Rheological properties of rennet casein-whey protein gels prepared at different mixing speeds

The rheological properties at small (oscillatory shear) and large (uniaxial compression) deformations of heat-induced gels (80 °C for 20 min, pH 7.3) containing 25% rennet casein (RCN), 2.5% disodium phosphate and 0%, 2.3% or 6.3% of whey protein isolate (WPI) were measured for samples cooked in a torque-rheometer at mixing speeds within a range of 20–200 rpm (shear rates: ∼15–230 s⁻¹). In addition, microstructure analyses were performed, separately staining RCN and WPI, by Confocal Scanning Laser Microscopy (CSLM). Both small and large deformation tests indicated that increasing addition of WPI prior to the cooking process of RCN resulted in gels exhibiting higher storage and deformability moduli than WPI-free samples. Increasing shear rates during cooking also affected the rheological properties of RCN–WPI gels, and stronger gels were formed as the shear rate during cooking was increased. Despite the data dispersion among replicates, the effect of shear rate on gel strength were evident for RCN gels with 6.3% WPI and relatively clear for gels with 2.3% WPI; however, the trend was uncertain for WPI-free RCN gels. Possible explanations for this observation are that when increasing WPI levels in the presence of RCN and heat, disulfide-thiol exchange reactions between denatured WPI and κ-casein (κ-CN) are increased and possibly promoted by shear rate, resulting in stronger and more cross-linked gel structure. CSLM results were not conclusive to support this hypothesis.     

Performance assessment of PID and IMC tuning methods for a mixing process with time delay

A flow process with time delay has been considered for modeling and control. A dilute solution of sodium chloride is used as tracer and an online conductivity measurement unit as sensor and recorder. The objective of the current study is to design control algorithms and present corresponding robust control analysis for the process. The control methodologies considered are (i) conventional PID control and (ii) internal model control (IMC). The control structures are comparatively analyzed using standard robustness measures for stability and performance. Of the two control algorithms, conventional PID and IMC, IMC exhibits faster settling time, no overshoot, better set-point tracking and disturbance rejection, and good robust performance than the PID control scheme.     

Glycocalyx‐Like Hydrogel Coatings for Small Diameter Vascular Grafts

Novel biological vascular conduits, such as decellularized tissue engineered vascular grafts (TEVGs) are hindered by high thrombogenicity. To mimic the antithrombogenic surface of native vessels with a continuous glycosaminoglycan layer that is present on endothelial cells (ECs), a hyaluronic acid (HA) modified surface is established, to effectively shield blood platelets from collagen‐triggered activation. Using the amine groups present on 4 mm diameter decellularized TEVGs, a continuous HA hydrogel coating is built via a bifunctional thiol‐reactive cross‐linker, thereby avoiding nonspecific collagen matrix cross‐linking. The HA hydrogel layer recreates a luminal wall, “hiding” exposed collagen from the bloodstream. In vitro blood tests show that adhered platelets, fibrinogen absorption, and fibrin formation on HA‐coated decellularized TEVGs are significantly lower than on uncoated decellularized TEVGs. The HA surface also inhibits macrophage adhesion in vitro. HA‐coated decellularized syngeneic rat aortae (≈1.5 mm diameter), and TEVGs in rat and canine models, respectively, are protected from aggressive thrombus formation, and preserve normal blood flow. Re‐endothelialization is also observed. HA‐coated TEVGs may be an off‐the‐shelf small‐diameter vascular graft with dual benefits: antithrombogenic protection and promotion of endothelium.     

Study of chemical and mechanical properties of Dharbai fiber reinforced polyester composites

This investigation is focused on identifying a new variety of natural fiber (Dharbai fiber) for reinforcement in polymer matrix composites. An investigation on extraction procedure of Dharbai fibers has been undertaken. The chemical properties of Dharbai fibers were determined experimentally as per TAPPI standards. The FT-IR Spectroscopy was used to study the chemical structure of Dharbai fibers and the tensile properties of these fibers were studied using single filament test. The fibers extracted were reinforced in polyester matrix by varying the fabrication parameters namely fiber weight content (%) and fiber length (mm). The effect of fiber weight content and fiber length on the mechanical properties of Dharbai fiber-polyester composites were evaluated as per ASTM standards. Scanning electron microscope was used to characterize the interfacial bonding between Dharbai fibers and polyester matrix. This study confirmed that, the Dharbai fibers could be used as an effective reinforcement material for making low load bearing polymer composites.     

Reliability of fine-pitch through-vias in glass interposers and packages for high-bandwidth computing and communications

Glass is an ideal substrate material to enable 2.5D and 3D packaging of ICs at low cost and high performance. However, it is a brittle material and is prone to failures during fabrication and operation. Large coefficient of thermal expansion (CTE) mismatch between copper and glass leads to thermomechanical stresses that can lead to glass cracking and delamination from glass interfaces. This paper focuses on modeling and reliability characterization of copper-plated through-package-vias (TPV) in glass packages. Thermomechanical simulations were carried out to obtain design guidelines for reliable TPVs in glass. Test-vehicles with different glass thicknesses and copper TPV fabrication conditions were fabricated for thermal cycling tests, resistance monitoring and failure analysis. The reliability characterization results showed good thermomechanical reliability of TPVs in ultra-thin glass panels.     

