Implementation of a novel low‐noise InGaAs detector enabling rapid near‐infrared multichannel Raman spectroscopy of pigmented biological samples

Pigmented tissues are inaccessible to Raman spectroscopy using visible laser light because of the high level of laser‐induced tissue fluorescence. The fluorescence contribution to the acquired Raman signal can be reduced by using an excitation wavelength in the near infrared range around 1000 nm. This will shift the Raman spectrum above 1100 nm, which is the principal upper detection limit for silicon‐based CCD detectors. For wavelengths above 1100 nm indium gallium arsenide detectors can be used. However, InGaAs detectors have not yet demonstrated satisfactory noise level characteristics for demanding Raman applications. We have tested and implemented for the first time a novel sensitive InGaAs imaging camera with extremely low readout noise for multichannel Raman spectroscopy in the short‐wave infrared (SWIR) region. The effective readout noise of two electrons is comparable to that of high quality CCDs and two orders of magnitude lower than that of other commercially available InGaAs detector arrays. With an in‐house built Raman system we demonstrate detection of shot‐noise limited high quality Raman spectra of pigmented samples in the high wavenumber region, whereas a more traditional excitation laser wavelength (671 nm) could not generate a useful Raman signal because of high fluorescence. Our Raman instrument makes it possible to substantially decrease fluorescence background and to obtain high quality Raman spectra from pigmented biological samples in integration times well below 20 s. Copyright © 2015 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.     

Surface enhanced Raman scattering of trans‐p‐coumaric and syringic acids

The vibrational spectra of trans‐p‐coumaric acid (pCA) and syringic acid (SA) are discussed. The spectral fingerprints of the organic acids observed in the infrared and Raman spectra are assigned to fundamental vibrational wavenumbers supported by quantum chemical computations. The average surface‐enhanced Raman scattering spectra of both acids have been obtained on silver colloidal solutions and the interpretation of the spectra is presented based on complementary Raman spectra and computational results for the silver salts. Copyright © 2009 John Wiley & Sons, Ltd.     

The analysis of pH‐dependent protonated conformers of 1‐hydroxyethylidene‐1,1‐diphosphonic acid by means of FT‐Raman spectroscopy,multivariate curve resolution and DFT modelling

1‐Hydroxyethylidene‐1,1‐diphosphonic acid (HEDP) solutions in the pH range 0.98–13.00 were analysed using FT‐Raman spectroscopy and ³¹P and ²³Na NMR spectroscopy. Vibrational bands for different protonated species were observed in the Raman spectra, whereas only a single NMR signal that shifted with pH was observed for all samples over the entire pH range. No significant shift in the ²³Na NMR signal was observed, confirming that formation of Na⁺(aq) complexes did not take place; hence, no interference with the different protonated forms of HEDP occurred. Vibrational bands were assigned using density functional theory(DFT)‐calculated spectra of the most likely conformers in solution. Multivariate curve resolution was performed on the Raman spectra in the region containing the PO stretching vibrations to determine the number of protonated species formed over the entire pH range. Chemometric analysis compares very favourably with the experimental species distribution diagram which was generated using the reported log K_H values. Copyright © 2009 John Wiley & Sons, Ltd.     

Bacterial mixture identification using Raman and surface‐enhanced Raman chemical imaging

The ability of normal Raman and surface‐enhanced Raman scattering (SERS) to identify and detect bacteria has shown great success in recent studies. The addition of silver nanoparticles to bacterial samples not only results in an enhanced Raman signal, but it also suppresses the native fluorescence associated with biological material. In this report, Raman chemical imaging (RCI) was used to analyze individual bacteria and complex mixtures of spores and vegetative cells. RCI uses every pixel or a binned pixel group (BPG) of the Raman camera as an independent Raman spectrograph, allowing collection of spatially resolved Raman spectra. The advantage of this technique resides primarily in the analysis of samples in complex backgrounds without the need for physically isolating or purifying the sample. Using a chemical imaging Raman microscope, we compare normal RCI to SERS‐assisted chemical imaging of mixtures of bacteria. In both cases, we are able to differentiate single bacterium in the Raman microscope's field of view, with a 60‐fold reduction in image acquisition time and a factor of 10 increase in the signal‐to‐noise ratio for SERS chemical imaging over normal RCI. Copyright © 2010 John Wiley & Sons, Ltd.     

