IR transmission prediction,processing, and characterization of dense La2Ce2O7

High-throughput computation, based on density functional theory (HT-DFT), is used to predict the bounds for optical transparency, from the ultraviolet to the infrared, for materials in the pyrochlore family. The HT-DFT approach adopted here uses an initial screening from Materials-Project database, with millions of calculated properties. Band gaps and phonon spectra were calculated from selected pyrochlore crystal structures taken from the Materials Project database. Short and long wavelength bounds for optical transparency were calculated for chemistries with stable, cubic structures. The calculations predict that La₂Ce₂O₇ has one of the broadest range of transparency for the pyrochlore family. Based on these calculations, dense polycrystalline samples of La₂Ce₂O₇ were produced by sintering and hot-isostatic pressing. Transparency was characterized by methods that did not require large samples with high optical quality, obtaining 7.15 and 7.5 µm at 95% and 90% normalized transmittance, respectively. Bandgap calculations suggest a lower bound of UV transparency cut-off of 0.3 µm. The infrared wavelength cut-off is higher than that reported for other pyrochlores, and higher than for yttria, zirconia, or other common infrared transparent ceramics. We discuss our prediction and characterization methods as well as the suitability of pyrochlores for mid- and far-infrared optical applications.     

Modularisierung von Gaswäschern für die CO2‐Entfernung aus Biogas

Modularization has been identified as one of the research fields of the ?50 % idea”?. A development methodology for modules must consider both the economies of scale for investment costs and costs of operation and maintenance. In this paper, the impact of an absorber module, which is offered as discretized diameter scaling, on the total process is investigated at the example of the CO₂ separation from biogas. The simulation shows the effect of this approach to the stripper diameter and the energy demand of the process. The calculations form the basis for applying cost models.     

Pyrolysis gas chromatographic analyses of untreated and flameproofed wools

The thermal degradation of untreated and wool treated by various flame retardants, using pyrolysis gas chromatography, has been studied. The concentration of CO, CO₂ and benzene produced does not appear to be affected by the flame retardants studied. The latter slightly decreases the concentration of toluene produced while the HCN production depends on the chemical composition of the retardant and on the temperature of exposure.     

Automated spectral smoothing with spatially adaptive penalized least squares

A variety of data smoothing techniques exist to address the issue of noise in spectroscopic data. The vast majority, however, require parameter specification by a knowledgeable user, which is typically accomplished by trial and error. In most situations, optimized parameters represent a compromise between noise reduction and signal preservation. In this work, we demonstrate a nonparametric regression approach to spectral smoothing using a spatially adaptive penalized least squares (SAPLS) approach. An iterative optimization procedure is employed that permits gradual flexibility in the smooth fit when statistically significant trends based on multiscale statistics assuming white Gaussian noise are detected. With an estimate of the noise level in the spectrum the procedure is fully automatic with a specified confidence level for the statistics. Potential application to the heteroscedastic noise case is also demonstrated. Performance was assessed in simulations conducted on several synthetic spectra using traditional error measures as well as comparisons of local extrema in the resulting smoothed signals to those in the true spectra. For the simulated spectra, a best case comparison with the Savitzky-Golay smoothing via an exhaustive parameter search was performed while the SAPLS method was assessed for automated application. The application to several dissimilar experimentally obtained Raman spectra is also presented.     

Surface temperature measurements on burning wood specimens in the Cone Calorimeter and the effect of grain orientation

Surface temperatures were measured on dry Douglas fir sapwood specimens during Cone Calorimeter tests using thermocouples and an infra-red pyrometer. Good agreement between the thermocouples and the pyrometer was obtained when (1) the emissivity was assumed to be 1.0 and (2) the thermocouples were in good contact with the surface and were not located in the proximity of a fissure. The major fissures were normal to the grain of the wood and the volatiles vented through the fissures. Char oxidation in the region between the vertical fissures resulted in higher surface temperatures.     

Alternating Cationic-Hydrophobic Peptide/Peptoid Hybrids: Influence of Hydrophobicity on Antibacterial Activity and Cell Selectivity

The influence of hydrophobicity on antibacterial activity versus the effect on the viability of mammalian cells for peptide/peptoid hybrids was examined for oligomers based on the cationic Lys-like peptoid residue combined with each of 28 hydrophobic amino acids in an alternating sequence. Their relative hydrophobicity was correlated to activity against both Gram-negative and Gram-positive species, human red blood cells, and HepG2 cells. This identified hydrophobic side chains that confer potent antibacterial activity (e. g., MICs of 2–8 μg/mL against E. coli) and low toxicity toward mammalian cells (<10 % hemolysis at 400 μg/mL and IC₅₀>800 μg/mL for HepG2 viability). Most peptidomimetics retained activity against drug-resistant strains. These findings corroborate the hypothesis that for related peptidomimetics two hydrophobicity thresholds may be identified: i) it should exceed a certain level in order to confer antibacterial activity, and ii) there is an upper limit, beyond which cell selectivity is lost. It is envisioned that once identified for a given subclass of peptide-like antibacterials such thresholds can guide further optimisation.     

Dynamic Control of Light Direction Enabled by Stimuli‐Responsive Liquid Crystal Gratings

The ability to control light direction with tailored precision via facile means is long‐desired in science and industry. With the advances in optics, a periodic structure called diffraction grating gains prominence and renders a more flexible control over light propagation when compared to prisms. Today, diffraction gratings are common components in wavelength division multiplexing devices, monochromators, lasers, spectrometers, media storage, beam steering, and many other applications. Next‐generation optical devices, however, demand nonmechanical, full and remote control, besides generating higher than 1D diffraction patterns with as few optical elements as possible. Liquid crystals (LCs) are great candidates for light control since they can form various patterns under different stimuli, including periodic structures capable of behaving as diffraction gratings. The characteristics of such gratings depend on several physical properties of the LCs such as film thickness, periodicity, and molecular orientation, all resulting from the internal constraints of the sample, and all of these are easily controllable. In this review, the authors summarize the research and development on stimuli‐controllable diffraction gratings and beam steering using LCs as the active optical materials. Dynamic gratings fabricated by applying external field forces or surface treatments and made of chiral and nonchiral LCs with and without polymer networks are described. LC gratings capable of switching under external stimuli such as light, electric and magnetic fields, heat, and chemical composition are discussed. The focus is on the materials, designs, applications, and future prospects of diffraction gratings using LC materials as active layers.     

Two-dimensional correlation analysis

This tutorial reviews the recent computational advances in two-dimensional (2D) correlation spectroscopy, presents the theory, and provides examples applying 2D correlation analysis. Two-dimensional correlation analysis is a method for visualizing the relationships among the variables in multivariate data and their temporal behavior by applying the complex cross-correlation function. This function measures correlations that occur at the same rate or frequency with respect to the data acquisition time. The complex cross-correlation function yields real and imaginary components that contain information about the phase behavior of the variables. The real component provides information about mutually dependent in-phase variations. Variations that occur out-of-phase (with time lags or leads) are given by the imaginary component. Two-dimensional correlation analysis is a general analysis method that can be used for the treatment of data from a variety of applications including image, distribution, environmental, and kinetic analysis.