110 research outputs found
Aerosol analysis by micro laser-induced breakdown spectroscopy: A new protocol for particulate matter characterization in filters
Atmospheric aerosols (particulate matter – PM) affect the air quality and climate, even in remote areas, such as the Antarctic Region. Current techniques for continuous PM monitoring are usually complex, costly, time consuming and do not provide real-time measurements. In this work, based on micro laser-induced breakdown spectroscopy (LIBS), an innovative method with an optical design and multi-elemental scanning imaging, is presented to characterize PM collected in filters from Antarctica. After following a simple protocol and under atmospheric pressure, the new approach allows to obtain a global visualization of the elemental PM composition of the filters with a minimum sample destruction and preparation. For the first time, we were able to map the localization of pollutants in filters at high spatial resolution and speed. This recent method offers a new insight on the characterization of PM, particularly in isolated areas, where no complex equipment and real time measurements are demanded
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Nanoparticle Mediated Tumor Vascular Disruption: A Novel Strategy in Radiation Therapy
More than 50% of all cancer patients receive radiation therapy. The clinical delivery of curative radiation dose is strictly restricted by the proximal healthy tissues. We propose a dual-targeting strategy using vessel-targeted-radiosensitizing gold nanoparticles and conformal-image guided radiation therapy to specifically amplify damage in the tumor neoendothelium. The resulting tumor vascular disruption substantially improved the therapeutic outcome and subsidized the radiation/nanoparticle toxicity, extending its utility to intransigent or nonresectable tumors that barely respond to standard therapies
Cavités de haute finesse pour la spectroscopie d'absorption haute sensibilité et haute précision : Application à l'étude de molécules d'intérêt atmosphérique.
High finesse cavities are used to measure very weak absorption features. Two different methodologies are investigated and applied to the study of molecules with atmospheric interest.First, Continuous Wave - Cavity Ring Down Spectroscopy (CW-CRDS) is used to study the atmospheric spectra of water vapour in the near infrared range. These measurements are performed for temperature and pressure of atmospheric relevance for DIAL applications (Differential Absorption Lidar). This study, financed by the European Space Agency (ESA), goes with the WALES mission (Water Vapour Lidar Experiment in Space). The experimental setup was conceived in order to control pressure, temperature and relative humidity conditions. A particular attention is done to characterize and describe the spectrometer.Then, measurements of red Oxygen B band are performed to demonstrate the huge performance of Optical Feedback Cavity Enhanced Absorption Spectroscopy (OF-CEAS). The desired optical feedback is obtained by light injection into the high finesse cavity through a glass plate placed inside the cavity and closed to the Brewster angle. We show a measurement dynamical range of 5 orders of magnitude (1e-5 to 1e-10 /cm) and a sensitivity of 1e-10 /cm/Hz^(1/2). Also, sampling absorption spectra by the super linear cavity frequency comb allows very precise frequency measurements. This is demonstrated by the determination of Oxygen pressure shifts with an absolute accuracy of around 5*1e-5 cm^(-1)/atm. To our knowledge, we provide the highest accuracy ever reported for this spectroscopic parameter.La haute sensibilité permise par l'emploi des cavités optiques est exploitée pour caractériser la signature spectrale de molécules d'intérêt atmosphérique. Deux méthodologies différentes sont abordées.Tout d'abord, la technique CW-CRDS (Continuous Wave – Cavity Ring Down Spectroscopie) est utilisée pour étudier l'évolution avec la pression et la température des spectres atmosphériques de la vapeur d'eau dans le proche infrarouge. Cette étude, destinée à calibrer des mesures d'absorption différentielle par Lidar, entre dans le cadre de la mission WALES (Water Vapour Lidar Experiment in Space) proposée par l'Agence Spatiale Européenne. Une attention particulière est portée pour décrire et caractériser le système expérimental.Ensuite, la technique OF-CEAS (Optical Feedback Cavity Enhanced Absorption Spectroscopy) et ses performances pour la spectroscopie sont mises en évidence avec l'étude de la bande B de l'oxygène dans le rouge. Cette technique repose sur un schéma d'injection avec rétroaction optique (de la cavité vers le laser) qui permet d'augmenter la cohérence de son émission pour mesurer les maxima de transmission des modes même avec des cavités de haute finesse. Une configuration nouvelle permettant ces effets est proposée (la cavité Brewster). Une gamme dynamique sur la mesure d'absorption d'environ cinq ordres de grandeurs est démontrée (1e-5 à 1e-10 /cm) ainsi qu'une sensibilité < 1e-10 /cm/Hz^(1/2). Un schéma d'acquisition mode par mode est employé et permet d'exploiter la linéarité du peigne de mode pour atteindre des hautes précisions sur la fréquence. La pertinence de cette approche est mise en évidence par la mesure de « pressure shifts » de l'oxygène obtenus avec une précision absolue record inférieure à 5*1e-5 cm^(-1)/atm
Cavités de haute finesse pour la spectroscopie d'absorption haute sensibilité et haute précision (application à l'étude de molécules d'intérêt atmosphérique)
La haute sensibilité permise par l'emploi des cavités optiques est exploitée pour caractériser la signature de molécules d'intérêt atmosphérique. Deux méthodologies sont abordées. Tout d'abord, la technique CW-CRDS est utilisée pour étudier l'évolution avec la pression et la température des spectres atmosphériques de la vapeur d'eau dans le proche infrarouge. Cette étude, destinée à calibrer des mesures par Lidar, entre dans le cadre de la mission WALES proposée par l'Agence Spatiale Européenne. Ensuite, la technique OF-CEAS et ses performances pour la spectroscopie sont mises en évidence avec la bande B de l'oxygène dans le rouge. Cette technique repose sur un schéma d'injection avec rétroaction optique qui permet d'augmenter la cohérence de l'émission laser et mesurer les maxima de transmission des modes. La linéarité du peigne de mode de la cavité est exploitée grâce à une acquisition mode par mode qui permet la mesure de "pressure shifts" de l'oxygène avec une précision recordLYON1-BU.Sciences (692662101) / SudocSudocFranceF
Saturated signals in spectroscopic imaging: why and how should we deal with this regularly observed phenomenon?
