Towards the in vivo prediction of fragility fractures with Raman spectroscopy

Fragility fractures, those fractures which result from low level trauma, have a large and growing socio‐economic cost in countries with aging populations. Bone‐density‐based assessment techniques are vital for identifying populations that are at higher risk of fracture, but do not have high sensitivity when it comes to identifying individuals who will go on to have their first fragility fracture. We are developing Spatially Offset Raman Spectroscopy (SORS) as a tool for retrieving chemical information from bone non‐invasively in vivo. Unlike X‐ray‐based techniques SORS can retrieve chemical information from both the mineral and protein phases of the bone. This may enable better discrimination between those who will or will not go on to have a fragility fracture because both phases contribute to bone's mechanical properties. In this study we analyse excised bone with Raman spectroscopy and multivariate analysis, and then attempt to look for similar Raman signals in vivo using SORS. We show in the excised work that on average, bone fragments from the necks of fractured femora are more mineralised (by 5–10%) than (cadaveric) non‐fractured controls, but the mineralisation distributions of the two cohorts are largely overlapped. In our in vivo measurements, we observe similar, but as yet statistically underpowered, differences. After the SORS data (the first SORS measurements reported of healthy and diseased human cohorts), we identify methodological developments which will be used to improve the statistical significance of future experiments and may eventually lead to more sensitive prediction of fragility fractures. © 2015 The Authors. Journal of Raman Spectroscopy Published by John Wiley & Sons, Ltd.     

Non‐invasive depth profiling by space and time‐resolved Raman spectroscopy

Time‐resolved Raman spectroscopy, spatially offset Raman spectroscopy and time‐resolved spatially offset Raman spectroscopy (TR‐SORS) have proven their capability for the non‐invasive profiling of deep layers of a sample. Recent studies have indicated that TR‐SORS exhibits an enhanced selectivity toward the deep layers of a sample. However, the enhanced depth profiling efficiency of TR‐SORS, in comparison with time‐resolved Raman spectroscopy and spatially offset Raman spectroscopy, is yet to be assessed and explained in accordance to the synergistic effects of spatial and temporal resolutions. This study provides a critical investigation of the depth profiling efficiency of the three deep Raman techniques. The study compares the efficiency of the various deep Raman spectroscopy techniques for the stand‐off detection of explosive precursors hidden in highly fluorescing packaging. The study explains for the first time the synergistic effects of spatial and temporal resolutions in the deep Raman techniques and their impact on the acquired spectral data. Copyright © 2013 John Wiley & Sons, Ltd.     

A line‐scan hyperspectral Raman system for spatially offset Raman spectroscopy

Spatially offset Raman spectroscopy (SORS) is a technique that can obtain subsurface layered information by collecting Raman spectra from a series of surface positions laterally offset from the excitation laser. Currently optical fiber probes are used as major tools in SORS measurement, which are either slow (single fiber probe with mechanical movement) or restricted in selecting offset range and interval (fiber probe array). This study proposes a new method to conduct SORS measurement based on a newly developed line‐scan hyperspectral Raman imaging system. A 785‐nm point laser was used as an excitation source. A detection module consisting of an imaging spectrograph and a charge‐coupled device camera was used to acquire line‐shape SORS data in a spectral region of −592 to 3015 cm⁻¹. Using a single scan, the system allowed simultaneous collection of a series of Raman spectra in a broad offset range (e.g. 0–36 mm in two sides of the incident laser) with a narrow interval (e.g. 0.07 mm). Four layered samples were created by placing butter slices with thicknesses of 1, 4, 7, and 10 mm on top of melamine powder, providing different individual Raman characteristics to test the line‐scan SORS technique. Self‐modeling mixture analysis (SMA) was used to analyze the SORS data. Raman spectra from butter and melamine were successfully retrieved for all four butter‐on‐melamine samples using the SMA method. The line‐scan SORS measurement technique provides a flexible and efficient method for subsurface evaluation, which has potential to be used for food safety and quality inspection. Copyright © 2015 John Wiley & Sons, Ltd.     

