Polymers from renewable resources. VIII. Thermal properties of the interpenetrating polymer networks derived from castor oil–isophorone diisocyanate–polyacrylamides

Castor oil was reacted with isophorone diisocyanate varying the isocyanate/hydroxyl ratio to produce a number of polyurethanes (PUs). All the PUs were reacted with acrylamide and methacrylamide using ethylene glycol dimethacrylate as the crosslinker and benzoyl peroxide as the initiator. Thermogravimetric analysis of the polymers was conducted using a computer analysis method for assigning the kinetic mechanism. The degradation steps have been discussed in the light of the kinetic parameters. © 1995 John Wiley & Sons, Inc.     

Variability-aware architecture level optimization techniques for robust nanoscale chip design

The design space for nanoscale CMOS circuits is vast, with multiple dimensions corresponding to process variability, leakage, power, thermal, reliability, security, and yield considerations. These design issues in the form of either objectives or constraints can be handled at various levels of digital design abstraction, such as architectural, logic and transistor. At the architectural level (a.k.a. Register-Transfer Level, RTL), there is a balanced degree of freedom for fast design exploration by exploring various values of design parameters. Correct design decisions at an early phase of the design cycle ensure that design errors are not propagated to lower levels of circuit abstraction, where it is costly to correct them. Moreover, design optimization at higher levels of abstraction provides a convenient way to deal with design complexity, facilitates design verification, and increases design reuse through intellectual property (IP) cores.     

Synthetic resin. XI. Preparation and characterization of resins derived from picoline and lutidine/aromatic hydroxy,amino, and chloro compounds/formaldehyde

A number of resin copolymers have been prepared by condensing α-picoline, γ-picoline, and lutidine separately with hydroxy acetophenone, hydroxy, amino, chloro benzoic acids, and toluic acid in the presence of sodium hydroxide and succinic acid as catalyst. The resins were characterized by infrared spectra of the characteristic groups. The solubility parameters were calculated from Small's group's contribution. The antifungal activity of the resins have also been investigated.     

Processing and physical properties of native grass-reinforced biocomposites

Big blue stem grass fiber-reinforced high density polyethylene powder biocomposites were fabricated using two separate processing schemes: (1) by compounding biofiber with the thermoplastic powder in an extruder and subsequently injection molding the extrusion pellets and (2) by combining biofiber and the powder thermoplastic powder using a modified sheet molding compounding (SMC) line and subsequently compression molding the sheet material. The physical properties including storage modulus, heat deflection temperature (HDT), notched Izod impact strength, and morphology were evaluated with dynamic mechanical analysis, Izod impact strength measurement, and microscopy observation. It was found that compression-molded specimens achieved similar modulus values to injection molded specimens for grass-reinforced high density polyethylene (HDPE) composites. The stiffness of the compression-molded specimens is related to the consolidation state of the samples, which depends on compression molding conditions such as temperature, pressure, and mold type. Compression-molded specimens exhibited a higher HDT and notched Izod impact strength compared to injection-molded samples. Grass fiber-reinforced cellulose acetate butyrate (CAB) biocomposites made with SMC processing had similar physical properties with grass fiber-reinforced HDPE composites, which indicates that natural fiber-reinforced CAB biocomposites have the potential to replace polyolefin-based composites for automotive applications. POLYM. ENG. SCI. 47:969–976, 2007. © 2007 Society of Plastics Engineers.     

Evaluating the role of composition and local structure on alkali out-diffusion in glasses for thin-film solar cells

The presence of alkali ions has reportedly improved the performance of CIGS/CZTS–based thin-film solar cells. The out-diffusion of the alkali ion, in particular, Na, from the glass substrate offers a facile scalable route of supplying the alkali ions during the growth of the absorber layer. In this work, we demonstrate the diffusion of different alkali ions (Li/Na/K) from composition tuned glasses with intentionally incorporated excess alkali ions into a thin Mo film, typically used as a bottom electrode in solar cells. We also evaluate the physical, mechanical, and thermal properties of the glasses for suitability as a substrate in thin-film deposition. The out-diffusion of alkali ions to the overlayer is found to be critically influenced by the composition and the local structure of the glasses. The Na ions exhibit the highest extent of diffusion among the alkali ions present in glass substrates, while that for the K-ions is the lowest. For the glasses with mixed alkali ions, the presence of Li facilitated the out-diffusion of Na, whereas K ions appear to inhibit the same. Differently with the existing reports, we show that the activation energy and the presence of Ca ions as additional modifiers play a crucial role in the transport mechanism of the ions. In addition, the synthesized glasses exhibit hardness of the order 5-7 GPa, density ~2.55 g cm^-3. The glass transition temperature lies between 535 and 580°C and the coefficient of thermal expansion 8.5-10 ppm/K, which is highly suitable for use as substrates in thin-film solar cells.     

A new high accuracy method for two-dimensional biharmonic equation with nonlinear third derivative terms: application to Navier–Stokes equations of motion

In this paper, we propose a new compact fourth-order accurate method for solving the two-dimensional fourth-order elliptic boundary value problem with third-order nonlinear derivative terms. We use only 9-point single computational cell in the scheme. The proposed method is then employed to solve Navier–Stokes equations of motion in terms of streamfunction–velocity formulation, and the lid-driven square cavity problem. We describe the derivation of the method in details and also discuss how our streamfunction–velocity formulation is able to handle boundary conditions in terms of normal derivatives. Numerical results show that the proposed method enables us to obtain oscillation-free high accuracy solution.     

Strain Rate Effects on Dynamic Fractures in Fine‐grained Granitic Rock

The effect of dynamic strain rates on failure responses of a fine‐grained granitic rock is studied experimentally and theoretically. Theoretical investigation employs a model incorporating dynamic fracture criterion with damage mechanics theory. Experimental investigation is conducted using split Hopkinson pressure bar device. In order to investigate the effects of microstructure on dynamic fracture failure under different loading rates, fragment debris of each tested specimen is collected and analyzed. It is found through the debris analysis that the granitic rock breaks down into the fragment debris in grain size scales and the effect of strain rates on the formation of fragment debris appears to be related to the microstructure of the rock. It is also found that dynamic inertia induced by the dynamic loading can reduce the effect of friction confinement generated by the contact between the cylindrical specimen and two split Hopkinson pressure bars on the dynamic responses of the specimen. Theoretical evaluations agree with the corresponding experimental observations.     

Artificial neural network based system identification and model predictive control of a flotation column

The paper describes the design of a neural network based model predictive controller for controlling the interface level in a flotation column. For the system identification, the tailings valve opening is subjected to a pseudo-random ternary signal and response of the interface level is recorded over a period of time. The data so generated is used to develop a dynamic feed forward neural network model. The model uses two past values and one present value of the tailings valve opening as well as interface level as inputs and predicts the future interface level. This model is used for the design of a model predictive controller to control the interface level. The controller was tested both for liquid–gas system as well as liquid–gas–solid system and was found to perform very satisfactorily. The performance of the controller was compared with that of a conventional PI controller for a two-phase system and was found to be better.