Microstructure analysis of methyl acrylate/methyl methacrylate copolymers by two‐dimensional NMR spectroscopy

Methyl acrylate (A)/methyl methacrylate (B) copolymers of different compositions were synthesized in bulk at 50°C and the compositions were determined from ¹H NMR spectra. Reactivity ratios were optimized using the least square methodology. Compositional and configurational assignments were done using two‐dimensional (2D) Heteronuclear Single Quantum Correlation (HSQC) and Total Correlation Spectroscopy (TOCSY) experiments. Methylene proton and carbon resonances were assigned for compositional and configurational sensitivity at tetrad level. Carbon resonances of methine group of methyl acrylate were assigned for compositional sensitivity up to triad level with the help of 2D HSQC spectra. α‐Methyl group of methyl methacrylate was assigned up to triad level of compositional and configurational placements for carbon and proton resonances by 2D HSQC spectroscopy. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 99: 1437–1445, 2006     

Microstructure analysis of methyl acrylate/methyl methacrylate copolymers by two‐dimensional NMR spectroscopy. II

In the present article, a comprehensive two‐dimensional heteronuclear multi bond correlation (HMBC) spectral analysis of methyl acrylate (A)/methyl methacrylate (B) copolymers is reported. The methylene carbon and methine carbon resonances assigned from the 2D HSQC spectroscopy were established by analyzing the two and three bond order couplings with α‐methyl protons, methylene protons, and methine protons. Quaternary carbon resonances of the B unit were assigned by investigating the two bond order couplings with α‐methyl protons and methylene protons. Assignments of carbonyl carbon resonances based on the analysis of three bond couplings with α‐methyl protons and methylene protons are reported. The analyses present comprehensive assignments of the carbonyl carbon resonances showing the critical contribution of 2D HMBC spectroscopy in the indirect analysis of carbon resonances. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

Optimal design and development of a 2-DOF PKM-based machine tool

This paper presents multiobjective optimization of a typical 2-degree-of-freedom (DOF) parallel kinematic machine (PKM) tool that has only single DOF joints. Nondimensional indices, namely global stiffness index (GSI), global conditioning index (GCI), and workspace index, are considered as the objectives for optimization. The indices GSI and GCI depict the variation of stiffness and dexterity of PKM within the workspace. The leg length and distance between two rails on which actuators slide are treated as design variables as these greatly influence the characteristics of PKM. A multiobjective genetic algorithm (MOGA) approach is implemented in MATLAB to find an efficient solution to this complex optimization problem. Fitness function includes inverse kinematics equations, Jacobian and stiffness matrices to compute and optimize the nondimensional indices. First, the optimal value of each index is obtained by single-objective GA. To further improve the results, a hybrid function PATTERNSEARCH is used. This helps to select appropriate boundary conditions for MOGA. To obtain the optimal values of all the three indices, a multiobjective GA is carried out. The results are compared with a conventional exhaustive search method of optimization. The obtained results show that the use of MOGA enhances the quality of the optimization outcome. Secondly, a prototype has been designed and developed with the optimal dimensions. The actual workspace of the PKM and influence of leg collision on the workspace are studied. Finally, a preliminary experimentation was carried out. A comparison between PKM and the three-axis serial kinematic machine tool is presented.     

Improved recognition of control chart patterns using artificial neural networks

Recognition of abnormal patterns in control charts provides clues to reveal potential quality problems in the manufacturing processes. One potentially popular approach for recognizing different control chart patterns (CCPs) is to develop heuristics based on various shape features of the patterns. The advantage of this approach is that the users can easily understand how a particular pattern is identified. However, consistency in the recognition performance is found to be considerably poor in the heuristics approach. Since shape features represent the main characteristics of the patterns in a condensed form, artificial neural network (ANN) with features extracted from the process data as input vector representation can facilitate efficient pattern recognition with a smaller network size. In this paper, a set of seven shape features is selected, whose magnitudes are independent of the process mean and standard deviation under a special representation of the sampling interval in the control chart plot. Based on these features, the CCPs are recognized using a multilayered perceptron neural network trained by back-propagation algorithm. The recognizer can recognize all the eight commonly observed CCPs. Extensive performance evaluation of this recognizer is carried out using simulated pattern data. Numerical results indicate that the developed ANN recognizer can perform well in real time process control applications with respect to both recognition accuracy and consistency.     

