In-line fiber-optic near-infrared spectroscopy: Monitoring of rheological properties in an extrusion process. Part II.

In an extrusion process, linear viscoelastic properties of molten poly(ethylene vinyl acetate) (EVA) copolymers, which have one principal factor of variation, can be estimated from in-line near-infrared (NIR) spectra. The NIR transmission spectra of molten polymer flow stream were collected in a flow cell attached to a single-screw extruder. Dynamic rheological functions obtained from linear viscoelastic measurements, for example, the complex viscosity response, are regressed against the NIR spectra. The primary method for the rheological measurements involved sinusoidal, oscillatory shear experiments at varying angular frequencies using a cone-and-plate viscometer. All measurements were carried out on molten EVA polymers at 200°C. Calibration models were built on spectra in the carbon—hydrogen (C—H) vibrational stretch, first overtone, wavelength region (1620–1840 nm), and these models were used to predict the rheological material functions of copolymer samples. The robustness of these models was tested on independent prediction samples that had not been included in the calibration models. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 68 :873–889, 1998     

In-line measurement of tempered cocoa butter and chocolate by means of near-infrared spectroscopy

In the present work cocoa butter and chocolate were precrystallized by means of a newly developed shear crystallizer. The shear crystallizer was integrated into a circular loop. The handling of precrystallized cocoa butter showed a high dependency on the timing of applied analysis. Differential scanning calorimetry, calorimetry, rheometry, and in-line near-infrared (NIR) were all directly influenced by the fat crystal structure. Nevertheless, for cocoa butter it was shown that mechanical energy input (rpm) had a significant influence on viscosity, melting enthalpy, and slope at the second point of inflection of a temper curve. Experiments with cocoa butter at constant exit temperature showed a linear increase of viscosity between 0.1 and 0.8 Pa·s in the range of 300 to 1300 rpm. Melting enthalpy increased in the same rpm interval from 0.02 to 2.5 J/g. Solidification time (from 4.5 to 0.5 min) and slope (from 0.82 to 0.15, second point of inflection of temper curve) consequently decreased (both with exponential approximation). For cocoa butter, slope and solidification time correlated linearly whereas solidification time and viscosity followed a power law fit. This proved that defined relationships exist between rheological data and data from temper curve measurements. Viscosity was linearly dependent on crystal content. By means of NIR spectroscopy good correlation models for cocoa butter viscosity, enthalpy (crystal content), and slope values were found. For precrystallized chocolate, analytical values such as viscosity and slope values were detected off-line and used for calibration of NIR spectroscopy.     

In-line fiber-optic near-infrared spectroscopy: Monitoring of rheological properties in an extrusion process. Part I.

In-line monitoring of chemical processes is desired for its numerous advantages, such as lesser waste, lower developmental cycle time, and lesser costs. In this study, a methodology is presented for estimating polymer rheological properties using fiber-optic near-infrared (NIR) spectroscopy. Predictive calibration models are developed for simultaneous, in-line monitoring of polymer melt flow index (MI) and comonomer concentration for a system of poly(ethylene vinyl acetate) copolymers. The NIR spectra of flowing, molten poly(ethylene vinyl acetate) (EVA) copolymers are collected in a flow cell attached to a single-screw extruder. Multivariate statistical regression analysis is presented for correlation of MI and absorbance in the methylene (C—H) stretch, first overtone NIR wavelength region (1620–1840 nm). Results for simultaneous, real-time monitoring of MI and comonomer composition are discussed in detail. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 68: 859–872, 1998     

Modeling of oil near-infrared spectroscopy based on similarity and transfer learning algorithm

Near-infrared spectroscopy mainly reflects the frequency-doubled and total-frequency absorption information of hydrogen-containing groups (0 -H, C-H, N-H, S-H) in organic molecules for near-infrared lights with different wavelengths, so it is applicable to testing of most raw materials and products in the field of petrochemicals. However, the modeling process needs to collect a large number of laboratory analysis data. There are many oil sources in China, and oil properties change frequently. Modeling of each raw material is not only unfeasible but also will affect its engineering application efficiency. In order to achieve rapid modeling of near-infrared spectroscopy and based on historical data of different crude oils under different detection conditions, this paper discusses about the feasibility of the application of transfer learning algorithm and makes it possible that transfer learning can assist in rapid modeling using certain historical data under similar distributions under a small quantity of new data. In consideration of the requirement of transfer learning for certain similarity of different datasets, a transfer learning method based on local similarity feature selection is proposed. The simulation verification of spectral data of 13 crude oils measured by three different probe detection methods is performed. The effectiveness and application scope of the transfer modeling method under different similarity conditions are analyzed.     

