Vibrational spectroscopic studies of wool

Fourier transfonn (FT) Raman, Raman microspectroscopy and Fourier transform infrared (FTIR) spectroscopy have been used for the structural analysis and characterisation of untreated and chemically treated wool fibres. For FT -Raman spectroscopy novel methods of sample presentation have been developed and optimised for the analysis of wool. No significant fluorescence was observed and the spectra could be obtained routinely. The stability of wool keratin to the laser source was investigated and the visual and spectroscopic signs of sample damage were established. Wool keratin was found to be extremely robust with no signs of sample degradation observed for laser powers of up to 600 m W and for exposure times of up to seven and half hours. Due to improvements in band resolution and signal-to-noise ratio, several previously unobserved spectral features have become apparent. The assignment of the Raman active vibrational modes of wool have been reviewed and updated to include these features. The infrared spectroscopic techniques of attenuated total reflectance (ATR) and photoacoustic (P A) have been used to examine shrinkproofed and mothproofed wool samples. Shrinkproofing is an oxidative chemical treatment used to selectively modifY the surface of a wool fibre. Mothproofing is a chemical treatment applied to wool for the prevention of insect attack. The ability of PAS and A TR to vary the penetration depth by varying certain instrumental parameters was used to obtain spectra of the near surface regions of these chemically treated samples. These spectra were compared with those taken with a greater penetration depth, which therefore represent more of the bulk wool sample. The PA and ATR spectra demonstrated that oxidation was restricted to the near-surface layer of wool. Extensive curve fitting of ATR spectra of untreated wool indicated that cuticle was composed of a mixed protein conformation, but was predominately that of an a.-helix. The cortex was proposed to be a mixture of both a.helical and ~-pleated sheet protein conformations. These findings were supported by PAS depth profiling results. Raman microspectroscopy was used in an extensive investigation of the molecular structure of the wool fibre. This included determining the orientation of certain functional groups within the wool fibre and the symmetry of particular vibrations. The orientation ofbonds within the wool fibre was investigated by orientating the wool fibre axis parallel and then perpendicular to the plane of polarisation of the electric vector of the incident radiation. It was experimentally determined that the majority of C=O and N-H bonds of the peptide bond of wool lie parallel to the fibre axis. Additionally, a number of the important vibrations associated with the a-helix were also found to lie parallel to the fibre axis. Further investigation into the molecular structure of wool involved determining what effect stretching the wool fibre had on bond orientation. Raman spectra of stretched and unstretched wool fibres indicated that extension altered the orientation ofthe aromatic rings, the CH2 and CH3 groups of the amino acids. Curve fitting results revealed that extension resulted in significant destruction of the a-helix structure a substantial increase in the P-pleated sheet structure. Finally, depolarisation ratios were calculated for Raman spectra. The vibrations associated with the aromatic rings of amino acids had very low ratios which indicated that the vibrations were highly symmetrical.

Raman spectroscopic study of the antimonate mineral bottinoite Ni[Sb2(OH)12].6H2O and in comparison with brandholzite Mg[Sb5+2(OH)12]•6H2O

Raman spectra of bottinoite Ni[Sb(OH)6].6H2O were studied, and related to the molecular structure of the mineral. An intense sharp Raman band at 618 cm-1 is attributed to the SbO symmetric stretching mode. The low intensity band at 735 cm-1 is ascribed to the SbO antisymmetric stretching vibration. Low intensity Raman bands were found at 501, 516 and 578 cm-1. Four Raman bands observed at 1045, 1080, 1111 and 1163 cm-1 are assigned to δ SbOH deformation modes. A complex pattern resulting from the overlapping band of the water and hydroxyl units is observed. Raman bands are observed at 3223, 3228, 3368, 3291, 3458 and 3510 cm-1. The first two Raman bands are assigned to water stretching vibrations. The two higher wavenumber Raman bands observed at 3466 and 3552 cm-1 and two infrared bands at 3434 and 3565 cm-1 are assigned to the stretching vibrations of the hydroxyl units. Observed Raman and infrared bands are connected with O-H…O hydrogen bonds and their lengths 2.72, 2.79, 2.86, 2.88 and 3.0 Å (Raman) and 2.73, 2.83 and 3.07 Å (infrared).