空间偏移拉曼光谱技术的发展及应用

传统拉曼光谱只能探测样品的表层信息,或者只能穿透透明的表层探测样品内部,对多层不透明或不透明包装的样品检测则不适用了,比如搜索隐蔽的爆炸物、识别有包装的假药、无损检测骨骼疾病等。空间偏移拉曼光谱（SORS）技术是一种新型光谱检测技术,能够非侵入不透明包装或表层直接获得样品内部深层特征信息,这一技术的出现解决了上述的难题。首先详细介绍了SORS技术的工作原理：其根本原理在于光子迁移理论,其系统激光光源的入射焦点与光谱系统中收集透镜的焦点在待测样品表层空间上偏移一定的距离ΔS。当激光入射到待测样品表层时,表层样品被激发或散射出宽带荧光,其中有一部分散射光将到达样品内部,样品内部深层处产生的拉曼散射光子相比于样品表层的光子在散射过程中更易于横向迁移,经多次散射后返回样品表层被光谱仪器接收系统收集。到达样品内部不同深度ΔH的散射光返回表层后的位置距离激光光源入射点在样品表层上有不同的偏移距离ΔS。当空间偏移距离ΔS＝0时,激光光源入射点与拉曼光谱收集点重合,此处激发的光子密度最大,系统收集到的拉曼光谱信号大部分来自样品表层,样品深层拉曼信号被淹没;当空间偏移距离ΔS≠0时,光谱仪器收集到的拉曼光谱信号中来自表层的信号衰减很快,来自样品深层的信号衰减较慢,使得更深层的拉曼散射光子比重变大,从而实现光谱分离,再结合多元数据分析方法可以获得样品内部不同深层次的拉曼光谱,即空间偏移拉曼光谱。该技术具有很好抑制表层物质拉曼光谱和荧光光谱干扰的能力,特别适用于隐蔽在不透明包装材料下的物质拉曼光谱的提取,从而快速、非侵入地对目标物成分进行鉴定。其次介绍了SORS技术的特点。SORS技术是拉曼光谱的衍生技术,具备拉曼光谱技术的制样简单、水分干扰小、样品消耗量小、灵敏度高等全部优点,除此之外,有效抑制荧光、深层检测、非侵入无损检测、远距离检测等特点,这些特点有效提高了拉曼光谱强度,降低用户的检测和生产成本以及提高检测人员的人身安全。同时概述并对比了SORS技术现有的三种工作方式：标准SORS、逆SORS和倾斜SORS。标准SORS技术可进行远距离非接触测量,逆SORS较之标准SORS具有更高的灵敏度和抗光谱扭曲的潜力,而且入射的有效光照面和空间偏移距离ΔS是可控的,避免了样品过热;倾斜SORS具有较高的检测灵敏度,而且实验装置容易实现。然后在大量调研文献的基础上综述了近些年来SORS技术结合其他技术在化工生产、安检、生物医学、考古艺术、食品安全、稽查打假以及国防安全等多个领域的国内外发展和应用。最后指出了SORS技术目前存在的问题并展望了该技术未来的发展前景。     

Photon migration of Raman signal in bone as measured with spatially offset Raman spectroscopy

Spatially offset Raman spectroscopy (SORS) is currently being developed as an in vivo tool for bone disease detection, but to date, information about the interrogated volume as influenced by the light propagation and scattering characteristics of the bone matrix is still limited. This paper seeks to develop our general understanding of the sampling depths of SORS in bone specimens as a function of the applied spatial offset. Equine metacarpal bone was selected as a suitable specimen of compact cortical bone large enough to allow several thin slices (600 µm) to be cut from the dorsal surface. Photon migration at 830‐nm excitation was studied with five bone slices and a 380‐µm‐thin polytetrafluoroethylene (PTFE) slice placed consecutively between the layers. To optimize Raman signal recovery of the PTFE with increasing depth within the bone stack required a corresponding increase in spatial offset. For example, to sample effectively at 2.2‐mm depth within the bone required an optimal SORS offset of 7 mm. However, with a 7‐mm offset, the maximum accessible penetration depth from which the PTFE signal could be still recovered was 3.7 mm. These results provide essential basic information for developing SORS technology for medical diagnostics in general and optimizing sampling through bone tissue, permitting a better understanding of the relationship between the offset and depth of bone assessed, in particular. Potential applications include the detection of chemically specific markers for changes in bone matrix chemistry localized within the tissue and not present in healthy bone. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.     

