Mechanical properties of oriented low‐density polyethylene with an oriented lamellar‐stack morphology

A quantitative study was undertaken of the anisotropy of low‐strain mechanical behavior for specially oriented polyethylene with controlled crystalline and lamellar orientation. The samples were prepared by the die drawing of injection‐molded rods of polyethylene and annealing. This produced a parallel lamellar structure for which a simple, three‐dimensional composite laminate model could be used to calculate the expected anisotropy. Experimental data, including X‐ray strain measurements of the lateral crystalline elastic constants, showed good quantitative agreement with the model prediction. The X‐ray strain measurements confirmed that the amorphous regions exert large constraints on the crystalline phase in the lateral directions, where an order of magnitude difference was found between the measured apparent lateral crystalline compliances in the lamellar‐stack sample and the expected values for a perfect crystal. © 2000 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 38: 755–764, 2000     

Simultaneous construction of a polyether backbone and a variety of keto side chains by three‐component polycondensation: An improved method for the use of a variety of silyl enol ethers

For the synthesis of polyethers with a variety of keto side chains in a one‐step reaction, the three‐component polycondensation of dialdehydes, diol disilyl ethers, and silyl enol ethers of ketones was investigated. The method of monomer addition strongly affected the molecular weight of polymers and was optimized to yield high molecular weight polymers by model reactions. A variety of dialdehydes, diol disilyl ethers, and silyl enol ethers were polymerized in the presence of a catalytic amount of triphenylmethyl (trityl) perchlorate in CH₂Cl₂ at −78 °C according to the method of monomer addition. This polymer synthesis was unusual in that it concurrently constructed both the polyether backbone and the keto side chains from three starting compounds. © 2000 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 38: 179–188, 2000     

The Need for Two‐Dimensional Gas Chromatography: Extent of Overlap in One‐Dimensional Gas Chromatograms

The need for two‐dimensional gas chromatography is justified by the extent of peak overlap in one‐dimensional gas chromatograms (GCs) of complex mixtures. Such overlap was predicted long ago by statistical‐overlap theory (SOT). In this paper, SOT is conceptually reviewed and its predictions are shown to be quantitatively accurate. GCs of complex mixtures of polychlorinated biphenyls, pyridine‐ and nitrogen‐containing polynuclear aromatic hydrocarbons, tetrachlorodibenzo‐p‐dioxins and dibenzofurans, fatty acid methyl esters, flavors and fragrances, and naphtha were simulated by commercial GC software on DB‐1, DB‐5, and Stabilwax stationary phases. The numbers of peak maxima in the GCs agreed with predictions of SOT, when the interval of time between successive peaks of pure compounds was described by Poisson statistics. This agreement was realized even though the time intervals actually are deterministic, not statistical. In addition, the numbers of mixture components were predicted with accuracy by regression of peak numbers against SOT. Similar regressions have been reported before, but the theory used here is more sophisticated and its predictions consequently are more accurate. Future directions for finalizing SOT are suggested.     

Proper Tuning of Comprehensive Two‐Dimensional Gas Chromatography (GC×GC) to Optimize the Separation of Complex Oil Fractions

Comprehensive two‐dimensional gas chromatography (GC×GC) is an utterly suitable separation technique for the analysis of complex samples, such as oil fractions. Once the two columns and the operating conditions are properly tuned, the technique is able to provide a detailed characterization of such materials. Some considerations applying to the tuning of a GC×GC system for a specific separation are presented and discussed. The authors present a number of different column sets and conditions which allow the separation of a non‐aromatic hydrocarbon solvent, a kerosene, the light end of a crude oil, and an olefinic fraction, respectively. The highly structured GC×GC chromatograms, together with chemical knowledge about the samples, provide a much more comprehensive characterization of the samples than hitherto possible.     

GC3: Comprehensive Three‐Dimensional Gas Chromatography

Comprehensive three‐dimensional gas chromatography (GC³) is demonstrated using modified GC×GC apparatus. A new thermal modulation scheme employing a single moving heater to operate two thermal modulators is introduced. Considerations of the bandwidth/resolution tradeoff of GC³ show that high‐speed tertiary columns would make GC³ practical, with modest loss of underlying GC×GC peak capacity.     

