drawing to wire form. This sequence of fabrication a) led to the production of fine fibrous dispersoids of NiAl3 as part of the Al-NiAl3 eutectic during the initial casting operation, b) permitted the retention of fine fibrous dispersiods of NiAl3 produced during casting without any significant coarsening during processing and c) led to uniform dispersion and general alignment of these fibrous dispersoids along a given direction in the product without any measurable fiber-matrix separation, extensive fiber-fragmentation or crack production in the matrix. These alloys can be processed to wire form as easily as aluminum and when processed by the above sequence, possess very attractive combination of high strength-high electrical conductivity. Tensile strengths range from 173 N/mm2 (at 0.6 pct Ni) to 241 N/mm2 (at 6.1 pct Ni) in combination with corresponding conductivity values between 62 pct IACS and 55.5 pct IACS. The wires also possess attractive yield strength; for instance, the 0.2 pct off-set strength of Al-6.1 pct Ni wire is 213 N/mm2. Using simple composite rules, the estimated strength and the conductivity of NiAl3 fibers were found to be 1380 N/mm2 and 18 pct IACS respectively, in these wires.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Defect-selective photothermal imaging: a sensitive tool for damage mapping in optical coatings

A defect-selective photothermal imaging system for the diagnostics of optical coatings is demonstrated. The instrument has been optimized for pump and probe parameters, detector performance, and signal processing algorithm. The imager is capable of mapping purely optical or thermal defects efficiently in coatings of low damage threshold and low absorbance. Detailed mapping of minor inhomogeneities at low pump power has been achieved through the simultaneous action of a low-noise fiber optic photothermal beam defection sensor and a common-mode-rejection demodulation (CMRD) technique. The linearity and sensitivity of the sensor have been examined theoretically and experimentally, and the signal to noise ratio improvement factor is found to be about 110 compared to a conventional bicell photodiode. The scanner is so designed that mapping of static or shock sensitive samples is possible. In the case of a sample with absolute absorptance of 3.8 x 10(-4), a change in absorptance of about 0.005 x 10(-4) has been detected without ambiguity, ensuring a contrast parameter of 760. This is about 1085% improvement over the conventional approach containing a bicell photodiode, at the same pump power. The merits of the system have been demonstrated by mapping two intentionally created damage sites in a MgF2 coating on fused silica at different excitation powers. Amplitude and phase maps were recorded for thermally thin and thick cases, and the results are compared to demonstrate a case which, in conventional imaging, would lead to a deceptive conclusion regarding the type and location of the damage. Also, a residual damage profile created by long term irradiation with high pump power density has been depicted.

The Role of Interface Modification on Thermal Degradation and Crystallization Behavior of Composites from Commingled Polypropylene Fiber and Banana Fiber

The thermal degradation behavior of banana fiber and polypropylene/banana fiber composites has been studied by thermogravimetric analysis. Banana fiber was found to be decomposing in two stages, first one around 320 degrees C and the second one around 450 degrees C. For chemically treated banana fiber, the decomposition process has been at a higher temperature, indicating thermal stability for the treated fiber. Activation energies for thermal degradation were estimated using Coats and Redfern method. Calorific value of the banana fiber was measured using a constant volume isothermal bomb calorimeter. rystallization studies exhibited an increase in the crystallization temperature and crystallinity of polypropylene upon the addition of banana fiber. POLYM. COMPOS., 31:1113-1123, 2010. (C) 2009 Society of Plastics Engineers.

An experimental approach for non-destructive evaluation of fatigue damage in CFRP composites

Study of fatigue phenomenon in composites requires a dynamic tool which can detect and identify different failure mechanisms involved. The tool should also be capable of monitoring the cumulative damage progression on-line. Acoustic Emission Technique has been utilized in the experimental investigations on unidirectional carbon fiber reinforced plastic (CFRP) composite specimens subjected to tension-tension fatigue. Amplitude as well as frequency distribution of Acoustic Emission (AE) signals have been studied to detect and characterize different failure mechanisms. For a quantitative measure of degradation of the material with fatigue load cycles, reduction in stiffness of the specimen has been measured intermittently. Ultrasonic imaging could give the information on the changes in the interior status of the material at different stages of fatigue life.

