Micro-spectroscopic investigation of Al and S speciation in hardened cement paste

Synchrotron-based micro X-ray fluorescence (micro-XRF) and micro X-ray absorption near edge spectroscopy (micro-XANES) have been used to determine the spatial distribution of Al and S and to identify the Al- and S-bearing species in compact hardened cement paste hydrated at 50 °C. The contribution of the S-bearing cement phases to the composed S K-edge XANES spectra collected in ten S-rich regions was determined using least-squares fitting. Ettringite and calcium monosulfoaluminate were identified as the main S-bearing species in the selected regions. Factor analysis was employed to determine the contribution of the various Al-bearing cement minerals to the composed Al K-edge XANES collected in different Al-rich regions of the cement matrix. Principal component analysis revealed that all spectra could be fitted using three components. Target transformation further suggested that the two Al-bearing clinker phases (aluminate, ferrite) and secondary phases of the hydrate assemblage (ettringite, AFm phases, hydrotalcite) contributed to the set of components that made up the experimental spectra. Least-squares fitting allowed the relative contribution of each reference compound to be determined. Aluminate and/or ferrite were detected in all Al-rich regions. AFm phases were identified in six out of the ten regions studied, while ettringite was detected in only two regions. The study confirmed that AFm phases are important cement minerals in hardened cement paste hydrated at 50 °C.     

Pilot studies on high recovery BWRO-EDR for near zero liquid discharge approach

A hybrid process combining reverse osmosis and electrodialysis has been shown to be effective in recovering 97-98% of brackish water as product water with chloride levels of 200 mg/L or less. Potential for scaling on the brine side of the electrodialysis unit was prevented by acidification, operating the electrodialysis in a reversal mode (EDR), and a side loop crystallizer which prevented buildup of scaling components. Settlers, inline microfiltration, and side-loop ultrafiltration kept suspended solids from returning to the EDR unit. This process was demonstrated in a series of more than eighty batch experiments of 1.5 to 1.8 m³ of RO concentrate of raw brackish groundwater from the Negev Highland, Israel. Each batch could be processed within a single day. The feed-water was concentrated from 0.3% to over 10% TDS super-concentrate while producing the water that could be recycled to the RO permeate. This super-concentrate from the EDR unit was further concentrated in a wind powered WAIV unit that brought final brine TDS to > 30%, and showed promise as a method to recover mineral byproducts such as magnesium salt. Initial economic estimates show that this hybrid process is competitive with conventional RO and other enhanced recovery processes for inland desalination requiring use of evaporation ponds.     

Pt and Sn Doped Sputtered CeO2 Electrodes for Fuel Cell Applications

The interaction of Pt with CeO₂ layers was investigated by using photoelectron spectroscopy. Thirty‐nanometre‐thick Pt and Sn doped CeO₂ layers were deposited simultaneously by rf‐magnetron sputtering on a Si(001) substrate and a carbon diffusion layer of a polymer membrane fuel cell by using a composite CeO₂–Pt–Sn target. The laboratory XPS and synchrotron radiation soft X‐ray and hard X‐ray photoemission spectra showed the formation of cerium oxide with completely ionised Pt^2+,4+ species, and with Pt⁴⁺ embedded in the film bulk. Hydrogen/air fuel cell activity measurements normalised to the amount of Pt used revealed high specific power of up to 5.4 × 10⁴ mW mg^–1 (Pt). The activity of these materials is explained by the strong activity of embedded Ptⁿ⁺ cations.     

Prediction of sensory attributes of European Emmental cheese using near-infrared spectroscopy: A feasibility study

The present work evaluated the ability of near infrared (NIR) spectroscopy in predicting some sensory attributes of 20 Emmental cheeses originating from different European regions. For the purpose of this study four appearance and texture attributes, namely, adhesivity, friability, elasticity and firmness and six olfacto-gustatory attributes namely, aroma intensity, odour intensity, bitterness, saltiness, acidity and sweetness were selected by the sensory panel. Calibration models between sensory properties and NIR spectra were developed using partial least squares (PLS) regression. The squared correlation coefficients (R²) were greater than 0.5 for adhesivity, elasticity, firmness, aroma, bitterness, saltiness, acidity and sweetness. In addition, a good correlation between sensory attributes and NIR spectra was found using canonical correlation analysis (CCA). Therefore, this work demonstrates the feasibility of NIR to predict some sensory attributes since a relatively high correlation between sensory data and NIR spectra was found. However, further research with a large data bases will be needed in order to validate the method.     