An intelligent background‐correction algorithm for highly fluorescent samples in Raman spectroscopy

Fluorescent background is a major problem in recoding the Raman spectra of many samples, which swamps or obscures the Raman signals. The background should be suppressed in order to perform further qualitative or quantitative analysis of the spectra. For this purpose, an intelligent background‐correction algorithm is developed, which simulates manual background‐correction procedure intelligently. It basically consists of three aspects: (1) accurate peak position detection in the Raman spectrum by continuous wavelet transform (CWT) with the Mexican Hat wavelet as the mother wavelet; (2) peak‐width estimation by signal‐to‐noise ratio (SNR) enhancing derivative calculation based on CWT but with the Haar wavelet as the mother wavelet; and (3) background fitting using penalized least squares with binary masks. This algorithm does not require any preprocessing step for transforming the spectrum into the wavelet space and can suppress the fluorescent background of Raman spectra intelligently and validly. The algorithm is implemented in R language and available as open source software ( http://code.google.com/p/baselinewavelet ). Copyright © 2009 John Wiley & Sons, Ltd.     

Raman analysis assessed by Fourier‐Transformed infrared and X‐ray fluorescence spectroscopies: a multi‐analytical approach of ancient chromolithographs from the 19th century

A set of chromolithographs from the 19th century were analysed to identify the fillers and pigments used for their elaboration. Because of the delicacy of the chromolithographs, the research involved the use of Raman, Fourier‐transform infrared and energy dispersive X‐ray fluorescence spectroscopies for a complete characterization of the works on paper without removing any microsamples. Despite the high fluorescence of the samples when analyzed by Raman spectroscopy, in this paper, we demonstrated that ink spectra can be successfully enhanced by subtracting the spectra of the supporting background paper. The results of the study showed that, apparently, the lithographer used a limited range of common inorganic pigments from the 19th century (carbon black, chrome yellow, Prussian blue, red ochre, red lead and vermilion) together with organic pigments (indigo blue, gamboge and a red organic pigment). The study also found that despite the fact that during the 19th and early 20th century the use of mixtures of several pigments was a common practice, unusual admixtures were used for the preparation of some colours of the studied chromolithographs. Copyright © 2011 John Wiley & Sons, Ltd.     

A stable ‘sandwich’ system of Surface‐Enhanced Resonance Raman Scattering for the analysis of β‐carotenes in a photosynthetic pigment‐protein complex

In plants, Photosystem I (PSI) is composed of a core complex and a membrane‐associated antenna complex light‐harvesting complex I that captures light and funnels its energy to the core complex. To obtain Raman structural information on β‐carotenes embedded in the PSI core complex, a ‘sandwich’ system of roughened silver slice: target protein complexes: single silver nanoparticles was fabricated for Surface‐Enhanced Resonance Raman Scattering (SERRS) measurements. This study provided a method to overcome spectral irreproducibility, which is the main drawback of Surface‐Enhanced Raman Scattering/SERRS‐based studies. The Raman spectra of β‐carotenes embedded in the PSI core complex can be obtained at very low sample concentrations (1–5 µg Chl/ml) and high signal/noise ratios. The β‐carotenes in the spinach PSI core complex were predominantly all‐trans configuration. The membrane protein‐mediated adsorption of silver nanoparticles induced the uniform distribution of a large number of single nanoparticles, which contributed to achieving highly reproducible SERRS spectra. This study is the first to apply single silver nanoparticle‐based SERRS analysis in membrane proteins. Copyright © 2013 John Wiley & Sons, Ltd.     