Cold-model investigation of the effect of dispersed phase inlet on the dispersion uniformity in a liquid-liquid cyclone reactor for ionic liquid-catalyzed isobutene alkylation

A liquid-liquid cyclone reactor was proposed for ionic liquid-catalyzed isobutane alkylation to improve the mixing efficiency and accelerate the separation between alkylate and ionic liquid. The Eulerian-Eulerian multiphase flow model and Reynolds stress model (RSM) were used to simulate the flow field in the reactor. A parameter, named the dispersion uniformity of dispersed phase, β, was used to quantify the dispersibility of the dispersed phase in the reaction chamber of the reactor. Moreover, the effects of the structural parameters of the dispersed phase inlet (slot) on the dispersion uniformity of the dispersed phase were investigated. As can be seen from the results, the angle of the slot has an effect on the inlet velocity direction, while the other structural parameters have an effect on the inlet velocity magnitude. The shear force is the impetus for the dispersion of the dispersed phase into the continuous phase, and the relative velocity is the cause of the shear force. Therefore, by analyzing the effect of the structural parameters of the slot on the dispersion uniformity, it can be deduced that the dispersion of the dispersed phase performs well under a suitable inlet velocity ratio range of the continuous phase to the dispersed phase (2.5-3.5).     

Comparative particle size determination of phenacetin bulk powder by using Kubelka-Munk theory and principal component regression analysis based on near-infrared spectroscopy

Purpose: The purpose of this study is to investigate the effect of particle size on Kubelka-Munk theoretical light diffusion of NIR spectra. And a chemoinfometrical method for quantitative determination of particle size of phenacetin crystalline powder based on Fourier-transformed near-infrared (FT-NIR) spectroscopy was established. Method: The sample powders of phenacetin were obtained by sieving using 37-590 μm screens. NIR spectra were taken with a total 60 NIR data points by using a FT-NIR spectrometer. Results: The NIR absorption patterns were almost identical for the samples. However, the base line of the spectrum was observed to increase with decreasing sample powder particle size. The scatter coefficient constants (S) were calculated from NIR spectra based on Kubelka and Munk light scattering theory. The S values determined were found to be constant within the wavenumbers studied; i.e., 4000-10 000 cm⁻¹. However, this light scatter coefficient, S, for phenacetin particle was found to be inversely proportional to particle size. Subsequently, the principal component regression (PCR) analysis based on a three-principal component model was applied in the analyses of NIR spectra of phenacetin powder samples with various particle sizes. By applying this method, the particle size for phenacetin can be estimated form the light scatter coefficient, S. The resulting plot showed a linear relationship between the predicted and actual particle size with a slope of 0.9167, an intercept of 20.61, and a correlation coefficient of 0.9147. The loading vector of PC1 showed a plateau at 4500-10 000 cm⁻¹, and the score of PC1 increased with increase of particle size. Conclusion: Quantitative particle size evaluation of phenacetin crystalline powder using the PCR method based on NIR spectra was useful for practical purpose in pharmaceutical industry, and their background was clarified by using Kubelka-Munk scattering theory.     

Dielectric spectroscopy during extrusion processing of polymer nanocomposites: a high throughput processing/characterization method to measure layered silicate content and exfoliation

Dielectric spectroscopy was conducted during extrusion processing of polyamide-6 (PA6) and layered silicate/polyamide-6 nanocomposites. Dielectric dispersion parameters were identified that appear sensitive to layered silicate concentration and degree of exfoliation. Specific to measuring layered silicate concentration is that the Maxwell-Wagner strength of dispersion, Δε_mw, increases linearly with the % mass fraction layered silicate content. This relationship is independent of exfoliation resulting in nanomorphology-averaged Δε_mw values that reflect layered silicate concentration; i.e. 12,800±519 indicates 1.29% mass fraction of a layered silicate in PA6. The nanomorphology is primarily reflected in the Maxwell-Wagner characteristic relaxation frequency value, f_mw, where, for example, 80.4±5 Hz indicates a mixed intercalated/exfoliated nanomorphology. However, following the nanomorphology with the f_mw value can in some cases be complicated because different nanomorphologies can yield the same f_mw value. In these cases we have found that there is a significant difference in the conductive resistance and segmental mobility of these polymers, as indicated by the σ_DC and fα values. For example, the intercalated and exfoliated nanocomposites have a f_mw value of about 5.1 Hz, but the exfoliated nanocomposites have σ_DC and fα values that are much larger than determined for the intercalated nanocomposites.