Subsurface analysis of painted sculptures and plasters using micrometre‐scale spatially offset Raman spectroscopy (micro‐SORS)

A recently developed variant of spatially offset Raman spectroscopy (SORS) for the non‐invasive analysis of thin painted layers, micro‐SORS, has been applied, for the first time, to real objects of Cultural Heritage – namely painted sculptures and plasters. Thin layers of paint originating from multiple restoration processes often applied over many centuries have been analysed non‐destructively using micro‐SORS to depths inaccessible to, or unresolvable into separate layers, by conventional confocal Raman microscopy. The concept has been demonstrated on several artistic artefacts of historical significance originating from Italy and dating from the medieval to the 18th century. The technique extends the depth applicability of Raman spectroscopy and with its inherently high chemical specificity that expands the portfolio of existing non‐destructive analytical tools in Cultural Heritage permitting to avoid cross‐sectional analysis often necessitated with this type of samples with conventional Raman microscopy. Currently, the method is non‐invasive only for artworks that can be placed under Raman microscope although there is a prospect for its use in a mobile system with largely removed restrictions on sample dimensions. © 2015 The Authors Journal of Raman Spectroscopy Published by John Wiley & Sons Ltd.     

Application of portable Raman spectroscopy and benchtop spatially offset Raman spectroscopy to interrogate concealed biomaterials

In this paper, we demonstrate the ability of portable Raman spectroscopy and benchtop spatially offset Raman spectroscopy (SORS) techniques to rapidly identify real and fake ivory samples. Both techniques were able to identify exposed genuine from fake ivory samples. In contrast to conventional Raman spectroscopy, SORS was, in addition, able to identify ivory concealed by plastics, paints, varnishes and cloth. Application of the SORS technique allows the interrogation of biomaterial samples through materials in which conventional Raman spectroscopic instrumentation cannot penetrate. Copyright © 2009 John Wiley & Sons, Ltd.     

Contrasting confocal with defocusing microscale spatially offset Raman spectroscopy

The study compares and contrasts conventional confocal Raman microscopy/spectroscopy (CRM) with a recently developed micrometer scale defocusing spatially offset Raman spectroscopy (micro‐SORS), a method providing a new analytical capability for investigating non‐destructively the chemical composition of subsurface, micrometer‐scale‐thick diffusely scattering layers at depths beyond the reach of CRM. Because of close similarities between the two techniques and comparable embodiment of the instrumentations, but radically different interpretations of data, it is crucially important to recognise which type of method is pertinent to a specific measurement. The distinction comes principally from the nature of sample, whether turbid (micro‐SORS measurement) or transparent (CRM measurement) on the spatial scale of the axial (z‐)scan of the measurement. Which type of sample one deals with may not always be easily recognisable with micro‐scale thick layers, and the study therefore also presents a simple method for suggesting whether CRM or micro‐SORS methodology applies. This test relies on an axial (z‐)scan performed through the sample in both the positive and negative directions from the normal, imaged sample surface position using conventional CRM instrument. The absence or presence of symmetry or asymmetry of the intensity profiles of measured Raman signals around the imaged sample surface position as a function of sample axial displacement then suggests which interpretation could apply. The study paves a way for the development of micro‐SORS as a widely applicable analytical tool deployable on conventional Raman microscopes. Copyright © 2015 John Wiley & Sons, Ltd.     