Finite element solution of three‐dimensional turbulent flows applied to mold‐filling problems

This paper presents a finite element solution algorithm for three‐dimensional isothermal turbulent flows for mold‐filling applications. The problems of interest present unusual challenges for both the physical modelling and the solution algorithm. High‐Reynolds number transient turbulent flows with free surfaces have to be computed on complex three‐dimensional geometries. In this work, a segregated algorithm is used to solve the Navier–Stokes, turbulence and front‐tracking equations. The streamline–upwind/Petrov–Galerkin method is used to obtain stable solutions to convection‐dominated problems. Turbulence is modelled using either a one‐equation turbulence model or the κ–ε two‐equation model with wall functions. Turbulence equations are solved for the natural logarithm of the turbulence variables. The change of dependent variables allows for a robust solution algorithm and good predictions even on coarse meshes. This is very important in the case of large three‐dimensional applications for which highly refined meshes result in untreatable large numbers of elements. The position of the flow front in the mold cavity is computed using a level set approach. Finally, equations are integrated in time using an implicit Euler scheme. The methodology presents the robustness and cost effectiveness needed to tackle complex industrial applications. Copyright © 2000 John Wiley & Sons, Ltd.     

Application of artificial neural network to evaluation of dimensional accuracy of 3D-printed polylactic acid parts

Additive manufacturing (AM) has begun to replace traditional fabrication because of its advantages, such as easy manufacturing of parts with complex geometry, and mass production. The most important limitation of AM is that dimensional accuracy cannot be achieved in all parts. Dimensional accuracy is essential for high reliability, high performance, and useful final products. This study investigates the impact of printing parameters on the dimensional accuracy of samples fabricated through fused deposition modeling (FDM), an additive manufacturing (AM) method utilizing polylactic acid (PLA) material. The experimental design process was performed using Taguchi methodology. ANOVA was used to determine the most important parameter affecting accuracy. Based on experimental studies, the optimal printing parameters for parts are determined as follows: concentric infill pattern, 3 mm wall thickness, 70% infill density, and a layer thickness of 200 μm. Artificial neural network (ANN) was used in the evaluation and prediction of the results. The R-square (R²) performance evaluation criterion was above 95% from the ANN results. This value shows that the results are significant. The data acquired from this study may assist in identifying optimal parameters that contribute to the fabrication of samples with high dimensional accuracy using the FDM method.     

Optimization and Validation of a Headspace Solid-Phase Microextraction with Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometric Detection for Quantification of Trace Aroma Compounds in Chinese Liquor (Baijiu)

The detection of trace aroma compounds in samples with complex matrices such as Chinese liquor (Baijiu) requires a combination of several methods, which makes the analysis process very complicated. Therefore, a headspace solid-phase microextraction (HS-SPME) method coupled with two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) was developed for the quantitation of a large number of trace compounds in Baijiu. Optimization of extraction conditions via a series of experiments revealed that dilution of the alcohol content of 8 mL of Baijiu to 5%, followed by the addition of 3.0 g of NaCl and subsequent SPME extraction with DVB/CAR/PDMS fiber coating over 45 min at 45 °C was the most suitable. To check the matrix effects, various model Baijiu matrices were investigated in detail. The quantitative method was established through an optimized model synthetic solution, which can identify 119 aroma compounds (esters, alcohols, fatty acids, aldehydes and ketones, furans, pyrazines, sulfur compounds, phenols, terpenes, and lactones) in the Baijiu sample. The developed procedure provided high recovery (86.79–117.94%), good repeatability (relative standard deviation < 9.93%), high linearity (R² > 0.99), and lower detection limits than reported methods. The method was successfully applied to study the composition of volatile compounds in different types of Baijiu. This research indicated that the optimized HS-SPME–GC×GC-TOFMS method was a valid and accurate procedure for the simultaneous determination of different types of trace compounds in Baijiu. This developed method will allow an improved analysis of other samples with complex matrices.