International audienceWe have all been confronted one day by saturated signals observed on acquired spectra, whatever the technique considered. A saturation, also known as clipping in signal processing, is a form of distortion that limits a signal once it exceeds a threshold. As a consequence, clipped or saturated bands with their characteristic plateau present numerical values that do not correspond to the analytical reality of the analyzed sample. Of course, analysts know that they cannot consider these erroneous values and therefore reconsider either sample preparation or instrument settings. Unfortunately, there are many experiments today (and this is the case in spectroscopic imaging) for which we will not be able to fight against the saturation effect that will undeniably be observed on the acquired spectra. The aim of this article is first to show why it is important to correct these saturation effects at the risk of having a biased view of the sample and more specifically in the context of multivariate data analysis. In a second step, we will look at strategies for managing saturated bands. An original concept will then be presented by considering saturated values as missing ones. A statistical imputation strategy will then be implemented in order to recover the information lost during the measurement
Statistical comparison of predictive models for quantitative analysis and classification in the framework of LIBS spectroscopy: A tutorial
Laser-Induced Breakdown Spectroscopy (LIBS) is a widely accepted technique used for both classification and quantification purposes considering complex and heterogeous samples. Based on a set of training spectra acquired from diverse and representative samples within a specific application domain, it becomes possible to apply various data processing techniques and modeling methods to construct the predictive model in question. Naturally the complexity of both the laser-matter and the laser-plasma interactions and the heterogeneity of natural samples often requires the development of various predictive models, which are then compared based on figures of merit such as the RMSEP (Root Mean Square Error of Prediction) value for quantification or the classification rate for qualitative analysis. Our ultimate goal is, of course, to select the model that appears to be the most accurate, which ultimately boils down to searching for the lowest RMSEP value or the highest classification rate. This is precisely where the whole problem lies because even if we observe a different level of error for two models, for example, this difference is not necessarily statistically significant. In such a case, we are therefore not allowed to say that the lower error indicates the best predictive model to consider. The purpose of this article is to provide a tutorial on introducing a statistical model comparison procedure, whether they are quantitative or qualitative. Two LIBS data sets have been used to illustrate the principles of the proposed method.Méthode pour la datation des mortiers de chaux archéologiques : caractérisation, extraction, datation, validationDiagnostique médical par intelligence artificielle appliquée à la microscopie LIBS élémentair
Should we prefer inverse models in quantitative LIBS analysis?
International audienceSince the 2000s, the analytical potential of laser-induced breakdown spectroscopy (LIBS) has been growing steadily. This is explained by the many advantages it provides such as its sensitivity, its speed of acquisition, but also the possibility of analyzing most samples as they are without preparation. Like many spectroscopies in the framework of quantitative analysis, LIBS uses the concept of indirect measurement to estimate the concentration of an element of interest in a given matrix. Thus, in the simplest case of univariate calibration, the emission signal at a particular wavelength is used as an input of a simple linear regression to obtain the associated concentration. This regression is one of the oldest statistical tools that can be used to make the link between two variables. On the basis of the calibration samples, the LIBS community is used to construct the function , such as emission signal = (concentration). With this so-called direct model, the prediction of the concentration of an unknown sample is then obtained by calculating (emission signal). This habit may be very surprising because many spectroscopies nowadays use the so-called inverse model. Thus, in this case, another function is calculated from the same data set, such as concentration = (emission signal). In this specific case, the function can be used directly to predict the concentration of a new sample. At first glance, we could say that this is not very important because it is the same as reversing the axis of abscissa and ordinate in a two-dimensional graph. In this paper, we will show that this choice is not insignificant because it may lead to statistical differences. Through the study of simulations and real cases, we will demonstrate that a difference in the predictive ability is observed between the direct and inverse regression in the framework of LIBS quantitative analysis
Diagnosis and correction methods for spectral interference in the framework of LIBS imaging
International audienceLaser-Induced Breakdown Spectroscopy (LIBS) has become a powerful imaging technique for elemental characterization in analytical chemistry due to its advantages over other techniques. Major, minor, and trace elements are detected with high measurement dynamic, a low limit of detection and a high acquisition rate, allowing for the quick analysis of large sample surfaces. Today, chemometric tools are commonly used to ensure the most comprehensive and unbiased exploration of such spectroscopic data. However, the integration of the signal from a wavelength assumed to be specific to the element of interest remains the basic tool for generating a chemical distribution map from a hyperspectral dataset. This classical approach is based on a strong assumption, the specificity of the chemical information on the spectral domain being considered. Any spectral interference inevitably result in the generation of a biased distribution image. In this publication, we demonstrate how Principal Component Analysis (PCA) can diagnose the potential presence of a spectral interference and how Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) can ultimately correct it if necessary using a LIBS imaging dataset obtained from the analysis of a complex rock sample. The proposed approach combines the simplicity and effectiveness of the integration method with the diagnostic and correction capabilities of chemometric tools, providing a comprehensive solution for spectral interference in LIBS imaging
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