基于逆向空间偏移拉曼光谱分析技术的无损药物检测方法研究

发展新型药物检测技术不仅能够杜绝假药对健康和生命的危害,更可以避免假药对社会道德和商业风气等产生不良影响。该研究工作,通过建立逆向空间偏移拉曼光谱（SORS）实验装置,克服了传统拉曼探测深度有限（约几百微米）的应用瓶颈,以无损、非接触的方式,克服不/半透明容器光学背景对光谱测量结果产生的影响,实现多种空间偏移量（Δs）条件下,样品特征光谱信息检测与分析,为开发基于逆向SORS技术的新型药物检测方法奠定实验基础。实验装置搭建过程中,采用785 nm半导体激光器与WITec UHTS300型拉曼光谱仪构建逆向SORS光谱分析装置。通过使用准直光束照射锥透镜形成环形激发光斑,并控制锥透镜与样品之间的距离,实现Δs连续可控变化。利用所搭建的光谱检测装置,分别测量聚乙烯方瓶（厚度为1.5 mm）和聚四氟乙烯离心管（厚度为4 mm）内对乙酰氨基酚和甲硝唑的拉曼特征光谱。利用环形光束照射会抑制容器峰强度这一特点,选取容器拉曼特征峰作为标准峰,分别对点光斑（Spot）和环形（Ring）光斑测量结果进行归一化处理,并将其强度相减（Ring-Spot）,得到逆向SORS光谱测量结果。实验结果表明,逆向SORS光谱检测方法能够克服表层容器光学背景对测量结果产生的干扰性因素,真实反映不/半透明容器内样品的分子指纹光谱信息。在实验测量范围内,当环形光束半径增大1倍时,聚乙烯方瓶内对乙酰氨基酚拉曼特征峰强度增大6倍,而聚四氟乙烯离心管内的甲硝唑各特征峰强度增强1倍。以上实验结果表明,逆向SORS技术能够准确检测不/半透明容器内,或有漫散射介质覆盖的样品深层化学成分的指纹光谱。通过提高系统信噪比并优化系统结构与功能,在建立小型化、集成化检测系统的条件下,逆向SORS技术可与现有的多种药物检测技术相互补充,发展成一种快捷、准确、操作简便的新型药物检测手段。     

基于逆向空间偏移拉曼光谱技术的多层混浊样品深层分析研究

空间偏移拉曼光谱（SORS）能够准确、快速、无损检测多层混浊介质样品深层生化构成信息。该研究通过搭建集成化逆向SORS光谱分析装置,在实现逆向SORS和背散射式拉曼光谱两种不同的光谱检测模式的基础上,检测与分析了不同空间偏移量（Δs）条件下双/三层组织模型内的深层拉曼光谱信息,并根据几何光学理论和投影测量原理,量化标定了Δs与锥透镜空间位置之间的关系,这为精确控制光谱检测条件提供了保障。为了验证该装置的检测能力,采用由羊肩胛骨/对乙酰氨基酚组成的双层模型和猪皮/硅橡胶/对乙酰氨基酚组成的三层模型,获得不同Δs条件下包含样品表层和深层信息的混合光谱。并进一步对该混合光谱进行面积归一化处理,观察到随着Δs的增大样品表层的拉曼贡献逐渐减小,而第二层以及第三层的拉曼贡献逐渐增大的现象。在此基础上,通过选择模型中每层物质的拉曼特征峰计算其相对拉曼强度,分析研究了相对拉曼强度、空间偏移量与样品厚度三者之间关系,即当Δs增大时相对拉曼强度比值随之增加,这清晰地表明深层物质的拉曼强度增加。然而,在同一Δs条件下,相对拉曼强度随着表层物质厚度的增大而减小。以上实验结果表明,我们搭建的集成化逆向SORS光谱分析装置可从深度达8 mm的生物模型下获取光谱信息,并证明了该装置在经皮无损探测方面的应用价值。     

