Synthesis and characterization of nanoporous phospho-tungstate organic-inorganic hybrid materials

Nanoporous phospho-tungstate organic-inorganic hybrid materials have been synthesized from sodium tungstate and mono-n-dodecyl phosphate (MDP), which was used as both surfactant and phosphorus precursor. These hybrid materials were thoroughly characterized by N2 adsorption, elemental analysis, powder XRD, FTIR, Raman, TG, TEM and XPS and possess lamellar structures with interlayer spacings of 3.2 nm. A plausible method for formation of hybrid materials comprised of lacunary Keggin anions and micelles of surfactants is proposed. © The Royal Society of Chemistry 2008.

Amine-functionalised hexagonal mesoporous silica as support for copper(II) acetylacetonate catalyst

Copper(II) acetylacetonate was anchored onto a hexagonal mesoporous silica (HMS) material using a two-step procedure: (i) functionalisation of the surface hydroxy groups with (3-aminopropyl)triethoxysilane (AMPTSi) and then (ii) anchoring of the copper(II) complex through Schiff condensation with free amine groups, using two different metal complex loadings. Upon the first step, nitrogen elemental analysis, XPS and DRIFT showed the presence of amine groups on the surface of the HMS material, and porosimetry indicated that the structure of the mesoporous material remained unchanged, although a slight decrease in surface area was observed. Atomic absorption, XPS and DRIFT showed that copper(II) acetylacetonate was anchored onto the amine-functionalised HMS by Schiff condensation between the free amine groups and the carbonyl groups of the copper(II) complex; using EPR an NO3 coordination sphere was proposed for the anchored copper(II) complex. The new [Cu(acac)2]-AMPTSi/HMS materials were tested in the aziridination of styrene at room temperature, using PhI=NTs as nitrogen source and acetonitrile as solvent. The styrene conversion and total TON of the heterogeneous phase reaction are higher than those of the same reaction catalysed in homogeneous phase by [Cu(acac)2]; nevertheless, the initial activity decreases and the reaction time increases due to substrate and product diffusion limitations. The heterogeneous catalyst showed a successive slight decrease in catalytic activity when reused for two more times. © Wiley-VCH Verlag GmbH & Co. KGaA, 2006.

Synthesis and characterization of silica-supported L-Lysine-based dendritic branches

Two series of novel modified silicas have been prepared in which individual dendritic branches have been attached to aminopropylsilica using standard peptide coupling methodology. The dendritic branches are composed of enantiomerically pure l-lysine building blocks, and hence, the modified silicas have the potential to act as chiral stationary phases in chromatography. In one series of modified silicas, the surface of the dendritic branch consists of Boc carbamate groups, whereas the other has benzoyl amide surface groups. Different coupling reagents have been investigated in order to maximize the loading onto the solid phase. The new supported dendritic materials have been fully characterized with properties of the bulk material determined by elemental analysis, 13C NMR, and IR spectroscopy, whereas XPS provides important information about the surface of the modified silica exposed to the incident X-rays, the key region in which potential chromatographic performance of these materials will take place. Although the bulk analyses indicate that loading of the dendritic branch onto silica decreases with increasing dendritic generation (and consequently steric bulk), XPS indicates that the optimum surface coverage is actually obtained at the second generation of dendritic growth.

Fenton chemistry-based detemplation of an industrially relevant microcrystalline beta zeolite. Optimization and scaling-up studies

A mild template removal of microcrystalline beta zeolite, based on Fenton chemistry, was optimized. Fenton detemplation was studied in terms of applicability conditions window, reaction rate and scale up. TGA and CHN elemental analysis were used to evaluate the detemplation effectiveness, while ICP, XRD, LPHR-Ar physisorption, and 27Al MAS NMR were applied to characterize the structure and texture of the resulting materials. The material properties were compared to calcination. By understanding the interplay of relevant parameters of the Fenton chemistry, the process can be optimized in order to make it industrially attractive for scale-up. The H2O2 utilization can be minimized down to 15 mL H2O2/g (88 °C, 30 ppm Fe), implying a high solid concentration and low consumption of H2O2. When Fe concentration must be minimized, values as low as 5 ppm Fe can be applied (88 °C, 30 mL H2O2/g), to achieve full detemplation. The reaction time to completeness can be reduced to 5 h when combining a Fe-oxalate catalyst with UV radiation. The protocol was scaled up to 100 times larger its original recipe. In terms of the material's properties, the scaled material is structurally comparable to the calcined counterpart (comparable Si/Al and XRD patterns), while it displays benefits in terms of texture and Al-coordination, the latter with full preservation of the tetrahedral Al

A novel silicon membrane-based biosensing platform using distributive sensing strategy and artificial neural networks for feature analysis

A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications.

