Complete filling of zeolite frameworks with polyalkynes formed in situ by transition-metal ion catalysts

We report the use of transition-metal-exchanged zeolites as media for the catalytic formation and encapsulation of both polyethyne and polypropyne, and computer modeling studies on the composites so formed. Alkyne gas was absorbed into the pores of zeolite Y (Faujasite) exchanged with transition-metal cations [Fe(II), Co(II), Cu(II), Ni(II), and Zn(II)]. Ni(II) and Zn(II) were found to be the most efficient for the production of poly-ynes. These cations were also found to be effective in polymer generation when exchanged in zeolites mordenite and beta. The resulting powdered samples were characterized by FTIR, Raman, diffuse reflectance electronic spectroscopy, TEM, and elemental analysis, revealing, nearly complete loading of the zeolite channels for the majority of the samples. Based on the experimental carbon content, we have derived the percentage of channel filling, and the proportion of the channels containing a single polymer chain for mordenite. Experimentally, the channels for Y are close to complete filling for polyethyne (PE) and polypropyne (PP), and this is also true for polyethyne in mordenite. Computer modeling studies using Cerius2 show that the channels of mordenite can only accept a single polymer chain of PP, in which case these channels are also completely filled.

Whole crop cereals 2. Prediction of apparent digestibility and energy value from in vitro digestion techniques and near infrared reflectance spectroscopy and of chemical composition by near infrared reflectance spectroscopy

Samples of whole crop wheat (WCW, n = 134) and whole crop barley (WCB, n = 16) were collected from commercial farms in the UK over a 2-year period (2003/2004 and 2004/2005). Near infrared reflectance spectroscopy (NIRS) was compared with laboratory and in vitro digestibility measures to predict digestible organic matter in the dry matter (DOMD) and metabolisable energy (ME) contents measured in vivo using sheep. Spectral models using the mean spectra of two scans were compared with those using individual spectra (duplicate spectra). Overall NIRS accurately predicted the concentration of chemical components in whole crop cereals apart from crude protein. ammonia-nitrogen, water-soluble carbohydrates, fermentation acids and solubility values. In addition. the spectral models had higher prediction power for in vivo DOMD and ME than chemical components or in vitro digestion methods. Overall there Was a benefit from the use of duplicate spectra rather than mean spectra and this was especially so for predicting in vivo DOMD and ME where the sample population size was smaller. The spectral models derived deal equally well with WCW and WCB and Would he of considerable practical value allowing rapid determination of nutritive value of these forages before their use in diets of productive animals. (C) 2008 Elsevier B.V. All rights reserved.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage

The microbial fermentability, ruminal degradability and digestibility of 48 maize silages were determined using in vitro gas production (GP), in situ degradability and in vitro digestibility procedures. The silages were produced from forage maize harvested throughout the summer of 1998, and represent a wide range of physiological maturities. Large variations among samples were observed for all biological parameters, with the exception of in vitro digestibility and the asymptote of in vitro GP. The potential of near infrared reflectance spectroscopy (NIRS) to predict the biological parameters measured was determined by regression of the biological data against the respective spectral profile. NIRS demonstrated only a moderate ability (R-2 > 0.60-0.80) to predict in vitro digestibility, modelled kinetics of gas production (excluding the asymptote of gas production) and the modelled ruminally soluble dry matter (DM) fraction. Calibration statistics for remaining biological parameters were unacceptably poor (R-2 = 0.60). (C) 2004 Elsevier B.V. All rights reserved.

Derivation of an urban materials spectral library through emittance and reflectance spectroscopy

Recent advances in thermal infrared remote sensing include the increased availability of airborne hyperspectral imagers (such as the Hyperspectral Thermal Emission Spectrometer, HyTES, or the Telops HyperCam and the Specim aisaOWL), and it is planned that an increased number spectral bands in the long-wave infrared (LWIR) region will soon be measured from space at reasonably high spatial resolution (by imagers such as HyspIRI). Detailed LWIR emissivity spectra are required to best interpret the observations from such systems. This includes the highly heterogeneous urban environment, whose construction materials are not yet particularly well represented in spectral libraries. Here, we present a new online spectral library of urban construction materials including LWIR emissivity spectra of 74 samples of impervious surfaces derived using measurements made by a portable Fourier Transform InfraRed (FTIR) spectrometer. FTIR emissivity measurements need to be carefully made, else they are prone to a series of errors relating to instrumental setup and radiometric calibration, which here relies on external blackbody sources. The performance of the laboratory-based emissivity measurement approach applied here, that in future can also be deployed in the field (e.g. to examine urban materials in situ), is evaluated herein. Our spectral library also contains matching short-wave (VIS–SWIR) reflectance spectra observed for each urban sample. This allows us to examine which characteristic (LWIR and) spectral signatures may in future best allow for the identification and discrimination of the various urban construction materials, that often overlap with respect to their chemical/mineralogical constituents. Hyperspectral or even strongly multi-spectral LWIR information appears especially useful, given that many urban materials are composed of minerals exhibiting notable reststrahlen/absorption effects in this spectral region. The final spectra and interpretations are included in the London Urban Micromet data Archive (LUMA; http://LondonClimate.info/LUMA/SLUM.html).

