Comparison of Algorithms for Baseline Correction of LIBS Spectra for Quantifying Total Carbon in Brazilian Soils

LIBS is a promising and versatile technique for multi-element analysis that usually takes less than a minute and requires minimal sample preparation and no reagents. Despite the recent advances in elemental quantification, the LIBS still faces issues regarding the baseline produced by background radiation, which adds non-linear interference to the emission lines. In order to create a calibration model to quantify elements using LIBS spectra, the baseline has to be properly corrected. In this paper, we compared the performance of three filters to remove random noise and five methods to correct the baseline of LIBS spectra for the quantification of total carbon in soil samples. All combinations of filters and methods were tested, and their parameters were optimized to result in the best correlation between the corrected spectra and the carbon content in a training sample set. Then all combinations with the optimized parameters were compared with a separate test sample set. A combination of Savitzky-Golay filter and 4S Peak Filling method resulted in the best correction: Pearson's correlation coefficient of 0.93 with root mean square error of 0.21. The result was better than using a linear regression model with the carbon emission line 193.04 nm (correlation of 0.91 with error of 0.26). The procedure proposed here opens a new possibility to correct the baseline of LIBS spectra and to create multivariate methods based on the a given spectral range.Comment: 13 pages, 5 figure

SR-FTiR microscopy and FTIR imaging in the earth sciences

During the last decades, several books have been devoted to the application of spectroscopic methods in mineralogy. Several short courses and meetings have addressed particular aspects of spectroscopy, such as the analysis of hydrous components in minerals and Earth materials. In these books, complete treatment of the infrared theory and practical aspects of instrumentation and methods, along with an exhaustive list of references, can be found. The present chapter is intended to cover those aspects of infrared spectroscopy that have been developed in the past decade and are not included in earlier reviews such as Volume 18 of Reviews in Mineralogy. These new topics involve primarily: (1) the use of synchrotron radiation (SR), which, although not a routine method, is now rather extensively applied in infrared studies, in particular those requiring ultimate spatial and time resolution and the analysis of extremely small samples (a few tens of micrometers); (2) the development of imaging techniques also for foreseen time resolved studies of geo-mineralogical processes and environmental studies.Comment: 36 pages, 24 figures - Reviews in Mineralogy & Geochemistry - Vol. 78 (2013) in pres

Smart monitoring of aeronautical composites plates based on electromechanical impedance measurements and artificial neural networks

This paper presents a structural health monitoring (SHM) method for in situ damage detection and localization in carbon fiber reinforced plates (CFRPs). The detection is achieved using the electromechanical impedance (EMI) technique employing piezoelectric transducers as high-frequency modal sensors. Numerical simulations based on the finite element method are carried out so as to simulate more than a hundred damage scenarios. Damage metrics are then used to quantify and detect changes between the electromechanical impedance spectrum of a pristine and damaged structure. The localization process relies on artificial neural networks (ANNs) whose inputs are derived from a principal component analysis of the damage metrics. It is shown that the resulting ANN can be used as a tool to predict the in-plane position of a single damage in a laminated composite plate

Development and Application of Chemometric Methods for Modelling Metabolic Spectral Profiles

The interpretation of metabolic information is crucial to understanding the functioning of a biological system. Latent information about the metabolic state of a sample can be acquired using analytical chemistry methods, which generate spectroscopic profiles. Thus, nuclear magnetic resonance spectroscopy and mass spectrometry techniques can be employed to generate vast amounts of highly complex data on the metabolic content of biofluids and tissue, and this thesis discusses ways to process, analyse and interpret these data successfully. The evaluation of J -resolved spectroscopy in magnetic resonance profiling and the statistical techniques required to extract maximum information from the projections of these spectra are studied. In particular, data processing is evaluated, and correlation and regression methods are investigated with respect to enhanced model interpretation and biomarker identification. Additionally, it is shown that non-linearities in metabonomic data can be effectively modelled with kernel-based orthogonal partial least squares, for which an automated optimisation of the kernel parameter with nested cross-validation is implemented. The interpretation of orthogonal variation and predictive ability enabled by this approach are demonstrated in regression and classification models for applications in toxicology and parasitology. Finally, the vast amount of data generated with mass spectrometry imaging is investigated in terms of data processing, and the benefits of applying multivariate techniques to these data are illustrated, especially in terms of interpretation and visualisation using colour-coding of images. The advantages of methods such as principal component analysis, self-organising maps and manifold learning over univariate analysis are highlighted. This body of work therefore demonstrates new means of increasing the amount of biochemical information that can be obtained from a given set of samples in biological applications using spectral profiling. Various analytical and statistical methods are investigated and illustrated with applications drawn from diverse biomedical areas

Discovering the cover: molecular imaging of Populus trichocarpa leaf surface by FT-IR spectroscopy and mass spectrometry techniques

All terrestrial plants are covered by cuticle and its most outer layer is called epicuticular waxes (EWs). This layer forms an actual leaf surface, therefore is a first line of defence against any environmental stress. Despite its crucial role in plant survival, for decades leaf surface was studied without required selectivity. In the present research, the leaf surface was investigated using selective sampling methods and molecular imaging tools: (1) MALDI-TOF-MS (matrix assisted laser/desorption ionization), (2) TOF-SIMS (time-of flight secondary ion) mass spectrometry imaging, (3) FT-IR (Fourier transform infrared) as well as (4) Raman spectroscopy imaging. These tools provide molecular specificity and spatially resolved information. The results were complemented with GC-MS, SEM (scanning electron microscopy), behavioral experiments and statistical analysis. The first sequenced tree, Populus trichocarpa, along with the leaf beetle Chrysomela populi were chosen as a model system. This system represents naturally occurring interaction between a specialist herbivore and its host plant. Following aspects were investigated: (1) Characterization of structure and chemical composition of leaf surface (2) Investigation of role of EW layer in the host recognition process (3) Analysis of wound-healing processes on the leaf surface in response to insect infestation (4) Distribution of leaf surface constituents with high resolution imaging techniques. Results allow to conclude, that: (1) Higly non polar aliphatic compounds detected on the leaf surface of P. trichocarpa play protective role rather than informative (2) EW layer lack compounds that would be necessary in the host recognition process (3) EWs are involved in early stage wound-healing process by their deposition on the injury area (4) Leaf surface compounds co-aggregate and form two distribution patterns, possibly transport of EW constituents depends on their chain length