Graph clustering and portable X-Ray Fluorescence: An application for in situ, fast and preliminary classification of transport amphoras

In the last decade, numerous papers have been delivered on the potential of portable X-Ray Fluorescence (XRF) in archaeological ceramics. Additionally, new chemometric methods have been proposed to manage chemical dataset and facilitate the use of geochemical discrimination for provenance classification of ancient ceramics. In this contribute, the potential of portable Energy Dispersive X-Ray Fluorescence (ED-XRF) analysis and chemical data processing by Graph Clustering is evaluated for provenance classification of archaeological potteries, discussing possible merits and limits of the employed routine. A ceramic assemblage represented by seventy-three transport amphorae classified by typological analysis have been used as testing materials; spectra have been collected on samples simulating in situ analysis conditions (e.g. on fresh cut surfaces without any preparation) and Graph Clustering method has been applied in chemical data processing; comparison with classical Cluster Analysis (CA) and Principal Component Analysis (PCA) is also evaluated. The obtained results favor the use of Graph Clustering for a preliminary classification of ceramics, which can be chemically analyzed in easy, fast and non-destructive way. With a 75.35% of correct attribution, the study shows the suitability of portable ED-XRF in rapid screening of a large number of ceramic samples usually recovered in the framework of archaeological excavation. Misclassifications have been mostly verified for samples exhibiting a coarse-grained clay paste, suggesting that the method is particularly suitable for fine-grained ceramic materials

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

Application of double-pulse micro-LIBS 3D compositional mapping to the analysis of ceramics

We developed a new Laser-Induced Breakdown Spectroscopy (LIBS) instrument for 3D compositional mappings of archaeological objects. The system, based on the Modì double-pulse instrument, allows the reconstruction of maps with lateral resolution up to 20 microns and sub-micron depth resolution

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

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

Pottery production and trades in Tamil Nadu region : new insights from Alagankulam and Keeladi excavation sites

This research is part of a wider scientific Italian-Indo project finalised to shed lights on pottery fabrication and trade circulation in Tamil Nadu region during Early Historical Period. The recent archaeological excavations carried out in Alagankulam—a famous harbour trading with the eastern and western world—and in Keeladi—the most ancient civilization centre attested in Tamil Nadu region—provided numerous fragments of archaeological ceramics. The typological analysis enabled the identification of different pottery classes, suggesting the presence of local productions, possible imports and imitations. Studied shards included common Indian vessels, fine wares and luxury ware repertoire. The provenance identification of some of the studied typologies is still debated in the literature; for long time, the misattribution of several ceramic classes has led to wrong interpretations on the commercial connections between India and the Western and Eastern Mediterranean area. The minero-petrographic and spectroscopic investigation of several ceramic fragments from the two investigated archaeological sites enabled the systematic compositional characterization of specific ceramic classes both locally manufactured and imported. The obtained results contributed to draw short-range and long-range connections in Tamil Nadu area

A hybrid calibration-free/artificial neural networks approach to the quantitative analysis of LIBS spectra

A 'hybrid' method is proposed for the quantitative analysis of materials by LIBS, combining the precision of the calibration-free LIBS (CF-LIBS) algorithm with the quickness of artificial neural networks. The method allows the precise determination of the samples' composition even in the presence of relatively large laser fluctuations and matrix effects. To show the strength and robustness of this approach, a number of synthetic LIBS spectra of Cu-Ni binary alloys with different composition were computer-simulated, in correspondence of different plasma temperatures, electron number densities and ablated mass. The CFLIBS/ANN approach here proposed demonstrated to be capable, after appropriate training, of 'learning' the basic physical relations between the experimentally measured line intensities and the plasma parameters. Because of that the composition of the sample can be correctly determined, as in CF-LIBS measurements, but in a much shorter time

Classification studies on Etruscan archaeological copper-based alloy findings from the Necropolis of ‘Pratino’ in Tuscania

In this communication, an extensive study and its results are presented about the composition of some Etruscan copper alloy findings. The objects came from Tomb 20 of the “Pratino” necropolis in Tuscania, near Viterbo (Italy), dating back to the late Hellenistic period. The excavation and study of the site was granted to the Lorenzo de' Medici Italian International Institute (Ld’M) in 2005. Since 2011, the activity is directed by the Center for Ancient Mediterranean and Near Eastern Studies (CAMNES). The archaeological materials were classified according to their composition, determined by a portable Energy Dispersive X-Ray Fluorescence (ED-XRF) instrument

An artificial neural network approach to laser-induced breakdown spectroscopy quantitative analysis

The usual approach to laser-induced breakdown spectroscopy (LIBS) quantitative analysis is based on the use of calibration curves, suitably built using appropriate reference standards. More recently, statistical methods relying on the principles of artificial neural networks (ANN) are increasingly used. However, ANN analysis is often used as a 'black box' system and the peculiarities of the LIBS spectra are not exploited fully. An a priori exploration of the raw data contained in the LIBS spectra, carried out by a neural network to learn what are the significant areas of the spectrum to be used for a subsequent neural network delegated to the calibration, is able to throw light upon important information initially unknown, although already contained within the spectrum. This communication will demonstrate that an approach based on neural networks specially taylored for dealing with LIBS spectra would provide a viable, fast and robust method for LIBS quantitative analysis. This would allow the use of a relatively limited number of reference samples for the training of the network, with respect to the current approaches, and provide a fully automatizable approach for the analysis of a large number of samples

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