The relationship between diffuse spectral reflectance of the soil and its cation exchange capacity is scale-dependent

Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

Notations and conventions in molecular spectroscopy: part 2. Symmetry notation

The field of Molecular Spectroscopy was surveyed in order to determine a set of conventions and symbols which are in common use in the spectroscopic literature. This document, which is Part 2 in a series, establishes the notations and conventions used for the description of symmetry in rigid molecules, using the Schoenflies notation. It deals firstly with the symmetry operators of the molecular point groups (also drawing attention to the difference between symmetry operators and elements). The conventions and notations of the molecular point groups are then established, followed by those of the representations of these groups as used in molecular spectroscopy. Further parts will follow, dealing inter alia with permutation and permutation-inversion symmetry notation, vibration-rotation spectroscopy and electronic spectroscopy.

In situ observation of lithium hydride hydrolysis by DRIFT spectroscopy

Polycrystalline LiH was studied in situ using diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy to investigate the effect water vapour has on the rate of production of the corrosion products, particularly LiOH. The reaction rate of the formation of surface LiOH was monitored by measurement of the hydroxyl (OH) band at 3676 cm(-1). The initial hydrolysis rate of LiH exposed to water vapour at 50% relative humidity was found to be almost two times faster than LiH exposed to water vapour at 2% relative humidity. The hydrolysis rate was shown to be initially very rapid followed by a much slower, almost linear rate. The change in hydrolysis rate was attributed to the formation of a coherent layer of LiOH on the LiH surface. Exposure to lower levels of water vapour appeared to result in the formation of a more coherent corrosion product, resulting in effective passivation of the surface to further attack from water. Crown Copyright (c) 2007 Published by Elsevier B.V. All rights reserved.

Identification of metabolites in human hepatic bile using 800 MHz 1H NMR spectroscopy, HPLC-NMR/MS and UPLC-MS

The first application of high field NMR spectroscopy (800 MHz for 1H observation) to human hepatic bile (as opposed to gall bladder bile) is reported. The bile sample used for detailed investigation was from a donor liver with mild fat infiltration, collected during organ retrieval prior to transplantation. In addition, to focus on the detection of bile acids in particular, a bile extract was analysed by 800 MHz 1H NMR spectroscopy, HPLC-NMR/MS and UPLC-MS. In the whole bile sample, 40 compounds have been assigned with the aid of two-dimensional 1H–1H TOCSY and 1H–13C HSQC spectra. These include phosphatidylcholine, 14 amino acids, 10 organic acids, 4 carbohydrates and polyols (glucose, glucuronate, glycerol and myo-inositol), choline, phosphocholine, betaine, trimethylamine-N-oxide and other small molecules. An initial NMR-based assessment of the concentration range of some key metabolites has been made. Some observed chemical shifts differ from expected database values, probably due to a difference in bulk diamagnetic susceptibility. The NMR spectra of the whole extract gave identification of the major bile acids (cholic, deoxycholic and chenodeoxycholic), but the glycine and taurine conjugates of a given bile acid could not be distinguished. However, this was achieved by HPLC-NMR/MS, which enabled the separation and identification of ten conjugated bile acids with relative abundances varying from approximately 0.1% (taurolithocholic acid) to 34.0% (glycocholic acid), of which, only the five most abundant acids could be detected by NMR, including the isomers glycodeoxycholic acid and glycochenodeoxycholic acid, which are difficult to distinguish by conventional LC-MS analysis. In a separate experiment, the use of UPLC-MS allowed the detection and identification of 13 bile acids. This work has shown the complementary potential of NMR spectroscopy, MS and hyphenated NMR/MS for elucidating the complex metabolic profile of human hepatic bile. This will be useful baseline information in ongoing studies of liver excretory function and organ transplantation.

Modelling spectral reflectance of open cork oak woodland: a simulation analysis of the effects of vegetation structure and background

This study analyses the influence of vegetation structure (i.e. leaf area index and canopy cover) and seasonal background changes on moderate-resolution imaging spectrometer (MODIS)-simulated reflectance data in open woodland. Approximately monthly spectral reflectance and transmittance field measurements (May 2011 to October 2013) of cork oak tree leaves (Quercus suber) and of the herbaceous understorey were recorded in the region of Ribatejo, Portugal. The geometric-optical and radiative transfer (GORT) model was used to simulate MODIS response (red, near-infrared) and to calculate vegetation indices, investigating their response to changes in the structure of the overstorey vegetation and to seasonal changes in the understorey using scenarios corresponding to contrasting phenological status (dry season vs. wet season). The performance of normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) is discussed. Results showed that SAVI and EVI were very sensitive to the emergence of background vegetation in the wet season compared to NDVI and that shading effects lead to an opposing trend in the vegetation indices. The information provided by this research can be useful to improve our understanding of the temporal dynamic of vegetation, monitored by vegetation indices.