DFT simulations and vibrational analysis of FTIR and FT‐Raman spectra of 2‐amino‐4,6‐dihydroxypyrimidine

This work deals with the vibrational spectroscopy of 2‐amino‐4,6‐dihydroxy pyrimidine (ADHP) by means of quantum chemical calculations. The mid‐ and far FTIR and FT‐Raman spectra were measured in the condensed state. The fundamental vibrational wavenumbers and intensity of vibrational bands were evaluated using density functional theory (DFT) with the standard B3LYP/6‐311 + G** methods and basis set combinations, and were scaled using various scale factors, which yielded good agreement between the observed and calculated wavenumbers. The vibrational spectra were interpreted with the aid of normal coordinate analysis based on the scaled density functional force field. The results of the calculations were applied to simulate the infrared and Raman spectra of the title compound, which showed excellent agreement with the observed spectra. Copyright © 2008 John Wiley & Sons, Ltd.     

Fourier‐transform surface‐enhanced Raman spectroscopy (FT‐SERS) applied to the identification of natural dyes in textile fibers: an extractionless approach to the analysis

In the present study, an application of a silver colloid substrate in order to obtain Fourier‐transform surface‐enhanced Raman (FT‐SER) spectra of natural historical dyes is presented. In detail, we collected a spectral database from solutions of pure dyes and then we carried out extractionless both hydrolysis and non‐hydrolysis FT‐SERS analyses on wool fibers previously dyed in our laboratory and on ancient textiles. The term ‘extractionless’ refers to a method of SERS analysis applied directly on the fiber, thus avoiding the extraction of dyes from textile samples. The combination of a low‐energy source of radiation, as in the FT‐Raman technique, with SER spectroscopy can bring the important advantage of reducing the fluorescence typical of ancient samples and organic dyes. In some historical textile samples, for which SER spectra by use of visible excitation could not be obtained, the FT‐SER spectrum of an iron‐gall dye was recorded without hydrolysis, while, with an HF hydrolysis pre‐treatment on ancient fibers, madder, lac dye and brazilwood were clearly recognized. Copyright © 2014 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.     

Surface‐enhanced Raman spectroscopy for trace‐level detection of explosives

The detection of explosives and their associated compounds for security screening is an active area of research and a wide variety of detection methods are involved in this very challenging area. Surface‐enhanced Raman scattering (SERS) spectroscopy is one of the most sensitive tools for the detection of molecules adsorbed on nano‐scale roughened metal surface. Moreover, SERS combines high sensitivity with the observation of vibrational spectra of species, giving complete information on the molecular structure of material under study. In this paper, SERS was applied to the detection of very small quantities of explosives adsorbed on industrially made substrates. The spectra were acquired with a compact Raman spectrometer. Usually, a high signal‐to‐noise (S/N) spectrum, suitable for identification of explosive molecules down to few hundreds of picograms, was achieved within 30 s. Our measurements suggest that it is possible to exploit SERS using a practical detection instrument for routine analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

Energy value determinations of industrialized foods: the potential of using X‐ray spectroscopy and partial least squares

This work reports the use of multivariate calibration models to determine energy values (EV) of industrialized dried vegetable products prepared for human consumption. These methods use energy dispersive X‐ray fluorescence spectra allied to chemometrics of the respective samples to substitute conventional EV determinations that are subject to several laborious steps. The samples are grouped in accordance with their principal raw material (corn, wheat, soy, milk and cassava). The chemometric tools applied reveal that the X‐ray scattering spectrum region furnishes the main contribution to the calibration models, where the presence of organic compounds is manifested through small variations in X‐ray scattering effects. These results are expected because EV values are based on the organic contents. The EV determination is fast, does not generate residuals and does not involve toxic reagents. The good results of the validation process (deviations < 14%) indicate that this is an alternative to conventional analytical methods and is very attractive for routine analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

