A new approach to non-linear multivariate calibration in laser-induced breakdown spectroscopy analysis of silicate rocks

In this paper a new approach to quantitative Laser-Induced Breakdown Spectroscopy (LIBS) analysis of silicate rocks is presented. The method is adapted from the Franzini and Leoni algorithm, a method widely used in X-Ray Fluorescence analysis for correcting the matrix effects in the determination of the composition of geological materials. To illustrate the features of the new method proposed, nine elements were quantified in 19 geological standards by building linear univariate calibration curves, linear multivariate calibration surfaces (PLS) and using Artificial Neural Networks. The results were then compared with the predictions derived from the application of the algorithm here proposed. It was found that the Franzini and Leoni approach gives results much more precise than linear uni- and multivariate approaches, and comparable with the ones derived from the application of Artificial Neural Networks. A definite advantage of the proposed approach is the possibility of building multivariate non-linear calibration surfaces using linear optimization algorithms, a feature which makes the application of the Franzini and Leoni method in LIBS analysis much simpler (and controllable) with respect to the algorithms based on Artificial Neural Networks

Shock waves in laser-induced plasmas

The production of a plasma by a pulsed laser beam in solids, liquids or gas is often associated with the generation of a strong shock wave, which can be studied and interpreted in the framework of the theory of strong explosion. In this review, we will briefly present a theoretical interpretation of the physical mechanisms of laser-generated shock waves. After that, we will discuss how the study of the dynamics of the laser-induced shock wave can be used for obtaining useful information about the laser-target interaction (for example, the energy delivered by the laser on the target material) or on the physical properties of the target itself (hardness). Finally, we will focus the discussion on how the laser-induced shock wave can be exploited in analytical applications of Laser-Induced Plasmas as, for example, in Double-Pulse Laser-Induced Breakdown Spectroscopy experiments

Improvement of the performances of a commercial hand-held laser-induced breakdown spectroscopy instrument for steel analysis using multiple artificial neural networks.

In this article, we present a study on the optimization of the analytical performance of a commercial hand-held laser-induced breakdown spectroscopy instrument for steel analysis. We show how the performances of the instrument can be substantially improved using a non-linear calibration approach based on a set of Artificial Neural Networks (ANNs), one optimized for the determination of the major elements of the alloy, and the others specialized for the analysis of minor components. Tests of the instrument on steel samples used for instrument internal calibration demonstrate a comparable accuracy with the results of the ANNs, while the latter are considerably more accurate when unknown samples, not used for calibration/training, are tested

Green-synthetized silver nanoparticles for Nanoparticle-Enhanced Laser Induced Breakdown Spectroscopy (NELIBS) using a mobile instrument

When compared to other analytical techniques, LIBS shows relatively low precision and, generally, high Limits of Detection (LODs). Until recently, the attempts in improving the LIBS performances have been based on the use of more stable/powerful lasers, high sensitivity detectors or controlled environmental parameters. This can hinder the competitiveness of LIBS by increasing the instrumental setup cost and the difficulty of operation. Sample treatment has proved to be a viable and simple way to increase the LIBS signal; in particular, the Nanoparticle-Enhanced Laser Induced Breakdown Spectroscopy (NELIBS) methodology uses a deposition of metal nanoparticles on the sample to greatly increase the emission of the LIBS plasma. In this work, we used a simple, fast, â\u80\u9cgreenâ\u80\u9d and low-cost method to synthetize silver nanoparticles by using coffee extract as reducing agents for a silver nitrate solution. This allowed us to obtain nanoparticles of about 25 nm in diameter. We then explored the application of such nanoparticles to the NELIBS analysis of metallic samples with a mobile LIBS instrument. By adjusting the laser parameters and optimizing the sample preparation procedure, we obtained a NELIBS signal that is 4 times the LIBS one. This showed the potential of green-synthetized nanoparticle for NELIBS applications and suggests the possibility of an in-situ application of the technique

Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review

In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings

Determination of Ash Content of coal by Laser-Induced Breakdown Spectroscopy

In this work, we report the results on the application of Laser-Induced Breakdown Spectroscopy (LIBS) to the analysis of coal, for the determination of its Ash Content. This parameter is critical for an efficient use of coal to produce electrical energy in power plants. The results obtained are compared with the ones obtained through conventional chemical laboratory analysis. The study here presented, although performed in the Laboratory, was set up trying to reproduce the real industrial conditions, with the purpose of easing the transfer of the results obtained to the on-line monitoring of coal quality at the power plant

Synthesis and Antiproliferative Activity of Nitric Oxide-Donor Largazole Prodrugs

The marine natural product Largazole is the most potent Class I HDAC inhibitor identified to date. Since its discovery, many research groups have been attracted by the structural complexity and the peculiar anticancer activity, due to its capability to discriminate between tumor cells and normal cells. Herein, we discuss the synthesis and the in vitro biological profile of hybrid analogues of Largazole, as dual HDAC inhibitor and nitric oxide (NO) donors, potentially useful as anticancer agents. In particular, the metabolic stability of the modified thioester moiety of Largazole, bearing the NO-donor function/s, the in vitro release of NO, and the antiproliferative activity in tumor cell lines are presented