Experimental and theoretical studies on six-membered ring hydrogen bond systems in crystalline drug substances

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Experimental and theoretical studies on molecular geometry and polymorphism in crystalline drug substances

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

High speed electrical breakdown mechanisms in gaseous, liquid and solid dielectric materials

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Surface modification of natural fibers using bacteria:depositing bacterial cellulose onto natural fibers to create hierarchical fiber reinforced nanocomposites

Triggered biodegradable composites made entirely from renewable resources are urgently sought after to improve material recyclability or be able to divert materials from waste streams. Many biobased polymers and natural fibers usually display poor interfacial adhesion when combined in a composite material. Here we propose a way to modify the surfaces of natural fibers by utilizing bacteria (Acetobacter xylinum) to deposit nanosized bacterial cellulose around natural fibers, which enhances their adhesion to renewable polymers. This paper describes the process of modifying large quantities of natural fibers with bacterial cellulose through their use as substrates for bacteria during fermentation. The modified fibers were characterized by scanning electron microscopy, single fiber tensile tests, X-ray photoelectron spectroscopy, and inverse gas chromatography to determine their surface and mechanical properties. The practical adhesion between the modified fibers and the renewable polymers cellulose acetate butyrate and poly(L-lactic acid) was quantified using the single fiber pullout test. © 2008 American Chemical Society.

Analysis of femtosecond laser surface patterning on bulk single-crystalline diamond

Preliminary work is reported on 2-D and 3-D microstructures written directly with a Yb:YAG 1026 nm femtosecond (fs) laser on bulk chemical vapour deposition (CVD) single-crystalline diamond. Smooth graphitic lines and other structures were written on the surface of a CVD diamond sample with a thickness of 0.7mm under low laser fluences. This capability opens up the opportunity for making electronic devices and micro-electromechanical structures on diamond substrates. The fabrication process was optimised through testing a range of laser energies at a 100 kHz repetition rate with sub-500fs pulses. These graphitic lines and structures have been characterised using optical microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy and atomic force microscopy. Using these analysis techniques, the formation of sp2 and sp3 bonds is explored and the ratio between sp2 and sp3 bonds after fs laser patterning is quantified. We present the early findings from this study and characterise the relationship between the graphitic line formation and the different fs laser exposure conditions. © 2012 Taylor & Francis.

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.

On some Sufficient Conditions for High Breakdown Point of ML Estimators

High breakdown point estimators LME(k) and LT E(k) for location and scale are obtained for symmetrical exponentially decreasing density family.

Application of the D-Fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator to a Generalized Logistic Model

2000 Mathematics Subject Classification: 62J12, 62F35

A holistic multi evidence approach to study the fragmentation behaviour of crystalline mannitol

Mannitol is an essential excipient employed in orally disintegrating tablets due to its high palatability. However its fundamental disadvantage is its fragmentation during direct compression, producing mechanically weak tablets. The primary aim of this study was to assess the fracture behaviour of crystalline mannitol in relation to the energy input during direct compression, utilising ball milling as the method of energy input, whilst assessing tablet characteristics of post-milled powders. Results indicated that crystalline mannitol fractured at the hydrophilic (011) plane, as observed through SEM, alongside a reduction in dispersive surface energy. Disintegration times of post-milled tablets were reduced due to the exposure of the hydrophilic plane, whilst more robust tablets were produced. This was shown through higher tablet hardness and increased plastic deformation profiles of the post-milled powders, as observed with a lower yield pressure through an out-of-die Heckel analysis. Evaluation of crystal state using x-ray diffraction/differential scanning calorimetry showed that mannitol predominantly retained the β-polymorph; however x-ray diffraction provided a novel method to calculate energy input into the powders during ball milling. It can be concluded that particle size reduction is a pragmatic strategy to overcome the current limitation of mannitol fragmentation and provide improvements in tablet properties.

Comprehensive characterization of Napier grass as a feedstock for thermochemical conversion

Study on Napier grass leaf (NGL), stem (NGS) and leaf and stem (NGT) was carried out. Proximate, ultimate and structural analyses were evaluated. Functional groups and crystalline components in the biomass were examined. Pyrolysis study was conducted in a thermogravimetric analyzer under nitrogen atmosphere of 20 mL/min at constant heating rate of 10 K/min. The results reveal that Napier grass biomass has high volatile matter, higher heating value, high carbon content and lower ash, nitrogen and sulfur contents. Structural analysis shows that the biomass has considerable cellulose and lignin contents which are good candidates for good quality bio-oil production. From the pyrolysis study, degradation of extractives, hemicellulose, cellulose and lignin occurred at temperature around 478, 543, 600 and above 600 K, respectively. Kinetics of the process was evaluated using reaction order model. New equations that described the process were developed using the kinetic parameters and data compared with experimental data. The results of the models fit well to the experimental data. The proposed models may be a reliable means for describing thermal decomposition of lignocellulosic biomass under nitrogen atmosphere at constant heating rate.

The thermal performance of the polysaccharides extracted from hardwood:cellulose and hemicellulose

The pyrolytic behaviour of individual component in biomass needs to be understood to gain insight into the mechanism of biomass pyrolysis. A comparative study on the pyrolysis of cellulose (hexose-based polysaccharides) and hemicallulose (pentose-based polysaccharides) is performed by two sets of experiments including TG analysis and Py-GC-MS/FTIR. The samples of these two polysaccharide components are thermally decomposed in TGA at the heating rate of 5 and 60 K/min to demonstrate the different characteristics of mass loss stage(s) between them. The yield of pyrolytic products is examined by a fluidized-bed fast pyrolysis unit. The experiment confirms that cellulose mainly contributes to bio-oil production (reaching the maximum of 72% at 580 °C), while hemicellulose works as an important precursor for the char production (∼25%). The compounds in the gaseous mixture (CO and CO2) and bio-oil (levoglucosan, furfural, aldehyde, acetone and acetic acid) are further characterized by GC-MS for cellulose and GC-FTIR for hemicellulose, and their formations are investigated thoroughly. © 2010 Elsevier Ltd. All rights reserved.