动态表面增强拉曼光谱在敌瘟磷快速定量分析中的应用

动态表面增强拉曼光谱是在干态与湿态表面增强拉曼光谱(SERS)检测的基础上发展而来的,不仅具有极好的信号增强,还具有良好的重复性与稳定性。提出了一种基于动态SERS与多元分析方法的敌瘟磷快速定量分析方法。实验中,首先测量100,50,10,5,1,0.5和0.1 mg·L-1敌瘟磷动态SERS谱图,并使用多项式校正方法去除光谱基线漂移。然后,处理后的全范围(600~1 800 cm-1)与特征范围(674~713,890~1 195,1 341~1 399和1 549~1 612 cm-1)光谱分别利用支持向量机回归(SVR)构建定量模型,实现对敌瘟磷的定量分析。同时,实验还评估了主成分分析(PCA)对定量分析结果的影响。实验结果表明特征范围光谱所建立的模型预测误差较小,而数据经过PCA处理后预测误差得到进一步下降。最优回归模型是由特征范围光谱经PCA处理后所构建的模型(RMSECV=0.065 7 mg·L-1),模型能够准确地预测敌瘟磷溶液浓度。为了测试实际检测中的效果,该方法被用来对苹果表面的敌瘟磷残留进行检测,并通过气相色谱法进行验证。结果表明该方法对于同一样本多次检测值波动较小,且检测均值与气相色谱检测值相差较小,相对误差最大仅为5.13%。此外,动态SERS检测可在2 min内完成,且后续数据处理也可在数秒内完成,同时整个过程的试剂消耗仅在2 μL左右。因此,所提出的方法在敌瘟磷快速准确检测具有极大优势。     

Multivariate analysis of combined Raman and fibre‐optic reflectance spectra for the identification of binder materials in simulated medieval paints

The non‐invasive identification of paint materials used in works of art is essential, both for preserving and restoring them, and also for understanding and verifying the history surrounding their creation. As such, the development of suitable non‐invasive techniques has received much interest in recent years. We have investigated the use of Fourier transform (FT)‐Raman spectroscopy and fibre‐optic reflectance spectroscopy (FORS), together with multivariate principal‐component analysis (PCA) techniques, in order to identify the pigment and binding materials used in made‐up samples representative of real artwork. We demonstrate that both types of spectroscopy provide complementary information which can be used to identify the pigments and binders in paint samples. We show that PCA with FT‐Raman spectra can be used to assist in the identification of oil‐based binders, and that the additional data provided by FORS spectra enables PCA on combined spectra to identify more complex proteinaceious and polysaccharide‐based binding media. The results presented here demonstrate that multivariate analyses of lead‐based paints, using data measured by FT‐Raman and FORS in conjunction, have much potential for identifying individual pigments and binders in paint samples. This provides a path towards computer‐assisted characterisation of paint materials on artwork. Copyright © 2013 John Wiley & Sons, Ltd.     

Improved blind‐source separation for spectra

A new method is proposed that improves the performance of independent component analysis (ICA) algorithms for separating overlapping spectra under certain circumstances. The method is designed for Raman spectra in particular, although it should be applicable to spectra with similar line shapes, such as nuclear magnetic resonance. In the zero‐noise case, conventional ICA fails to separate synthetic Raman spectra completely; by maximising smoothness, as opposed to other more traditional measures of statistical independence, better performance can be achieved. The new method is tested against artificial and real Raman spectra, and demonstrates improved performance for each. The algorithm is fully automated, requiring no user input or judgement in order to separate the spectra. Copyright © 2011 John Wiley & Sons, Ltd.     

Label‐free optical detection of type II diabetes based on surface‐enhanced Raman spectroscopy and multivariate analysis

Surface‐enhanced Raman scattering (SERS) spectroscopy was first employed to detect oxyhemoglobin (OxyHb, the common type of hemoglobin) variation in type II diabetic development without using exogenous reagents. Using silver nanoparticles as SERS‐active substrate, high‐quality SERS spectra are obtained from blood OxyHb samples of 49 diabetic patients and 40 healthy volunteers. Tentative assignment of the observed SERS bands indicates specific structural changes of OxyHb molecule in diabetes, including heme transformation and globin variation. Furthermore, partial least squares and principal component analysis combined with linear discriminate analysis diagnostic algorithms are employed to analyze and classify the SERS spectra acquired from diabetic and healthy OxyHb, yielding the diagnostic accuracies of 90.0% and 95.5%, respectively. This exploratory work suggests that the silver nanoparticles‐based OxyHb SERS method in combination with multivariate statistical analysis has great potential for the label‐free detection of type II diabetes. Copyright © 2014 John Wiley & Sons, Ltd.     

