Microwave‐promoted rapid synthesis of new optically active poly(amide imide)s derived from N,N′‐(pyromellitoyl)‐bis‐L‐isoleucine diacid chloride and aromatic diamines

A pyromellitic dianhydride (benzene‐1,2,4,5‐tetracarboxylic dianhydride) was reacted with L ‐isoleucine in acetic acid, and the resulting imide acid [N,N′‐(pyromellitoyl)‐bis‐L ‐isoleucine] (4) was obtained in a high yield. 4 was converted into N,N′‐(pyromellitoyl)‐bis‐L ‐isoleucine diacid chloride by a reaction with thionyl chloride. The polycondensation reaction of this diacid chloride with several aromatic diamines, including 1,4‐phenylenediamine, 4,4′‐diaminodiphenyl methane, 4,4′‐diaminodiphenylsulfone (4,4′‐sulfonyldianiline), 4,4′‐diaminodiphenylether, 2,4‐diaminotoluene, and 1,3‐phenylenediamine, was developed with two methods. The first method was polymerization under microwave irradiation, and the second method was low‐temperature solution polymerization, with trimethylsilyl chloride used as an activating agent for the diamines. The polymerization reactions proceeded quickly and produced a series of optically active poly(amide imide)s with good yields and moderate inherent viscosities of 0.17–0.25 dL/g. All of the aforementioned polymers were fully characterized by IR, elemental analyses, and specific rotation. Some structural characterization and physical properties of these optically active poly(amide imide)s are reported. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 951–959, 2004     

Direct polycondensation of N‐trimellitylimido‐L‐isoleucine with aromatic diamines

N‐Trimellitylimido‐L ‐isoleucine (3) was prepared from the reaction of trimellitic anhydride with L ‐isoleucine [L ‐2‐amino‐3‐methylvalerianic acid or (2S,3S)‐2‐amino‐3‐methyl‐n‐valerinic acid] in an N,N‐dimethylformamide solution at the refluxing temperature. The direct polycondensation reaction of the monomer imide diacid (3) with 1,4‐phenylenediamine, 4,4′‐diaminodiphenylmethane, 4,4′‐diaminodiphenylsulfone, diaminodiphenylether, 1,5‐naphthalendiamine, 2,4‐diaminotoluene, and 1,3‐phenylenediamine was performed in a medium consisting of triphenyl phosphite, N‐methyl‐2‐pyrolidone (NMP), pyridine, and calcium chloride. The polycondensation was performed under two different conditions: in one method, the reaction mixture was heated in an NMP solution at 60, 90, and then 130°C for different periods of time, and in the other method, the reaction mixture was refluxed only for 1 min in the same solvent. The resulting poly(amide imide)s (PAIs), with inherent viscosities of 0.21–0.37 dL/g, were obtained in high yields. All of these compounds were fully characterized by IR spectra, elemental analyses, and specific rotation measurements. Some structural characterizations and physical properties of these new optically active PAIs were examined. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 116–122, 2003     

Model-based design of experiments for polyether production from bio-based 1,3-propanediol

Sequential model-based design of experiments (MDBOE) accounts for information from previous experiments when selecting conditions for new experiments. In the current study, sequential MBDOE is used to select operating conditions for experiments in a batch-reactor that produces bio-based polytrimethylene ether glycol (PO3G). These Bayesian A-optimal experiments are designed to obtain improved estimates of 70 fundamental-model parameters, while accounting for industrial data from eight previous runs. Settings are selected for three decision variables: reactor temperature, initial catalyst level, and initial water concentration. If only one new experiment is conducted, it should be run at high temperature, with relatively high concentrations of catalyst and initial water. When two new runs are conducted, one should use an intermediate catalyst concentration. The effectiveness of the proposed MBDOE approach is tested using Monte-Carlo simulations, revealing that the selected experiments are superior compared to experiments selected randomly from corners of the permissible design space.     

Application of different CFD multiphase models to investigate effects of baffles and nanoparticles on heat transfer enhancement

In this work, the effect of baffles in a pipe on heat transfer enhancement was studied using computational fluid dynamics (CFD) in the presence of Al₂O₃ nanoparticles which are dispersed into water. Fluid flow through the horizontal tube with uniform heat flux was simulated numerically and three dimensional governing partial differential equations were solved. To find an accurate model for CFD simulations, the results obtained by the single phase were compared with those obtained by three different multiphase models including Eulerian, mixture and volume of fluid (VOF) at Reynolds numbers in range of 600 to 3000, and two different nanoparticle concentrations (1% and 1.6%). It was found that multiphase models could better predict the heat transfer in nanofluids. The effect of baffles on heat transfer of nanofluid flow was also investigated through a baffled geometry. The numerical results show that at Reynolds numbers in the range of 600 to 2100, the heat transfer of nanofluid flowing in the geometry without baffle is greater than that of water flowing through a tube with baffle, whereas the difference between these effects (nanofluid and baffle) decreases with increasing the Reynolds number. At higher Reynolds numbers (2100–3000) the baffle has a greater effect on heat transfer enhancement than the nanofluid.     

