Raman spectroscopy of the multi anion mineral arsentsumebite Pb2Cu(AsO4)(SO4)(OH) and in comparison with tsumebite Pb2Cu(PO4)(SO4)(OH)

The mineral arsentsumebite Pb2Cu(AsO4)(SO4)(OH), a copper arsenate-sulfate hydroxide of the brackebuschite group has been characterised by Raman spectroscopy. The brackebuschite mineral group are a series of monoclinic arsenates, phosphates and vanadates of the general formula A2B(XO4)(OH,H2O), where A may be Ba, Ca, Pb, Sr, while B may be Al, Cu2+,Fe2+, Fe3+, Mn2+, Mn3+, Zn and XO4 may be AsO4, PO4, SO4,VO4. Bands are assigned to the stretching and bending modes of SO42- AsO43- and HOAsO3 units. Raman spectroscopy readily distinguishes between the two minerals arsentsumebite and tsumebite. Raman bands attributed to arsenate are not observed in the Raman spectrum of tsumebite. Phosphate bands found in the Raman spectrum of tsumebite are not found in the Raman spectrum of arsentsumebite. Raman spectroscopy readily distinguishes the two minerals tsumebite and arsentsumebite.

Raman spectroscopy of the multi-anion mineral mallestigite Pb3Sb5+(SO4)(AsO4)(OH)6•3H2O – a mineral of archaeological significance

Some minerals are formed which show poorly defined X-ray diffraction patterns. Vibrational spectroscopy offers one of the few methods for the assessment of the structure of the oxyanions in such minerals. Among this group of minerals is mallestigite with formula Pb3Sb5+(SO4)(AsO4)(OH)6•3H2O. The objective of this research is to determine the molecular structure of the mineral mallestigite using vibrational spectroscopy. Raman and infrared bands are attributed to the AsO43- , SO42- and water stretching vibrations. Mallestigite is a mineral formed in ancient waste dumps such as occurs at Mallestiger, Carinthia, Austria and as such is a mineral of archaeological significance.

Raman spectroscopy of decrespignyite (Y,REE)4Cu(CO3)4Cl(OH)5•2(H2O) and in relation with other halogenated carbonates including bastnasite, hydroxybastnasite, parisite and northupite

Raman spectroscopy complimented with infrared spectroscopy has been used to study the rare earth based mineral decrespignyite (Y,REE)4Cu(CO3)4Cl(OH)5•2(H2O) and compared with the Raman spectra of a series of selected natural halogenated carbonates from different origins including bastnasite, parisite and northupite. The Raman spectrum of decrespignyite displays three bands are at 1056, 1070 and 1088 cm-1 attributed to the CO32- symmetric stretching vibration. The observation of three symmetric stretching vibrations is very unusual. The position of CO32- symmetric stretching vibration varies with mineral composition. Raman bands of decrespignyite show bands at 1391, 1414, 1489 and 1547 cm-1. Raman spectra of bastnasite, parisite and northupite show a single band at 1433, 1420 and 1554 cm-1 assigned to the ν3 (CO3)2- antisymmetric stretching mode. The observation of additional Raman bands for the ν3 modes for some halogenated carbonates is significant in that it shows distortion of the carbonate anion in the mineral structure. Four Raman bands are observed at 791, 815, 837 and 849 cm-1and assigned to the (CO3)2- ν2 bending modes. Raman bands are observed for decrespignyite at 694, 718 and 746 cm-1 and are assigned to the (CO3)2- ν4 bending modes. Raman bands are observed for the carbonate ν4 in phase bending modes at 722 cm-1 for bastnasite, 736 and 684 cm-1 for parisite, 714 cm-1 for northupite. Multiple bands are observed in the OH stretching region for decrespignyite, bastnasite and parisite indicating the presence of water and OH units in the mineral structure.

Raman spectroscopy of selected tsumcorite Pb(Zn,Fe3+)2(AsO4)2(OH,H2O) minerals –implications for arsenate accumulation

The presence of arsenic in the environment is a hazard. The accumulation of arsenate by a range of cations in the formation of minerals provides a mechanism for the accumulation of arsenate. The formation of the tsumcorite minerals is an example of a series of minerals which accumulate arsenate. There are about twelve examples in this mineral group. Raman spectroscopy offers a method for the analysis of these minerals. The structure of selected tsumcorite minerals with arsenate and sulphate anions were analysed by Raman spectroscopy. Isomorphic substitution of sulphate for arsenate is observed for gartrellite and thometzekite. A comparison is made with the sulphate bearing mineral natrochalcite. The position of the hydroxyl and water stretching vibrations are related to the strength of the hydrogen bond formed between the OH unit and the AsO43- anion. Characteristic Raman spectra of the minerals enable the assignment of the bands to specific vibrational modes.