Development of an on-demand beam pulsing system for Pixe-analysis of thick targets

This work concerns the developnent of a proton irduced X-ray emission (PIXE) analysis system and a multi-sample scattering chamber facility. The characteristics of the beam pulsing system and its counting rate capabilities were evaluated by observing the ion-induced X-ray emission from pure thick copper targets, with and without beam pulsing operation. The characteristic X-rays were detected with a high resolution Si(Li) detector coupled to a rrulti-channel analyser. The removal of the pile-up continuum by the use of the on-demand beam pulsing is clearly demonstrated in this work. This new on-demand pu1sirg system with its counting rate capability of 25, 18 and 10 kPPS corresponding to 2, 4 am 8 usec main amplifier time constant respectively enables thick targets to be analysed more readily. Reproducibility tests of the on-demard beam pulsing system operation were checked by repeated measurements of the system throughput curves, with and without beam pulsing. The reproducibility of the analysis performed using this system was also checked by repeated measurements of the intensity ratios from a number of standard binary alloys during the experimental work. A computer programme has been developed to evaluate the calculations of the X-ray yields from thick targets bornbarded by protons, taking into account the secondary X-ray yield production due to characteristic X-ray fluorescence from an element energetically higher than the absorption edge energy of the other element present in the target. This effect was studied on metallic binary alloys such as Fe/Ni and Cr/Fe. The quantitative analysis of Fe/Ni and Cr/Fe alloy samples to determine their elemental composition taking into account the enhancement has been demonstrated in this work. Furthermore, the usefulness of the Rutherford backscattering (R.B.S.) technique to obtain the depth profiles of the elements in the upper micron of the sample is discussed.

Elemental partitioning and microstructural development in duplex stainless steel weld metal

A thermodynamic analysis which is capable of estimating the austenite/ferrite equilibria in duplex stainless steels has been carried out using the sublattice thermodynamic model. The partitioning of alloying elements between the austenite and ferrite phases has been calculated as a function of temperature. The results showed that chromium partitioning was not influenced significantly by the temperature. The molybdenum, on the other hand, was found to partition preferentially into ferrite phase as the temperature decreases. A strong partitioning of nickel into the austenite was observed to decrease gradually with increasing temperature. Among the alloying elements, average nitrogen concentration was found to have the most profound effect on the phase balance and the partitioning of nitrogen into the austenite. The partitioning coefficient of nitrogen (the ratio of the mole fraction of nitrogen in the austenite to that in the ferrite) was found to be as high as 7.0 around 1300 K. Consequently, the volume fraction of austenite was influenced by relatively small additions of nitrogen. The results are compared with the experimentally observed data in a duplex stainless steel weld metal in conjunction with the solid state δ → δ + γ phase transformation. Particular attention was given to the morphological instability of grain boundary austenite allotriomorphs. A compariso between the experimental results and calculations indicated that the instability associated with irregular austenite perturbations results from the high degree of undercooling. The results suggest that the model can be used successfully to understand the development of the microstructure in duplex stainless steel weld metals.

Kinetic study of the pyrolysis of miscanthus and its acid hydrolysis residue by thermogravimetric analysis

The kinetic parameters of the pyrolysis of miscanthus and its acid hydrolysis residue (AHR) were determined using thermogravimetric analysis (TGA). The AHR was produced at the University of Limerick by treating miscanthus with 5 wt.% sulphuric acid at 175 °C as representative of a lignocellulosic acid hydrolysis product. For the TGA experiments, 3 to 6 g of sample, milled and sieved to a particle size below 250 μm, were placed in the TGA ceramic crucible. The experiments were carried out under non-isothermal conditions heating the samples from 50 to 900 °C at heating rates of 2.5, 5, 10, 17 and 25 °C/min. The activation energy (EA) of the decomposition process was determined from the TGA data by differential analysis (Friedman) and three isoconversional methods of integral analysis (Kissinger–Akahira–Sunose, Ozawa–Flynn–Wall, Vyazovkin). The activation energy ranged from 129 to 156 kJ/mol for miscanthus and from 200 to 376 kJ/mol for AHR increasing with increasing conversion. The reaction model was selected using the non-linear least squares method and the pre-exponential factor was calculated from the Arrhenius approximation. The results showed that the best fitting reaction model was the third order reaction for both feedstocks. The pre-exponential factor was in the range of 5.6 × 1010 to 3.9 × 10+ 13 min− 1 for miscanthus and 2.1 × 1016 to 7.7 × 1025 min− 1 for AHR.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.