Raman spectroscopy of kaolinites using different excitation wavelengths

The Raman spectra of both low- and high-defect kaolinites in the hydroxyl stretching and low-wavenumber region were obtained with excitation at three visible wavelengths of 633, 514 and 442 nm and a UV wavelength of 325 nm. The UV-excited spectra were comparable to those excited by the visible wavelengths. The Raman spectra show hydroxyl stretching bands at 3621 cm-1 attributed to the inner hydroxyl, at 3692 and 3684 cm-1 attributed to the longitudinal and transverse optic modes of the inner surface hydroxyls and at 3668 and 3653 cm-1 assigned to the out-of phase vibrations of the inner surface hydroxyls. Two bands were observed in the spectral profile at 3695 cm-1 for the high-defect kaolinite at 3698 and 3691 cm-1 and were assigned to TO/LO splitting. An increase in relative intensity of the transverse optic mode is observed with decrease in laser wavelength. The intensity of the out-of-phase vibrations at 3668 and 3653 cm-1 of the inner surface hydroxyls shows a linear relationship with the longitudinal and transverse optic modes. In the low-wavenumber region excellent correlation was found between the experimentally determined and the calculated band positions.

Raman spectroscopy of the copper chloride minerals nantokite, eriochalcite and claringbullite - implications for copper corrosion

The application of Raman spectroscopy to the study of the copper chloride minerals nantokite, eriochalcite and claringbullite has enabled the vibrational modes for the CuCl, CuOH and CuOH2 to be determined. Nantokite is characterised by bands at 205 and 155 cm-1 attributed to the transverse and longitudinal optic vibrations. Nantokite also has an intense band at 463 cm-1, eriochalcite at 405 and 390 cm-1 and claringbullite at 511 cm-1. These bands are attributed to CuO stretching modes. Water librational bands at around 672 cm-1 for eriochalcite have been identified and hydroxyl deformation modes of claringbullite at 970, 906 and 815 cm-1 are observed. Spectra of the three minerals are so characteristically different that the minerals are readily identified by Raman spectroscopy. The minerals are often determined in copper corrosion products by X-ray diffraction. Raman spectroscopy offers a rapid, in-situ technique for the identification of these corrosion products.

Infrared and infrared emission spectroscopy of gallium oxide α-GaO(OH) nanostructures

Infrared spectroscopy has been used to study nano to micro sized gallium oxyhydroxide α-GaO(OH), prepared using a low temperature hydrothermal route. Rod-like α-GaO(OH) crystals with average length of ~2.5 μm and width of 1.5 μm were prepared when the initial molar ratio of Ga to OH was 1:3. β-Ga2O3 nano and micro-rods were prepared through the calcination of α-GaO(OH) The initial morphology of α-GaO(OH) is retained in the β-Ga2O3 nanorods. The combination of infrared and infrared emission spectroscopy complimented with dynamic thermal analysis were used to characterise the α-GaO(OH) nanotubes and the formation of β-Ga2O3 nanorods. Bands at around 2903 and 2836 cm-1 are assigned to the -OH stretching vibration of α-GaO(OH) nanorods. Infrared bands at around 952 and 1026 cm-1 are assigned to the Ga-OH deformation modes of α-GaO(OH). A significant number of bands are observed in the 620 to 725 cm-1 region and are assigned to GaO stretching vibrations.

Poly(3-hexyl-thiophene) coil-wrapped single wall carbon nanotube investigated by scanning tunneling spectroscopy

Scanning Tunneling Spectroscopy was performed on a (15,0) single wall carbon nanotube partially wrapped by Poly(3-hexyl-thiophene). On the bare nanotube section, the local density of states is in good agreement with the theoretical model based on local density approximation and remarkably is not perturbed by the polymer wrapping. On the coiled section, a rectifying current-voltage characteristic has been observed along with the charge transfer from the polymer to the nanotube. The electron transfer from Poly(3-hexyl-thiophene) to metallic nanotube was previously theoretically proposed and contributes to the presence of the Schottky barrier at the interface responsible for the rectifying behavior.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

Small molecule–biopolymer interactions : Ultraviolet–visible and fluorescence spectroscopy and chemometrics

Interactions between small molecules with biopolymers e.g. the bovine serum albumin (BSA protein), are important, and significant information is recorded in the UV–vis and fluorescence spectra of their reaction mixtures. The extraction of this information is difficult conventionally and principally because there is significant overlapping of the spectra of the three analytes in the mixture. The interaction of berberine chloride (BC) and the BSA protein provides an interesting example of such complex systems. UV–vis and fluorescence spectra of BC and BSA mixtures were investigated in pH 7.4 Tris–HCl buffer at 37 °C. Two sample series were measured by each technique: (1) [BSA] was kept constant and the [BC] was varied and (2) [BC] was kept constant and the [BSA] was varied. This produced four spectral data matrices, which were combined into one expanded spectral matrix. This was processed by the multivariate curve resolution–alternating least squares method (MCR–ALS). The results produced: (1) the extracted pure BC, BSA and the BC–BSA complex spectra from the measured heavily overlapping composite responses, (2) the concentration profiles of BC, BSA and the BC–BSA complex, which are difficult to obtain by conventional means, and (3) estimates of the number of binding sites of BC.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.