Raman spectroscopy of the multi-anion mineral schlossmacherite (H3O,Ca)Al3(AsO4,PO4,SO4)2(OH)6

The mineral schlossmacherite (H3O,Ca)Al3(AsO4,PO4,SO4)2(OH)6 , a multi-cation-multi-anion mineral of the beudantite mineral subgroup has been characterised by Raman spectroscopy. The mineral and related minerals functions as a heavy metal collector and is often amorphous or poorly crystalline, such that XRD identification is difficult. The Raman spectra are dominated by an intense band at 864 cm-1, assigned to the symmetric stretching mode of the AsO43- anion. Raman bands at 809 and 819 cm-1 are assigned to the antisymmetric stretching mode of AsO43- . The sulphate anion is characterised by bands at 1000 cm-1 (ν1), and at 1031, 1082 and 1139 cm-1 (ν3). Two sets of bands in the OH stretching region are observed: firstly between 2800 and 3000 cm-1 with bands observed at 2850, 2868, 2918 cm-1 and secondly between 3300 and 3600 with bands observed at 3363, 3382, 3410, 3449 and 3537 cm-1. These bands enabled the calculation of hydrogen bond distances and show a wide range of H-bond distances.

Raman spectroscopic study of the mineral shattuckite Cu5(SiO3)4(OH)2

Shattuckite Cu5(SiO3)4(OH)2 is a copper hydroxy silicate and is commonly known as a ‘healing’ mineral. Three shattuckite mineral samples from three different origins were analysed by Raman spectroscopy. Some Raman bands are common in the spectra of the minerals. Raman bands at around 890, 1058 and 1102 are described as the ν3 –SiO3 antisymmetric stretching vibrations. The Raman band at 670 cm-1 is assigned to the ν4 bending modes of the -SiO3 units and the band at around 785 cm-1is due to Si-O-Si chain stretching mode. Raman (and infrared) spectroscopy proves that water is in the molecular structure of shattuckite; thus the formula is better written as Cu5(SiO3)4(OH)2•xH2O.

Single crystal raman spectroscopy of natural finnemanite and comparison with the synthesised analogue

The single crystal Raman spectra of natural mineral finnemanite Pb5(AsO3)3Cl from the Långban locality, Filipstad district, Värmland province, Sweden are presented for the first time. It is a hexagonal mineral belonging to the ortho arsenite group, where the [AsO3]3- ion is isolated. The spectra of finnemanite are characterized by a strong band at 734 cm-1 overlying a shoulder at 726 cm-1, and broad overlapping bands in the lower wavenumber with the strongest band positioned at 174 cm-1. Band assignments were made based on band symmetry, experimental band positions from literature and DFT calculated Raman spectrum, and spectral comparison with other ortho arsenite minerals reinerite, cafarsite, and nealite and synthetic lead arsenite compounds Pb2(AsO2)3Cl, Pb2As2O5, and PbAs2O4 . The band at 734 cm-1 was assigned to υ1(AsO3), bands at 726 and 640 cm-1 assigned to υ3, 372 and 357 cm-1 to υ2, and 244, 239 and 207 cm-1 to υ4. The single crystal spectra of finnemanite showed good mode separation, allowing bands to be assigned a symmetry species of Ag, E1g, or E2g.

Single crystal raman spectroscopy of natural paulmooreite Pb2As2O5 and in comparison with the synthesised analogue

The single crystal Raman spectra of natural mineral paulmooreite Pb2As2O5 from the Långban locality, Filipstad district, Värmland province, Sweden are presented for the first time. It is a monoclinic mineral containing an isolated [As2O5]4-. Depolarised and single crystal spectra of the natural and synthetic sample compare favorably and are characterized by strong bands around 186 and 140 cm-1 and three medium bands at 800 – 700 cm-1. Band assignments were made based on band symmetry and spectral comparison between experimental band positions and those resulting from Hartree-Fock calculation of an isolated [As2O5]4- ion. Spectral comparison was also made with lead arsenites such as synthetic PbAs2O4 and Pb2(AsO2)3Cl and natural finnemanite in order to determine the contribution of the terminal and bridging O in paulmooreite. Bands at 760 – 733 cm-1 were assigned to terminal As-O vibrations, whereas stretches of the bridging O occur at 562 and 503 cm-1. The single crystal spectra showed good mode separation, allowing bands to be assigned a symmetry species of Ag or Bg.

Infrared and Raman spectroscopic studies of archaeological materials

The use of vibrational spectroscopic techniques to characterise historical artefacts and art works continues to grow and to provide the archaeologist and art historian with significant information with which to understand the nature and activities of previous peoples and civilizations. In addition, conservators can gain knowledge of the composition of artworks or historical objects and so are better equipped to ensure their preservation. Both infrared and Raman have been widely used. Microspectroscopy is the preferred sampling technique as it requires only a very small sample, which often can be recovered. The use of synchrotron radiation in conjunction with IR microspectroscopy is increasing because of the substantial benefits in terms of improved spatial resolution and signal-to-noise ratio. The key trend for the future is the growth in the use of portable instruments, both IR and Raman, which are becoming important because they allow non-destructive measurements to be made in situ, for example at an archaeological site or at a museum.