Passive signal enhancement in spatially offset Raman spectroscopy

We demonstrate experimentally, for the first time, the feasibility of enhancing signals in Spatially Offset Raman Spectroscopy (SORS) using a dielectric bandpass filter, building on our earlier experimental work on the enhancement of transmission Raman signals. The method is shown to lead to the enhancement of both the surface and subsurface Raman layer signal improving the signal‐to‐noise ratio of Raman spectra from the deep areas of samples, thus enhancing the technique's sensitivity and penetration depth. The filter is placed over the laser illumination zone, on the sample surface acting as a ‘unidirectional’ mirror transmitting the collimated laser beam on one side and reflecting photons escaping from the sample back into it. This enhances the degree of coupling of laser radiation into the medium and associated generated Raman signal. The feasibility study was performed on a two‐layer sample with the second layer located at the limit of the penetration depth of the method for this sample. The sample consisted of a 2.2‐mm over‐layer of a thinned paracetamol tablet followed by a 2‐mm layer of trans‐stilbene powder. The Raman signal was collected from a spatially offset region through a hole fabricated within the filter. The experiments demonstrate the presence of an enhancement of the Raman signal from both the layers by a factor of 4.4–4.5 and the improved signal‐to‐noise ratio of sublayer signal by a factor of 2.2, in agreement with photon shot noise dominated signal. Copyright © 2008 John Wiley & Sons, Ltd.     

Deconvolution of pure component FT‐Raman spectra from thermal emission of barium sulfate and graphite samples using the BTEM algorithm

Band‐target entropy minimization (BTEM) was applied for the extraction of pure component Raman spectra from samples exhibiting a significant thermal background due to sample emission. In this method, singular value decomposition was first used to calculate the right singular vectors of the spectroscopic data matrix. Then the non‐noise right singular vectors were examined for localized spectral features, which were subsequently used for spectral recovery. These local features were targeted with the BTEM algorithm to recover the pure component Raman spectra. Accordingly, the interfering thermal background was removed. This method of analysis is applied to graphite and barium sulfate Raman spectroscopic data. Copyright © 2006 John Wiley & Sons, Ltd.     

Information‐theoretic chemometric analyses of Raman data for chemical reaction studies

A methodology of multivariate chemometric techniques based on the information‐theoretic approach was applied for elucidating chemical reaction information from a Raman data array R _m×ν that arises from in situ reaction monitoring. This reaction‐induced dynamic dataset R _m×ν can be contaminated by random cosmic ray spikes found in the midst of characteristic spectral variations associated with the disappearance or emergence of Raman active reactants, intermediates and products. Such spurious cosmic spikes were identified and removed using a novel and fast numerical approach based on maximum and minimum spectral entropy principles while preserving the genuine reaction‐induced spectral variations. Subsequently, the band‐target entropy minimization (BTEM) algorithm, a minimum spectral entropy based self‐modeling curve resolution technique, was applied to recover the pure component spectra of Raman active chemical species. Information gain through the chemometric analyses was calculated using information entropies with base 2 logarithm. This sequence of information‐theoretic chemometric analyses (or transinformations) was successfully tested on the reaction spectral data obtained from alcoholysis of acetic anhydride, which contains four Raman active chemical species. It is envisioned that this series of multivariate statistical analyses will be useful in chemical reaction studies and process analytical technology (PAT) applications that utilize in situ Raman spectroscopy to monitor transient dynamic changes in chemical concentrations, and also in Raman microscopy/imaging data containing spatial variations. Copyright © 2010 John Wiley & Sons, Ltd.     

Use of thermo‐Raman spectroscopy and chemometric analysis to identify dehydration steps of hydrated inorganic samples—application to copper sulfate pentahydrate

In situ thermo‐Raman spectroscopy (TRS) measurements were performed in order to investigate solid‐phase transformation of the copper sulfate pentahydrate from room temperature up to 300 °C. Band‐target entropy minimization (BTEM), a blind‐source separation algorithm, was employed in order to identify and reconstruct the pure component spectra of the species involved in the dehydration process. In spite of low signal‐to‐noise ratio and elevated baseline spectral data, BTEM was successfully utilized to identify and reconstruct four pure component spectra of copper sulfate pentahydrate, trihydrate, monohydrate, and anhydrate, which were formed during this thermally induced process. Subsequent mapping of these four pure component spectral estimates back onto the preprocessed spectra yielded the relative concentrations of each individual species. Finally, the transition temperatures of each dehydration step could be unambiguously deduced from the obtained concentration profile. The current study shows that combined thermo‐Raman spectroscopy and chemometric analysis provides an effective tool to determine the dehydration temperatures as well as to identify the structures of each individual species involved in a solid‐phase dehydration process. Copyright © 2009 John Wiley & Sons, Ltd.     