Optical Measurement of Peak Air Shock Pressures Following Explosions

High speed video and streak camera imaging are used to measure peak pressures for explosions of spherical charges of the high explosive C‐4 (92 % trimethylenetrinitramine, C₃H₆N₆O₆). The technique measures the velocity of the air shock produced by the detonation of the explosive charges, converts this velocity to a Mach number, and uses the Mach number to determine a peak shock pressure. Peak pressure measurements are reported from a few millimeters to approximately one meter from the charge surface. Optical peak pressure measurements are compared to peak pressures measured using piezoelectric pressure transducers, and to peak pressure measurements estimated using the blast computer code CONWEP. A discussion of accuracy of peak pressures determined optically is provided.     

Confirmation of brand identity in foods by near infrared transflectance spectroscopy using classification and class-modelling chemometric techniques — The example of a Belgian beer

Food and beverage processors require tools to monitor conformance of finished goods to their defined specification; regulatory authorities need appropriate methods for detecting retail fraud. In this report, samples (n = 275) of Belgian and other European beers were collected and analysed using near infrared transflectance spectroscopy; three class-modelling techniques (soft independent modelling of class analogy, SIMCA; potential functions techniques, POTFUN; and unequal dispersed classes, UNEQ) were employed to characterise beer types (firstly Trappist and then Rochefort) while a classification method (partial least squares discriminant analysis, PLS-DA) was applied to discriminate between two final beer classes: Rochefort 8° and Rochefort 10°. The class-models and the classification rules developed were validated by means of an external prediction set. A discussion on the appropriate use of these chemometric approaches is included. Modelling of Trappist beers met with limited success while model efficiencies for Rochefort samples were highest for SIMCA and UNEQ applications i.e. 81.4% and 84.5% respectively. The classification of beers as Rochefort 8? or Rochefort 10? was possible with an average correct classification rate of 93.4%.     

Enhanced NIR Calibration for Wort Fermentability Using Orthogonal Signal Correction

An enhanced method for the calibration of Near Infra Red (NIR) reflectance spectra to wort fermentability is proposed using a signal pre‐processing algorithm called orthogonal signal correction (OSC). Pre‐processing NIR spectra prior to partial least squares Project to Latent Structures (PLS) regression modelling is becoming commonplace in multivariate calibration. A set of twenty wort samples subjected to a replicated 2² factorial design with a centre point and nine production samples were used to construct multivariate prediction models. The experimental design factors were the mash tun saccharification temperature and time used to purposely provide a sample set with significant leverage in the fermentability responses. Calibration PLS models for both wort apparent degree of fermentation (ADF) and final attenuation apparent extract (Final AE) values with and without OSC corrected spectra were compared demonstrating significant improvements in prediction capability with the prior (Q² = 0.90 versus Q² = 0.28). The OSC algorithm removed almost 60% of the variance in the NIR spectra, which was independent or orthogonal to the fermentability measures. By cleaning up the spectra, the standard errors of prediction (SEP) for ADF and Final AE were improved by 50 and 90%, respectively, illustrating not only the enhancement in calibration but also the aptness for process control applications. Various model validation tests, including an external validation example and random response permutation, verify the validity of the models using OSC. Furthermore, interpretation of the important wavelengths related to wort fermentability is provided and demonstrates that some key wavelengths are related to both carbohydrate overtones as well as nitrogen functional groups. The application of OSC prior to developing calibration models with NIR demonstrates promising results for brewers interested in real time control of wort fermentability.     

Study of the electrochemical behaviour of a 300 W PEM fuel cell stack by Electrochemical Impedance Spectroscopy

Electrochemical Impedance Spectroscopy (EIS) is a suitable and powerful diagnostic testing method for fuel cells because it is non-destructive and provides useful information about fuel cell performance and its components. In this work, EIS measurements were carried out on a 300 W stack with 20 elementary cells. Electrochemical impedance spectra were recorded either on each cell or on the stack. Parameters of a Randles-like equivalent circuit were fitted to the experimental data. In order to improve the quality of the fit, the classical Randles cell was extended by changing the standard plane capacitor into a constant phase element (CPE). The effects of output current, cell position, operating temperature and humidification temperature on the impedance spectra were studied.     

光纤近红外漫反射光谱技术在前胡族植物分类中的应用探讨

探讨了近红外光谱技术在前胡族植物分类中的可能性。用系统聚类分析获得的分类结果与传统的植物学分类比较一致 ,说明本方法应用于前胡族植物中三亚族的分类是基本可行的。     

近红外光谱法测定混合汁中还原糖含量

采用近红外光谱法测定混合汁中还原糖含量 ,获得良好效果 ,所建模型标准误差小而决定系数高。定标决定系数 R2 、交互定标标准误差 (SECV)、交互定标决定系数 (1-VR)分别为 0 .95 1,0 .0 74 ,0 .85 0 ,具有较好的相关性。用 5 2个随机混合汁样品检验该模型 ,近红外法预测结果与传统滴定法测定结果的检验工作标准误差 (SEP(C) )为 0 .0 75 ,检验决定系数 RSQ为 0 .85 0 ,证明测定所建近红外法定标模型具有较好的稳定性。