Rationalizing the SER spectra of bacteria

The SER spectra of riboflavin and FAD are identical and are resonance enhanced at 514 or 532 nm. Signals from FAD/ riboflavin dominated SER spectra whenever these compounds were present with proteins or bacteria. SER spectra of very different bacteria such as Pseudomonas. aeruginosa, Bacillu. subtilis and Geobacillus. stearothermophilus were dominated by signals from FAD, even when these bacteria were added to a preformed colloid. The SERS signal of FAD is greatly reduced at 785 nm, and SER spectra of bacteria excited at 785 nm are quite different than those collected at 514 or 532 nm. This supports the assignment of the peaks in the 514 nm SER spectra of bacteria to FAD rather to amino acids or N-acetylglucosamine. The SER spectra of certain mixes of adenine and FAD showed similar changes to those of bacteria when the excitation was changed from 514/532 nm to 785 nm. The ratio of colloid: bacteria was of critical important for obtaining good SER spectra, and the addition of sodium sulfate was also beneficial. Removal of EPS from bacteria before analysis facilitated interaction with the silver surface, and may be a useful step to include in identification protocols.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Dussertite BaFe3+3(AsO4)2(OH)5 : a Raman spectroscopic study of a hydroxy-arsenate mineral

The mineral dussertite, a hydroxy-arsenate mineral of formula BaFe3+3(AsO4)2(OH)5, has been studied by Raman complimented with infrared spectroscopy. The spectra of three minerals from different origins were investigated and proved quite similar, although some minor differences were observed. In the Raman spectra of Czech dussertite, four bands are observed in the 800 to 950 cm-1 region. The bands are assigned as follows: the band at 902 cm-1 is assigned to the (AsO4)3- ν3 antisymmetric stretching mode, at 870 cm-1 to the (AsO4)3- ν1 symmetric stretching mode, and both at 859 cm-1 and 825 cm-1 to the As-OM2+/3+ stretching modes/and or hydroxyls bending modes. Raman bands at 372 and 409 cm-1 are attributed to the ν2 (AsO4)3- bending mode and the two bands at 429 and 474 cm-1 are assigned to the ν4 (AsO4)3- bending mode. An intense band at 3446 cm-1 in the infrared spectrum and a complex set of bands centred upon 3453 cm-1 in the Raman spectrum are attributed to the stretching vibrations of the hydrogen bonded (OH)- units and/or water units in the mineral structure. The broad infrared band at 3223 cm-1 is assigned to the vibrations of hydrogen bonded water molecules. Raman spectroscopy identified Raman bands attributable to (AsO4)3- and (AsO3OH)2- units.

Synthesis and characterisation of cobalt hydroxy carbonate Co2CO3(OH)2 Nanomaterials

In an attempt to make nanofibres based upon cobalt oxides, a novel compound a hydrated cobalt hydroxy carbonate was formed. This compound is related to the minerals of the rosasite mineral group. X-ray diffraction showed that the formed compound was a cobalt hydroxy carbonate and SEM displayed bundles of fibres on the micron scale in length and nanoscale in width. The morphology was compared with that of the rosasite mineral group. XPS proved two bond energies for cobalt and three for oxygen in the compound. The compound was characterised by vibrational spectroscopy and the spectra related to minerals of the rosasite mineral group. The stability of the synthetic mineral was limited to temperatures below 200°C.

A Raman spectroscopic study of the antimony mineral klebelsbergite Sb4O4(OH)2(SO4)

Many minerals based upon antimonite and antimonate anions remain to be studied. Most of the bands occur in the low wavenumber region, making infrared spectroscopy difficult to use. This problem can be overcome by using Raman spectroscopy. Raman spectra of the mineral klebelsbergite Sb4O4(OH)2(SO4) were studied, and related to the structure of the mineral. Raman bands observed at 971 cm-1 and a series of overlapping bands are observed at 1029, 1074, 1089, 1139 and 1142 cm-1 are assigned to the SO42- ν1 symmetric and ν3 antisymmetric stretching modes. Two Raman bands are observed at 662 and 723 cm-1 and assigned to the SbO ν3 antisymmetric and ν1 symmetric stretching modes. The intense Raman bands at 581, 604 and 611 cm-1 are assigned to the ν4 SO42- bending modes. Two overlapping bands at 481 and 489 cm-1 are assigned to the ν2 SO42- bending mode. Low intensity bands at 410, 435 and 446 cm-1 may be attributed to OSbO bending modes. The Raman band at 3435 cm-1 is attributed to the OH stretching vibration of the OH units. Multiple Raman bands for both SO42- and SbO stretching vibrations support the concept of the non-equivalence of these units in the klebelsbergite structure. It is proposed that two sulphate anions are distorted to different extents in the klebelsbergite structure.

