Far infrared filters for the GALILEO-Jupiter and other missions

Extrapolation of PbTe/II-VI multilayer interference-filter technique from 20 to beyond 40µm is described and PbTe transparency reviewed; improvements below 20µm are reported. A composite filter cutting on steeply at 40µm is described that uses absorptive films of ZnS and As2S3, thin Quartz, and supplementary multilayer interference. Absorptive filters are described containing the II-VI compounds since these are found transparent at wavelengths shorter and longer than their reststrahl.

Durability assessment of PbTe/II-IV infrared filters (Space Shuttle 1st LDEF)

Residual stress having been further reduced, selected infrared coatings composed of thin films of (PbTe/ ZnS (or ZnSe) can now be made which comply with the durability requirements of MIL-48616 whilst retaining transparency. Such improved durability is due to the sequence:- i) controlled deposition, followed by ii) immediate exposure to air, followed by iii) annealing in vacuo to relieve stress. (At the time of writing we assume the empiric procedure "exposure to air/annealing in vacuo" acts to relieve the inherent stresses of deposition). As part of their testing, representative sample filters prepared by the procedure are being assembled for the shuttle's 1st Long Duration Exposure Facility (to be placed in earth orbit for a considerable period and then recovered for analysis). The sample filters comprise various narrowband-designs to permit deduction of the constituent thin film optical properties. The Reading assembly also contains representative sample of the infrared crystals, glasses, thin-film absorbers and bulk absorbers, and samples of shorter-wavelength filters prepared similarly but made with Ge/SiO. Findings on durability and transparency after exposure will be reported.

Infrared absorption spectra, radiative efficiencies, and global warming potentials of perfluorocarbons: Comparison between experiment and theory

Experimentally and theoretically determined infrared spectra are reported for a series of straight-chain perfluorocarbons: C2F6, C3F8, C4F10, C5F12, C6F14, and C8F18. Theoretical spectra were determined using both density functional (DFT) and ab initio methods. Radiative efficiencies (REs) were determined using the method of Pinnock et al. (1995) and combined with atmospheric lifetimes from the literature to determine global warming potentials (GWPs). Theoretically determined absorption cross sections were within 10% of experimentally determined values. Despite being much less computationally expensive, DFT calculations were generally found to perform better than ab initio methods. There is a strong wavenumber dependence of radiative forcing in the region of the fundamental C-F vibration, and small differences in wavelength between band positions determined by theory and experiment have a significant impact on the REs. We apply an empirical correction to the theoretical spectra and then test this correction on a number of branched chain and cyclic perfluoroalkanes. We then compute absorption cross sections, REs, and GWPs for an additional set of perfluoroalkenes.

Infrared linear dichroism spectroscopy on amyloid fibrils aligned by molecular combing

We report the use of molecular combing as an alignment method to obtain macroscopically oriented amyloid fibrils on planar surfaces. The aligned fibrils are studied by polarized infrared spectroscopy. This gives structural information that cannot be definitively obtained from standard infrared experiments on isotropic samples, for example, confirmation of the characteristic cross-beta amyloid core structure, the side-chain orientation from specific amino acids, and the arrangement of the strands within the fibrils, as we demonstrate here. We employed amyloid fibrils from hen egg white lysozyme (HEWL) and from a model octapeptide. Our results demonstrate molecular combing as a straightforward method to align amyloid fibrils, producing highly anisotropic infrared linear dichroism (IRLD) spectra.

Assessment of the consistency of H2O line intensities over the near-infrared using sun-pointing ground-based Fourier transform spectroscopy

We report on the consistency of water vapour line intensities in selected spectral regions between 800–12,000 cm−1 under atmospheric conditions using sun-pointing Fourier transform infrared spectroscopy. Measurements were made across a number of days at both a low and high altitude field site, sampling a relatively moist and relatively dry atmosphere. Our data suggests that across most of the 800–12,000 cm−1 spectral region water vapour line intensities in recent spectral line databases are generally consistent with what was observed. However, we find that HITRAN-2008 water vapour line intensities are systematically lower by up to 20% in the 8000–9200 cm−1 spectral interval relative to other spectral regions. This discrepancy is essentially removed when two new linelists (UCL08, a compilation of linelists and ab-initio calculations, and one based on recent laboratory measurements by Oudot et al. (2010) [10] in the 8000–9200 cm−1 spectral region) are used. This strongly suggests that the H2O line strengths in the HITRAN-2008 database are indeed underestimated in this spectral region and in need of revision. The calculated global-mean clear-sky absorption of solar radiation is increased by about 0.3 W m−2 when using either the UCL08 or Oudot line parameters in the 8000–9200 cm−1 region, instead of HITRAN-2008. We also found that the effect of isotopic fractionation of HDO is evident in the 2500–2900 cm−1 region in the observations.