Surface Protection and Morphological Study of Copper by Green Corrosion Inhibitor: 8QSC in HNO<Subscript>3</Subscript> Medium

The inhibition performance and surface protection of green corrosion inhibitor 8-quinoline sulphonyl chloride (8QSC) on copper (Cu) was evaluated by chemical (weight loss) method in 0.5, 1.0 and 2.0 M HNO₃ solutions and by electrochemical methods such as potentiodynamic polarization (PDP), AC-impedance spectroscopy (AC-IS) and linear polarization resistance in 1.0 M HNO₃ solution at room temperature. Both chemical and electrochemical techniques showed that 8QSC is an efficient green corrosion inhibitor for copper and the efficiency reached 90.4% by weight loss method and 88.4% by AC-IS method at optimum concentration of (300 ppm) 8QSC. The adsorption behavior of 8QSC on copper metal in acid medium obeyed the Langmuir isotherm. The thermodynamic parameters of the adsorption processes were calculated and discussed. AC-IS technique exhibits one capacitive loop, indicating that the corrosion reaction was controlled by charge transfer process. The PDP curves revealed that 8QSC acts as a mixed-type inhibitor. Protective layer of 8QSC on copper surface was examined by SEM, AFM and FT-IR techniques. The experimental results corroborated with results obtained from theoretical DFT studies.     

MODELING OF HYDROPROCESSING REACTIONS

Langmuir-Hinshelwood-Hougen-Watson rate expressions are developed for the hydroprocessing of quinoline, naphthalene and dibenzothiophene based on batch reactor data at 350^°C and at 500 psig. Based on competitive adsorption, the kinetics are extended to binary mixtures of quinoline/naphtha-lene and quinoline/dibenzothiophene. In doing so, the differences in hydrogenation and hydro-genolysis sites are taken into consideration. In all cases, the agreement between the predicted and experimental results are good     

On-Line Learning Failure-Tolerant Neural-Aided Controller for Earthquake Excited Structures

This paper presents an on-line learning failure-tolerant neural controller capable of controlling buildings subjected to severe earthquake ground motions. In the proposed scheme the neural controller aids a conventional H∞ controller designed to reduce the response of buildings under earthquake excitations. The conventional H∞ controller is designed to reduce the structural responses for a suite of severe earthquake excitations using specially designed frequency domain weighting filters. The neural controller uses a sequential learning radial basis function neural network architecture called extended minimal resource allocating network. The parameters of the neural network are adapted on-line with no off-line training. The performance of the proposed neural-aided controller is illustrated using simulation studies for a two degree of freedom structure equipped with one actuator on each floor. Results are presented for the cases of no failure and failure of the actuator on each of the two floors under several earthquake excitations. The study indicates that the performance of the proposed neural-aided controller is superior to that of the H∞ controller under no actuator failure conditions. In the presence of actuator failures, the performance of the primary H∞ controller degrades considerably, since actuator failures have not been considered for the design. Under these circumstances, the neural-aided controller is capable of controlling the acceleration and displacement structural responses. In many cases, using the neural-aided controller, the response magnitudes under failure conditions are comparable to the performance of the H∞ controller under no-failure conditions.     

Effects of entrainment and agglomeration of particles on combustion of nano-aluminum and water mixtures

The combustion of nano-aluminum and water mixtures is studied theoretically for a particle size of 80 nm and over a pressure range of 1–10 MPa. Emphasis is placed on the effects of entrainment and agglomeration of particles on the burning rate and its dependence on pressure. The flame thickness increases by a factor of ∼10, when particle entrainment is considered. This lowers the conductive heat flux at the ignition front, thereby reducing the burning rate. The pressure dependence of the burning rate is attributed to the changes in the burning time and velocity of particles with pressure. In the diffusion limit, the pressure exponent increases from 0 to 0.5, when the entrainment index increases from 0 to 1.0. A similar trend is observed in the kinetics-controlled regime, although the corresponding value exceeds the diffusion counterpart by 0.5. The kinetics-controlled model significantly over-predicts the burning rate and its pressure exponent, depending on the entrainment index. The present analysis suggests that nano-particles formed closely-packed agglomerates of diameter 3–5 μm, which may burn under diffusion-controlled conditions at high pressures.     

Effect of packing density on flame propagation of nickel-coated aluminum particles

The combustion-wave propagation of nickel-coated aluminum particles is studied theoretically for packing densities in the range of 10–100% of the theoretical maximum density. Emphasis is placed on the effect of packing density on the burning properties. The energy conservation equation is solved numerically and the burning rate is determined by tracking the position of the flame front. Atomic diffusion coefficients and reaction rate of isolated nickel-coated aluminum particles are input parameters to the model. The burning behaviors and combustion wave structures are dictated by the heat transfer from the flame zone to the unburned region. Five different models for the effective thermal conductivity of the mixture are employed. The impact of radiation heat transfer is also assessed. As a specific example, the case with a particle size of 79 μm is considered in detail. The burning rate remains nearly constant (<1 cm/s) up to a packing density of 60%, and then increases sharply toward the maximum value of 11.55 cm/s at a density of 100%. The Maxwell–Eucken–Bruggeman model of thermal conductivity offers the most accurate predictions of the burning rate for all loading densities.