SERS‐based detection of barcoded gold nanoparticle assemblies from within animal tissue

We have explored the potential of deep Raman spectroscopy, specifically surface‐enhanced spatially offset Raman spectroscopy (SESORS), for non‐invasive detection from within animal tissue, by employing SERS‐barcoded nanoparticle (NP) assemblies as the diagnostic agent. This concept has been experimentally verified in a clinically‐relevant backscattered Raman system with an excitation line of 785 nm under ex vivo conditions. We have shown that our SORS system, with a fixed offset of 2–3 mm, offered sensitive probing of injected 2‐quinolinethiol‐barcoded NP assemblies through animal tissue containing both protein and lipid. In comparison with that of non‐aggregated SERS‐barcoded gold NPs, we have demonstrated that the tailored SERS‐barcoded aggregated NP assemblies have significantly higher detection sensitivity. We report that these NP assemblies can be readily detected at depths of 7–8 mm from within animal proteinaceous tissue with high signal‐to‐noise ratio. In addition, they could also be detected from beneath 1–2 mm of animal tissue with high lipid content, which generally poses a challenge because of high absorption of lipids in the near‐infrared region. We have also shown that the signal intensity and signal‐to‐noise ratio at a particular depth is a function of the SERS tag concentration used and that our SORS system has a 2‐quinolinethiol detection limit of 10⁻⁶ M. Higher detection depths may possibly be obtained with optimization of the NP assemblies, along with improvements in the instrumentation. Such NP assemblies offer prospects for in vivo, non‐invasive detection of tumours along with scope for incorporation of drugs and their targeted and controlled release at tumour sites. These diagnostic agents combined with drug delivery systems could serve as a ‘theranostic agent’, an integration of diagnostics and therapeutics into a single platform. Copyright © 2013 John Wiley & Sons, Ltd.     

Detailed spectroscopic analysis of complex multi‐component materials using a combination of Raman mapping with BTEM

The combined application of Raman microscopy and self‐modeling curve resolution techniques can address a wide range of material characterization problems. In particular, the combination of Raman microscopy and the Band‐Target Entropy Minimization (BTEM) algorithm has been applied to various organic, inorganic, pharmaceutical and bio‐material related problems. In the present contribution, the principles behind this type of analysis are reviewed, followed by a number of case‐by‐case studies. For each of these examples, a Raman microscopic mapping measurement (consisting of 100 s up to 1000 s of spectra) is performed, followed by BTEM analysis which provides the underlying pure component spectra of the constituents present in the system without the use of any a priori information. In most cases, outstanding signal‐to‐noise ratios for components at the 0.1‐1.0 % level can be obtained, and sometimes trace constituents can also be detected. Subsequently, the identity of the components can be determined by comparison to spectral libraries. Finally, the reconstructed pure component spectra can be further used to obtain the spatial distribution of the constituents present in the sample. Copyright © 2012 John Wiley & Sons, Ltd.     

Experimentally validated Raman Monte Carlo simulation for a cuboid object to obtain Raman spectroscopic signatures for hidden material

In conventional Raman spectroscopic measurements of liquids or surfaces the preferred geometry for detection of the Raman signal is the backscattering (or reflection) mode. For non‐transparent layered materials, sub‐surface Raman signals have been retrieved using spatially offset Raman spectroscopy (SORS), usually with light collection in the same plane as the point of excitation. However, as a result of multiple scattering in a turbid medium, Raman photons will be emitted in all directions. In this study, Monte Carlo simulations for a three‐dimensional layered sample with finite geometry have been performed to confirm the detectability of Raman signals at all angles and at all sides of the object. We considered a non‐transparent cuboid container (high density polyethylene) with explosive material (ammonium nitrate) inside. The simulation results were validated with experimental Raman intensities. Monte Carlo simulation results reveal that the ratio of sub‐surface to surface signals improves at geometries other than backscattering. In addition, we demonstrate through simulations the effects of the absorption and scattering coefficients of the layers, and that of the diameter of the excitation beam. The advantage of collecting light from all possible 4π angles, over other collection modes, is that this technique is not geometry specific and molecular identification of layers underneath non‐transparent surfaces can be obtained with minimal interference from the surface layer. To what extent all sides of the object will contribute to the total signal will depend on the absorption and scattering coefficients and the physical dimensions. Copyright © 2015 John Wiley & Sons, Ltd.     