Enhancement of pool-boiling heat transfer using nanostructured surfaces on aluminum and copper

Enhanced pool-boiling critical heat fluxes (CHF) at reduced wall superheat on nanostructured substrates are reported. Nanostructured surfaces were realized using a low temperature process, microreactor-assisted-nanomaterial-deposition. Using this technique we deposited ZnO nanostructures on Al and Cu substrates. We observed pool-boiling CHF of 82.5 W/cm² with water as fluid for ZnO on Al versus a CHF of 23.2 W/cm² on bare Al surface with a wall superheat reduction of 25–38 °C. These CHF values on ZnO surfaces correspond to a heat transfer coefficient of ～23,000 W/m² K. We discuss our data and compare the behavior with conventional boiling theory.     

Influence of slip condition on transient laminar flow over an infinite vertical plate with ramped temperature in the presence of chemical reaction and thermal radiation

An analysis was made using the numerical approach of a transient laminar slip flow over an infinite vertical plate with ramped and constant temperatures in which chemical reaction is involved and thermal radiation had to be considered. Slip conditions have caused much concern because of their broad applicability in industry and chemical engineering. By following the finite element technique, the equation of momentum together with the equations of energy and species was numerically solved. The expressions for skin friction, Nusselt number, and Sherwood number are also derived. The variations in fluid velocity, fluid temperature, and species concentration are displayed graphically whereas numerical values of skin friction, Nusselt number, and Sherwood number are presented in tabular form for various values of the pertinent flow parameters. The findings indicate that the radiation has a noticeable impact to a minor intensity of R and is more apparent in the constant condition than in the ramped condition. Radiation and buoyancy effects produce a strong flow near the plate, which is accelerated by slip. Finally, it is shown logically and mathematically that when two buoyancies are opposite and equal in magnitude with equal solutal and thermal diffusions, the flow should be taken as stationary flow in the absence of radiation and the presence/absence of slip.     

Life cycle water consumption and withdrawal requirements of ethanol from corn grain and residues

We assessed the water requirements of ethanol from corn grain and crop residue. Estimates are explicit in terms of sources-green (GW) and blue (BW) water, consumptive and nonconsumptive requirements across the lifecycle, including evapotranspiration, application and conveyance losses, biorefinery uses, and water use of energy inputs, and displaced requirements or credits due to coproducts. Ethanol consumes 50-146 L/vehicle kilometer traveled (VKT) of BW and 1-60 L/VKT of GW for irrigated corn and 0.6 L/VKT of BW and 70-137 L/VKT of GW for rain-fed corn after coproduct credits. Extending the system boundary to consider application and conveyance losses and the water requirements of embodied energy increases the total BW withdrawal from 23% to 38% and BW + GW consumption from 5% to 16%. We estimate that, in 2009, 15-19% of irrigation water is used to produce the corn required for ethanol in Kansas and Nebraska without coproduct credits and 8-10% after credits. Harvesting and converting the cob to ethanol reduces both the BW and GW intensities by 13%. It is worth noting that the use of GW is not without impacts, and the water quantity and water quality impacts at the local/seasonal scale can be significant for both fossil fuel and biofuel.     

Monodispersed and size-controlled multibranched gold nanoparticles with nanoscale tuning of surface morphology

A novel seed-mediated synthetic route to produce multibranched gold nanoparticles is reported, in which it is possible to precisely tune both their size and nanostructuration, while maintaining an accurate level of monodispersion. The nanoscale control of surface nanoroughness/branching, ranging from small bud-like features to elongated spikes, allows to obtain fine tuning of the nanoparticle optical properties, up to the red and near-IR region of the spectrum. Such anisotropic nanostructures were demonstrated to be excellent candidates for SERS applications, showing significantly higher signals with respect to the standard spherical nanoparticles.     

A test method for determining adhesion forces and Hamaker constants of cementitious materials using atomic force microscopy

A method for determining Hamaker constant of cementitious materials is presented. The method involved sample preparation, measurement of adhesion force between the tested material and a silicon nitride probe using atomic force microscopy in dry air and in water, and calculating the Hamaker constant using appropriate contact mechanics models. The work of adhesion and Hamaker constant were computed from the pull-off forces using the Johnson–Kendall–Roberts and Derjagin–Muller–Toropov models. Reference materials with known Hamaker constants (mica, silica, calcite) and commercially available cementitious materials (Portland cement (PC), ground granulated blast furnace slag (GGBFS)) were studied. The Hamaker constants of the reference materials obtained are consistent with those published by previous researchers. The results indicate that PC has a higher Hamaker constant than GGBFS. The Hamaker constant of PC in water is close to the previously predicted value C₃S, which is attributed to short hydration time (≤ 45 min) used in this study.