Anaerobic retting of banana and arecanut wastes in a plug flow digester for recovery of fiber, biogas and compost

Leaves and leaf sheath of banana and areca husk (Areca catechu) constitute an important component of urban solid waste (USW) in India which are difficult to degrade under normal windrow composting conditions. A successful method of anaerobic digestion built around the fermentation properties of these feedstock has been evolved which uses no moving parts, pretreatment or energy input while enabling recovery of four products: fiber, biogas, compost and pest repellent. An SRT of 27 d and 35 d was found to be optimum for fiber recovery for banana leaf and areca husk, respectively. Banana leaf showed a degradation pattern different from other leaves with slow pectin-1 degradation (80%) and 40% lignin removal in 27 d SRT. Areca husk however, showed a degradation pattern similar to other plant biomass. Mass recovery levels for banana leaf were fiber-20%, biogas-70% (400 ml/g TS) and compost-10%. For areca husk recovery was fiber-50%, biogas-45% (250 ml/g TS) and compost-5%. (C) 2012 Elsevier Inc. All rights reserved.

Non-Destructive Evaluation of Defects and Damage in Composite Materials and Structures

The mechanical behaviour of composite materials differs from that of conventional structural materials owing to their heterogeneous and anisotropic nature. Different types of defects and anomalies get induced in these materials during the fabrication process. Further, during their service life, the components made of composite materials develop different types of damage. The performance and life of such components is governed by the combined effect of all these defects and damage. While porosity, voids, inclusions etc., are some defects those can get induced during the fabrication of composites, matrix cracks, interface debonds, delaminations and fiber breakage are major types of service induced damage which are of concern. During the service life of components made of composites, one type of damage can grow and initiate another type of damage. For example, matrix cracks can gradually grow to the interface and initiate debonds. Interface debonds in a particular plane can lead to delaminations. Consequently, the combined effect of different types of distributed damage causes the failure of the component. A set of non-destructive evaluation (NDE) methods is well established for testing conventional metallic materials. Some of them can also be utilized for composite materials as they are, and in some cases with a little different approach or modification. Ultrasonics, Radiography, Thermography, Fiber Optics, Acoustic Emision Techniques etc., to name a few. Detection, evaluation and characterization of different types of defects and damage encountered in composite materials and structures using different NDE tools is discussed briefly in this paper.

Damage mechanisms in stainless steel and chromium carbide coatings under controlled environment fretting conditions

Fretting is of a serious concern in many industrial components, specifically, in nuclear industry for the safe and reliable operation of various component and/or system. Under fretting condition small amplitude oscillations induce surface degradation in the form of surface cracks and/or surface wear. Comprehensive experimental studies have been carried out simulating different fretting regimes under ambient and vacuum (10(-9) MPa) conditions and, temperature up to 400 degrees C. Studies have been carried out with stainless steel spheres on stainless steel flats, and stainless steel spheres against chromium carbide, with 25% nickel chrome binder coatings. Mechanical responses are correlated with the damage observed. It has been observed that adhesion plays a vital role in material degradation process, and its effectiveness depends on mechanical variables such as normal load, interfacial tangential displacement, characteristics of the contacting bodies and most importantly on the environment conditions. Material degradation mechanism for ductile materials involved severe plastic deformation, which results in the initiation or nucleation of cracks. Ratcheting has been observed as the governing damage mode for crack nucleation under cyclic tangential loading condition. Further, propagation of the cracks has been observed under fatigue and their orientation has been observed to be governed by the contact conditions prevailing at the contact interface. Coated surfaces show damage in the form of brittle fracture and spalling of the coatings. Existence of stick slip has been observed under high normal load and low displacement amplitude. It has also been observed that adhesion at the contact interface and instantaneous cohesive strength of the contacting bodies dictates the occurrence of material transfer. The paper discusses the mechanics and mechanisms involved in fretting damage under controlled environment conditions. (C) 2015 Elsevier B.V. All rights reserved.