Pure component Raman spectral reconstruction from glazed and unglazed Yuan,Ming, and Qing shards: a combined Raman microscopy and BTEM study

Raman mapping measurements were performed on the glazed and unglazed surfaces of shards excavated from Yuan, Ming, and Qing dynasty strata. A number of areas on each surface were chosen. Circa 21 × 21 pixels were measured for each area using both 514 and 785‐nm laser as the Raman excitation. Data were collected from 100–3600 cm⁻¹. Many sets of spectra exhibited very intense fluorescence. In spite of the intense fluorescence, the resulting sets of spectra were collated and analyzed together using the band‐target entropy minimization (BTEM) algorithm. Pure component spectral estimates of many of the major components were achieved, without the use of any a priori information such as spectral libraries. These include α‐silica quartz, carbon, anatase, cobalt oxides, hematite, glassy silicate, and lanthanide complexes. In addition, two further unidentified pure component spectra A and B were recovered as well as an interference pattern due to the microscopic texture of the shards (associated with small particle/thin layer domains). The carbon was primarily present in elemental form, i.e. mixture of amorphous and graphitic (unordered and ordered domains); however there is an evidence of some partial oxidation, i.e. formation of carboxylates. The interference patterns and the lanthanide complexes were only observed when using the longer wavelength red laser. The cobalt oxides and the anatase were only observed when using the green laser. In summary, the combination of Raman microscopy and BTEM has allowed the enumeration of many of the underlying spectral patterns present and hence unambiguous identification of the major individual components present in the archaeological samples. This approach would appear applicable to other classes of archaeological materials as well. Limitations and extensions of the present approach are discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Triply resonant Raman scattering in perovskite semiconductor CsSnI3

We report on the first‐order and second‐order Raman scattering (SORS) by longitudinal optical (LO) phonons in perovskite semiconductor CsSnI₃. The intensity of SORS is stronger than that of the first order. The spectral line shape of SORS is asymmetric and much broader than that of the first order. It is identified that the strong SORS intensity is attributable to the triply enhanced resonant process, which is naturally implemented through the peculiar band structure of this semiconductor compound having two adjacent parallel conduction bands with a separation close to the energy of two LO phonons. Copyright © 2012 John Wiley & Sons, Ltd.     

Comparison of chemometric methods in the analysis of pharmaceuticals with hyperspectral Raman imaging

Chemical imaging method of vibrational spectroscopy, which provides both spectral and spatial information, creates a three‐dimensional (3D) dataset with a huge amount of data. When the components of the sample are unknown or their reference spectra are not available, the classical least squares (CLS) method cannot be applied to create visualized distribution maps. Raman image datasets can be evaluated even in such cases using multivariate (chemometric) methods for extracting the needed hidden information. The capability of chemometrics‐assisted Raman mapping is evaluated through the analysis of pharmaceutical tablets (considered as unknown) with the aim of estimating the pure component spectra based on the collected Raman image. Six chemometric methods, namely, principal component analysis (PCA), maximum autocorrelation factors (MAF), sample–sample 2D correlation spectroscopy (SS2D), self‐modeling mixture analysis (SMMA), multivariate curve resolution–alternating least squares (MCR‐ALS), and positive matrix factorization (PMF), were compared. SMMA was found to be the best choice to determine the number of components. MCR‐ALS and PMF provided the pure component spectra with the highest quality. MCR‐ALS was found to be superior to PMF in the estimation of Raman scores (which correspond to the concentrations) and yielded almost the same results as CLS (using the real reference spectra). Thus, the combination of Raman mapping and chemometrics could be successfully used to characterize unknown pharmaceuticals, identify their ingredients, and obtain information about their structures. This may be useful in the struggles against illegal and counterfeit products and also in the field of pharmaceutical industry when contaminants are to be identified. Copyright © 2011 John Wiley & Sons, Ltd.