Water vapour continuum absorption in near-infrared windows derived from laboratory measurements

In most near-infrared atmospheric windows, absorption of solar radiation is dominated by the water vapor self-continuum and yet there is a paucity of measurements in these windows. We report new laboratory measurements of the self-continuum absorption at temperatures between 293 and 472 K and pressures from 0.015 to 5 atm in four near-infrared windows between 1 and 4 m (10000-2500 cm-1); the measurements are made over a wider range of wavenumber, temperatures and pressures than any previous measurements. They show that the self-continuum in these windows is typically one order of magnitude stronger than given in representations of the continuum widely used in climate and weather prediction models. These results are also not consistent with current theories attributing the self continuum within windows to the far-wings of strong spectral lines in the nearby water vapor absorption bands; we suggest that they are more consistent with water dimers being the major contributor to the continuum. The calculated global-average clear-sky atmospheric absorption of solar radiation is increased by 0.75 W/m2 (which is about 1% of the total clear-sky absorption) by using these new measurements as compared to calculations with the MT_CKD-2.5 self-continuum model.

Clear-sky biases in satellite infrared estimates of upper tropospheric humidity and its trends

We use microwave retrievals of upper tropospheric humidity (UTH) to estimate the impact of clear-sky-only sampling by infrared instruments on the distribution, variability and trends in UTH. Our method isolates the impact of the clear-sky-only sampling, without convolving errors from other sources. On daily time scales IR-sampled UTH contains large data gaps in convectively active areas, with only about 20-30 % of the tropics (30 S­ 30 N) being sampled. This results in a dry bias of about -9 %RH in the area-weighted tropical daily UTH time series. On monthly scales, maximum clear-sky bias (CSB) is up to -30 %RH over convectively active areas. The magnitude of CSB shows significant correlations with UTH itself (-0.5) and also with the variability in UTH (-0.6). We also show that IR-sampled UTH time series have higher interannual variability and smaller trends compared to microwave sampling. We argue that a significant part of the smaller trend results from the contrasting influence of diurnal drift in the satellite measurements on the wet and dry regions of the tropics.

Prediction of coagulation properties, titratable acidity and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000–900 cm−1) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a30, mm), TA (SH°/50 mL; SH° = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm−1. Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm−1, 3,040 to 1,700 cm−1, and 4,000 to 3,470 cm−1. The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a30, range 58 mm), 0.25 SH°/50 mL (TA, range 3.58 SH°/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R2 = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R2 = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.

Visible-near infrared spectroscopy sensor for predicting curd and whey composition during cheese processing

The potential of visible-near infrared spectra, obtained using a light backscatter sensor, in conjunction with chemometrics, to predict curd moisture and whey fat content in a cheese vat was examined. A three-factor (renneting temperature, calcium chloride, cutting time), central composite design was carried out in triplicate. Spectra (300–1,100 nm) of the product in the cheese vat were captured during syneresis using a prototype light backscatter sensor. Stirring followed upon cutting the gel, and samples of curd and whey were removed at 10 min intervals and analyzed for curd moisture and whey fat content. Spectral data were used to develop models for predicting curd moisture and whey fat contents using partial least squares regression. Subjecting the spectral data set to Jack-knifing improved the accuracy of the models. The whey fat models (R = 0.91, 0.95) and curd moisture model (R = 0.86, 0.89) provided good and approximate predictions, respectively. Visible-near infrared spectroscopy was found to have potential for the prediction of important syneresis indices in stirred cheese vats.

Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy

The potential of near infrared spectroscopy in conjunction with partial least squares regression to predict Miscanthus xgiganteus and short rotation coppice willow quality indices was examined. Moisture, calorific value, ash and carbon content were predicted with a root mean square error of cross validation of 0.90% (R2 = 0.99), 0.13 MJ/kg (R2 = 0.99), 0.42% (R2 = 0.58), and 0.57% (R2 = 0.88), respectively. The moisture and calorific value prediction models had excellent accuracy while the carbon and ash models were fair and poor, respectively. The results indicate that near infrared spectroscopy has the potential to predict quality indices of dedicated energy crops, however the models must be further validated on a wider range of samples prior to implementation. The utilization of such models would assist in the optimal use of the feedstock based on its biomass properties.