Wave propagation in elastic solids undergoing damage and growth process

Modeling and analysis of wave propagation in elastic solids undergoing damage and growth process are reported in this paper. Two types of diagnostic problems, (1) the propagation of waves in the presence of a slow growth process and (2) the propagation of waves in the presence of a fast growth process, are considered. The proposed model employs a slow and a fast time scale and a homogenization technique in the wavelength scale. A detailed analysis of wave dispersion is carried out. A spectral analysis reveals certain low-frequency bands, where the interaction between the wave and the growth process produces acoustic metamaterial-like behavior. Various practical issues in designing an efficient method of acousto-ultrasonic wave based diagnostics of the growth process are discussed. Diagnostics of isotropic damage in a ductile or quasi-brittle solid by using a micro-second pulsating signal is considered for computer simulations, which is to illustrate the practical application of the proposed modeling and analysis. The simulated results explain how an estimate of signal spreading can be effectively employed to detect the presence of a steady-state damage or the saturation of a process.

Effect of pregnant mare serum gonadotropin on the induction and degradation of FSH and LH receptors in the granulosa cell of the immature rat

The relative induction of FSH and LH receptors in the granulosa cells of immature rat ovary by pregnant mare serum gonadotropin (PMSG) has been studied. A single injection of PMSG (15 IU) brought about a 3- and 12-fold increase in FSH and LH receptor concentration,respectively, in the granulosa cells. Maximal concentration was reached by 72 h but the receptor levels showed a sharp decline during the next 24–48 h. The kinetic properties of the newly formed FSH receptors were indistinguishable from the pre-existing ones. The induced FSH receptors were functional as demonstrated by an increase in the in vitro responsiveness of the cells to exogenous FSH in terms of progesterone production. Treatment of immature rats with cyanoketone, an inhibitor of Δ5,3β-hydroxysteroid dehydrogenase, prior to PMSG injection effectively reduced the PMSG-stimulated increase in the serum estradiol, uterine weight and LH receptors but had no effect on the FSH receptor induction. The ability of PMSG to induce gonadotropin receptors can be arrested at any given time by injecting its antibody, thereby suggesting a continuous need for the hormonal inducer. Estrogen in the absence of the primary inducer was unable to maintain the induced LH and FSH receptor concentration. Inhibition of prostaglandin synthesis using indomethacin also had no effect on either the induction or degradation of gonadotropin receptors. Administration of PMSG antiserum, 48 h after PMSG injection, brought about a rapid decline in the induced receptors over the next 24 h, with a rate constant and \iota 1/2 of 0.078 h−1 and 8.9 h for FSH receptors and 0.086 h−1 and 8.0 h for the LH receptors, respectively.

Gossypol mediated DNA degradation

Gossypol, a polyphenolic compound isolated from cotton plant was found to degrade pBR322 DNA Image in a reaction which required the presence of a metal ion, a reducing agent (2-mercaptoethanol) and oxygen as revealed after agarose gel electrophoresis. Fe3+ and Co2+ showed maximum degradation whereas addition of Ca2+ and Mg2+ prevented the gossypol mediated DNA damage. Gossypol caused degradation of rat liver DNA incubated Image even in the absence of added metal ions and 2-mercaptoethanol. Incubation of intact rat liver nuclei with gossypol reveled DNA degradation and nuclei isolated from rats treated with gossypol Image showed higher succestibility to DNA fragmentation when incubated with gossypol Image than control nuclei. EcoRl and AIuI digestion of DNA isolated from gossypol treated rats gave clear cut evidence for DNA degradation. These observations indicate that gossypol is genotoxic and considereable care has to be exercised in its use. SDS, sodium dodecayl sulphate; TE buffer, Tris-HCL-EDTA buffer.