A comparison of noise models in a hybrid reference spectrum and principal components analysis algorithm for Raman spectroscopy

Raman spectroscopy exploits the Raman scattering effect to analyze chemical compounds with the use of laser light. Raman spectra are most commonly analyzed using the ordinary least squares (LS) method. However, LS is known to be sensitive to variability in the spectra of the analyte and background materials. In a previous paper, we addressed this problem by proposing a novel algorithm that models expected variations in the analyte as well as background signals. The method was called the hybrid LS and principal component analysis (HLP) algorithm and used an unweighted Gaussian distribution to model the noise in the measured spectra. In this paper, we show that the noise in fact follows a Poisson distribution and improve the noise model of our hybrid algorithm accordingly. We also approximate the Poisson noise model by a weighted Gaussian noise model, which enables the use of a more efficient solver algorithm. To reflect the generalization of the noise model, we from hereon call the method the hybrid reference spectrum and principal components analysis (HRP) algorithm. We compare the performance of LS and HRP with the unweighted Gaussian (HRP‐G), Poisson (HRP‐P), and weighted Gaussian (HRP‐WG) noise models. Our experiments use both simulated data and experimental data acquired from a serial dilution of Raman‐enhanced gold‐silica nanoparticles placed on an excised pig colon. When the only signal variability was zero‐mean random noise (as examined using simulated data), HRP‐P consistently outperformed HRP‐G and HRP‐WG, with the latter coming in as a close second. Note that in this scenario, LS and HRP‐G were equivalent. In the presence of random noise as well as variations in the mean component spectra, the three HRP algorithms significantly outperformed LS, but performed similarly among themselves. This indicates that, in the presence of significant variations in the mean component spectra, modeling such variations is more important than optimizing the noise model. It also suggests that for real data, HRP‐WG provides a desirable trade‐off between noise model accuracy and computational speed. Copyright © 2013 John Wiley & Sons, Ltd.     

Density functional and experimental studies on the FT‐IR and FT‐Raman spectra and structure of benzoic acid and 3,5‐dichloro salicylic acid

FT‐IR and FT‐Raman spectra of benzoic acid (BA) and 3,5‐dichloro salicylic acid (SA) have been recorded in the regions of 4000–400 and 4000–50 cm⁻¹ respectively. The spectra were interpreted with the aid of normal coordinate analysis following the full structure optimizations and force field calculations based on density functional theory (DFT) using standard B3LYP6‐31G** method and basis set combinations. The DFT force field transformed to natural internal coordinates was corrected by a well‐established set of scale factors that were found to be transferable to the title compounds. The infrared and Raman spectra were also predicted from the calculated intensities. Comparison of the simulated spectra with the experimental spectra provides important information about the ability of the computational method to describe the vibrational modes. Copyright © 2008 John Wiley & Sons, Ltd.     

Poly(vinylpyrrolidone)‐stabilized silver nanoparticles for strained‐silicon surface enhanced Raman spectroscopy

Poly(vinylpyrrolidone)‐stabilized silver nanoparticles deposited onto strained‐silicon layers grown on graded Si_1−xGe_x virtual substrates are utilized for selective amplification of the Si–Si vibration mode of strained silicon via surface‐enhanced Raman scattering spectroscopy. This solution‐based technique allows rapid, highly sensitive and accurate characterization of strained silicon whose Raman signal would usually be overshadowed by the underlying bulk SiGe Raman spectra. The analysis was performed on strained silicon samples of thickness 9, 17.5 and 42 nm using a 488 nm Ar⁺ micro‐Raman excitation source. The quantitative determination of strained‐silicon enhancement factors was also made. Copyright © 2011 John Wiley & Sons, Ltd.