Studying the Effects of Nucleating Agents on Texture Modification of Puffed Corn‐Fish Snack

To improve textural attributes of puffed corn‐fish snack, the effects of 1%, 1.5%, and 2% of calcium carbonate, magnesium silicate (talc), sodium bicarbonate as well as 5% and 10% of wheat bran (as the nucleating materials) on textural attributes were studied. Sensory evaluation, bulk density, expansion ratio, maximum force, and count peaks were measured using the Kramer test. The results showed that all of the additives except bran significantly enhanced the texture. Among them, talc at 0.5% was the best to enhance the density and expansion ratio. Effects of using 0.5% talc on puffed corn‐fish snack microstructure were studied using scanning electron microscopy. The average cell diameter of 109 ± 48 μm and cell numbers per square centimeter of 67.4 for talc‐treated products were obtained, while for nontalc‐treated extrudates, average cell diameter of 798 ± 361 μm and cell numbers per square centimeter of 13.9 were found. Incorporation of 0.5% w/w of magnesium silicate reduced (7‐fold) the average cell diameter while increased (4‐fold) the cell number.     

Studies on unfolding energy spectra of neutrons using maximumlikelihood expectation–maximization method

Energy spectra of neutrons are important for identification of unknown neutron sources and for determination of the equivalent dose. Although standard energy spectra of neutrons are available in some situations, e.g.,for some radiotherapy treatment machines, they are unknown in other cases, e.g., for photoneutrons created in radiotherapy rooms and neutrons generated in nuclear reactors. In situations where neutron energy spectra need to be determined, unfolding the required neutron energy spectra using the Bonner sphere spectrometer(BSS) and nested neutron spectrometer(NNS) has been found promising. However, without any prior knowledge on the spectra, the unfolding process has remained a tedious task.In this work, a standalone numerical tool named‘‘NRUunfold' was developed which could satisfactorily unfold neutron spectra for BSS or NNS, or any other systems using similar detection methodology. A generic and versatile algorithm based on maximum-likelihood expectation–maximization method was developed and benchmarked against the widely used STAY'SL algorithm which was based on the least squares method. The present method could output decent results in the absence of precisely calculated initial guess, although it was also remarked that employment of exceptionally bizarre initial spectra could lead to some unreasonable output spectra. The neutron count rates computed using the manufacturer's response functions were used for sensitivity studies. The present NRUunfold code could be useful for neutron energy spectrum unfolding for BSS or NNS applications in the absence of a precisely calculated initial guess.     

High performance multilayered nano-crystalline silicon/silicon-oxide light-emitting diodes on glass substrates

A low-temperature hydrogenation-assisted sequential deposition and crystallization technique is reported for the preparation of nano-scale silicon quantum dots suitable for light-emitting applications. Radio-frequency plasma-enhanced deposition was used to realize multiple layers of nano-crystalline silicon while reactive ion etching was employed to create nano-scale features. The physical characteristics of the films prepared using different plasma conditions were investigated using scanning electron microscopy, transmission electron microscopy, room temperature photoluminescence and infrared spectroscopy. The formation of multilayered structures improved the photon-emission properties as observed by photoluminescence and a thin layer of silicon oxy-nitride was then used for electrical isolation between adjacent silicon layers. The preparation of light-emitting diodes directly on glass substrates has been demonstrated and the electroluminescence spectrum has been measured.     

Using prior parameter knowledge in model-based design of experiments for pharmaceutical production

Sequential model-based design of experiments (MBDoE) uses information from previous experiments to select new experimental conditions. Computation of MBDoE objective functions can be impossible due to a noninvertible Fisher information matrix ( FIM ). Previously, we evaluated a leave-out (LO) approach that designed experiments by removing problematic model parameters from the design process. Unfortunately, the LO approach can be computationally expensive due to its iterative nature. In this study, we propose a simplified Bayesian approach that makes the FIM invertible by accounting for prior parameter information. We compare the proposed simplified Bayesian approach to the LO approach for sequential A-optimal design. Results from a pharmaceutical case study show that the proposed approach is superior, on average, for design of experiments. We suggest that simplified Bayesian MBDoE should be combined with a subset-selection-based approach for parameter estimation. This combined methodology gave the best results on average for the case study.