Evaluating mid-infrared spectroscopy as a new technique for predicting sensory texture attributes of processed cheese

The objective of this study was to investigate the potential application of mid-infrared spectroscopy for determination of selected sensory attributes in a range of experimentally manufactured processed cheese samples. This study also evaluates mid-infrared spectroscopy against other recently proposed techniques for predicting sensory texture attributes. Processed cheeses (n = 32) of varying compositions were manufactured on a pilot scale. After 2 and 4 wk of storage at 4 degrees C, mid-infrared spectra ( 640 to 4,000 cm(-1)) were recorded and samples were scored on a scale of 0 to 100 for 9 attributes using descriptive sensory analysis. Models were developed by partial least squares regression using raw and pretreated spectra. The mouth-coating and mass-forming models were improved by using a reduced spectral range ( 930 to 1,767 cm(-1)). The remaining attributes were most successfully modeled using a combined range ( 930 to 1,767 cm(-1) and 2,839 to 4,000 cm(-1)). The root mean square errors of cross-validation for the models were 7.4(firmness; range 65.3), 4.6 ( rubbery; range 41.7), 7.1 ( creamy; range 60.9), 5.1(chewy; range 43.3), 5.2(mouth-coating; range 37.4), 5.3 (fragmentable; range 51.0), 7.4 ( melting; range 69.3), and 3.1 (mass-forming; range 23.6). These models had a good practical utility. Model accuracy ranged from approximate quantitative predictions to excellent predictions ( range error ratio = 9.6). In general, the models compared favorably with previously reported instrumental texture models and near-infrared models, although the creamy, chewy, and melting models were slightly weaker than the previously reported near-infrared models. We concluded that mid-infrared spectroscopy could be successfully used for the nondestructive and objective assessment of processed cheese sensory quality..

Prediction of processed cheese instrumental texture and meltability by mid-infrared spectroscopy coupled with chemometric tools

The objective of this study was to determine the potential of mid-infrared spectroscopy coupled with multidimensional statistical analysis for the prediction of processed cheese instrumental texture and meltability attributes. Processed cheeses (n = 32) of varying composition were manufactured in a pilot plant. Following two and four weeks storage at 4 degrees C samples were analysed using texture profile analysis, two meltability tests (computer vision, Olson and Price) and mid-infrared spectroscopy (4000-640 cm(-1)). Partial least squares regression was used to develop predictive models for all measured attributes. Five attributes were successfully modelled with varying degrees of accuracy. The computer vision meltability model allowed for discrimination between high and low melt values (R-2 = 0.64). The hardness and springiness models gave approximate quantitative results (R-2 = 0.77) and the cohesiveness (R-2 = 0.81) and Olson and Price meltability (R-2 = 0.88) models gave good prediction results. (c) 2006 Elsevier Ltd. All rights reserved..

On-line prediction of cheese making using backscatter of near infrared indices light

The potential of a fibre optic sensor, detecting light backscatter in a cheese vat during coagulation and syneresis, to predict curd moisture, fat loses and curd yield was examined. Temperature, cutting time and calcium levels were varied to assess the strength of the predictions over a range of processing conditions. Equations were developed using a combination of independent variables, milk compositional and light backscatter parameters. Fat losses, curd yield and curd moisture content were predicted with a standard error of prediction (SEP) of +/- 2.65 g 100 g(-1) (R-2 = 0.93), +/- 0.95% (R-2 = 0.90) and +/- 1.43% (R-2 = 0.94), respectively. These results were used to develop a model for predicting curd moisture as a function of time during syneresis (SEP = +/- 1.72%; R-2 = 0.95). By monitoring coagulation and syneresis, this sensor technology could be employed to control curd moisture content, thereby improving process control during cheese manufacture. (c) 2007 Elsevier Ltd. All rights reserved..

Application of mid-infrared spectroscopy to the prediction of maturity and sensory texture attributes of cheddar cheese

The objective of this study was to determine the potential of mid-infrared spectroscopy in conjunction with partial least squares (PLS) regression to predict various quality parameters in cheddar cheese. Cheddar cheeses (n = 24) were manufactured and stored at 8 degrees C for 12 mo. Mid-infrared spectra (640 to 4000/cm) were recorded after 4, 6, 9, and 12 mo storage. At 4, 6, and 9 mo, the water-soluble nitrogen (WSN) content of the samples was determined and the samples were also evaluated for 11 sensory texture attributes using descriptive sensory analysis. The mid-infrared spectra were subjected to a number of pretreatments, and predictive models were developed for all parameters. Age was predicted using scatter-corrected, 1st derivative spectra with a root mean square error of cross-validation (RMSECV) of 1 mo, while WSN was predicted using 1st derivative spectra (RMSECV = 2.6%). The sensory texture attributes most successfully predicted were rubbery, crumbly, chewy, and massforming. These attributes were modeled using 2nd derivative spectra and had, corresponding RMSECV values in the range of 2.5 to 4.2 on a scale of 0 to 100. It was concluded that mid-infrared spectroscopy has the potential to predict age, WSN, and several sensory texture attributes of cheddar cheese..