Combined time- and space-resolved Raman spectrometer for the non-invasive depth profiling of chemical hazards

A time-resolved inverse spatially offset Raman spectrometer was constructed for depth profiling of Raman-active substances under both the lab and the field environments. The system operating principles and performance are discussed along with its advantages relative to traditional continuous wave spatially offset Raman spectrometer. The developed spectrometer uses a combination of space- and time-resolved detection in order to obtain high-quality Raman spectra from substances hidden behind coloured opaque surface layers, such as plastic and garments, with a single measurement. The time-gated spatially offset Raman spectrometer was successfully used to detect concealed explosives and drug precursors under incandescent and fluorescent background light as well as under daylight. The average screening time was 50 s per measurement. The excitation energy requirements were relatively low (20 mW) which makes the probe safe for screening hazardous substances. The unit has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than previous picosecond-based systems, to provide a functional platform for in-line or in-field sensing of chemical substances.

Non-invasive, quantitative analysis of drug mixtures in containers using spatially offset Raman spectroscopy (SORS) and multivariate statistical analysis

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for non-invasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform non-invasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.

Raman spectroscopy of the multianion mineral gartrellite-PbCu(Fe3+,Cu)(AsO4)2(OH,H2O)2

The multianion mineral gartrellite PbCu(Fe3+,Cu)(AsO4)2(OH,H2O)2 has been studied by a combination of Raman and infrared spectroscopy. The vibrational spectra of two gartrellite samples from Durango and Ashburton Downs were compared. Gartrellite is one of the tsumcorite mineral group based upon arsenate and sulphate anions. Crystal symmetry is either triclinic in the case of an ordered occupation of two cationic sites, triclinic due to ordering of the H bonds in the case of species with 2 water molecules per formula unit, or monoclinic in the other cases. Characteristic Raman spectra of the minerals enable the assignment of the bands to specific vibrational modes. These spectra are related to the structure of gartrellite. The position of the hydroxyl and water stretching vibrations are related to the strength of the hydrogen bond formed between the OH unit and the AsO4 anion.

Raman spectroscopic study of the mineral arsenogorceixite BaAl3AsO3(OH)(AsO4,PO4)(OH,F)6

Arsenogorceixite BaAl3AsO3(OH)(AsO4,PO4)(OH,F)6 belongs to the crandallite mineral subgroup of the alunite supergroup. Arsenogorceixite forms a continuous series of solid solutions with related minerals including gorceixite, goyazite, arsenogoyazite, plumbogummite and philipsbornite. Two minerals from (a) Germany and (b) from Ashburton Downs, Australia were analysed by Raman spectroscopy. The spectra show some commonality but the intensities of the peaks vary. Sharp intense Raman bands for the German sample, are observed at 972 and 814 cm−1 attributed to the ν1 PO43− and AsO43− symmetric stretching modes. Raman bands at 1014, 1057, 1148 and 1160 cm−1 are attributed to the ν1 PO2 symmetric stretching mode and ν3 PO43− antisymmetric stretching vibrations. Raman bands at 764 and 776 cm−1 and 758 and 756 cm−1 are assigned to the ν3 AsO43− antisymmetric stretching vibrations. For the Australian mineral, the ν1 PO43− band is found at 973 cm−1. The intensity of the arsenate bands observed at 814, 838 and 870 cm−1 is greatly enhanced. Two low intensity Raman bands at 1307 and 1332 cm−1 are assigned to hydroxyl deformation modes. The intense Raman band at 441 cm−1 with a shoulder at 462 cm−1 is assigned to the ν2 PO43− bending mode. Raman bands at 318 and 340 cm−1 are attributed to the (AsO4)3−ν2 bending. The broad band centred at 3301 cm−1 is assigned to water stretching vibrations and the sharper peak at 3473 cm−1 is assigned to the OH stretching vibrations. The observation of strong water stretching vibrations brings into question the actual formula of arsenogorceixite. It is proposed the formula is better written as BaAl3AsO3(OH)(AsO4,PO4)(OH,F)6·xH2O. The observation of both phosphate and arsenate bands provides a clear example of solid solution formation.

Deep Raman spectroscopy for the non-invasive standoff detection of concealed chemical threat agents

Deep Raman spectroscopy has been utilized for the standoff detection of concealed chemical threat agents from a distance of 15 meters under real life background illumination conditions. By using combined time and space resolved measurements, various explosive precursors hidden in opaque plastic containers were identified non-invasively. Our results confirm that combined time and space resolved Raman spectroscopy leads to higher selectivity towards the sub-layer over the surface layer as well as enhanced rejection of fluorescence from the container surface when compared to standoff spatially offset Raman spectroscopy. Raman spectra that have minimal interference from the packaging material and good signal-to-noise ratio were acquired within 5 seconds of measurement time. A new combined time and space resolved Raman spectrometer has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than picosecond-based laboratory systems.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.