Infrared and infrared emission spectroscopy of nesquehonite Mg(OH)(HCO3)•2H2O : implications for the formula of nesquehonite

The mineral nesquehonite Mg(OH)(HCO3)•2H2O has been analysed by a combination of infrared (IR) and infrared emission spectroscopy (IES). Both techniques show OH vibrations, both stretching and deformation modes. IES proves the OH units are stable up to 450°C. The strong IR band at 934 cm-1 is evidence for MgOH deformation modes supporting the concept of HCO3- units in the molecular structure. Infrared bands at 1027, 1052 and 1098 cm-1 are attributed to the symmetric stretching modes of HCO3- and CO32- units. Infrared bands at 1419, 1439, 1511, and 1528 cm-1 are assigned to the antisymmetric stretching modes of CO32- and HCO3- units. IES supported by thermoanalytical results defines the thermal stability of nesquehonite IES defines the changes in the molecular structure of nesquehonite with temperature. The results of IR and IES supports the concept that the formula of nesquehonite is better defined as Mg(OH)(HCO3)•2H2O.

A Raman and infrared spectroscopic study of the mineral delvauxite CaFe3+4(PO4,SO4)2(OH)8•4-6H2O- a ‘colloidal’ mineral

The mineral delvauxite CaFe3+4(PO4,SO4)2(OH)8•4-6H2O has been characterised by Raman spectroscopy and infrared spectroscopy. The mineral is associated with the minerals diadochite and destinezite. Delvauxite appears to vary in crystallinity from amorphous to semi-crystalline. The mineral is often X-ray non-diffracting. The minerals are found in soils and may be described as ‘colloidal’ minerals. Vibrational spectroscopy enables determination of the molecular structure of delvauxite. Bands are assigned to phosphate and sulphate stretching and bending modes. Two symmetric stretching modes for both the phosphate and sulphate symmetric stretching modes support the concept of non-equivalent phosphate and sulphate units in the mineral structure. Multiple water bending and stretching modes imply that non-equivalent water molecules in the structure exist with different hydrogen bond strengths.

Application of higher order statistics/spectra in biomedical signals : a review

For many decades correlation and power spectrum have been primary tools for digital signal processing applications in the biomedical area. The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. Higher order spectra, also known as polyspectra, are spectral representations of higher order statistics, i.e. moments and cumulants of third order and beyond. HOS (higher order statistics or higher order spectra) can detect deviations from linearity, stationarity or Gaussianity in the signal. Most of the biomedical signals are non-linear, non-stationary and non-Gaussian in nature and therefore it can be more advantageous to analyze them with HOS compared to the use of second order correlations and power spectra. In this paper we have discussed the application of HOS for different bio-signals. HOS methods of analysis are explained using a typical heart rate variability (HRV) signal and applications to other signals are reviewed.

Ultrafast near infrared sintering of TiO2 layers on metal substrates for dye-sensitized solar cells

A limiting step to roll-to-roll production of dye-sensitized solar cells on metals is TiO2 sintering (10-30 min). Near infrared (NIR) heating is a novel process innovation which directly heats titanium substrates giving rapid binder removal and sintering. NIR heating (for 12.5 s) at varying power gave titanium temperatures of 545, 685 and 817 degrees Celsius yielding cells with efficiencies of 2.9, 2.8 and 2.5%. Identical cells prepared in a conventional oven (1800 s) at 500, 600 and 800 degrees Celsius gave 2.9, 2.6 and 0.2% efficiency. NIR sintering is ultrafast and has a wide process window making it ideal for rapid manufacturing on metals.