More than one dynamic crossover in protein hydration water

Studies of liquid water in its supercooled region have led to many insights into the structure and behavior of water. While bulk water freezes at its homogeneous nucleation temperature of approximately 235 K, for protein hydration water, the binding of water molecules to the protein avoids crystallization. Here we study the dynamics of the hydrogen bond (HB) network of a percolating layer of water molecules, comparing measurements of a hydrated globular protein with the results of a coarse-grained model that has been shown to successfully reproduce the properties of hydration water. With dielectric spectroscopy we measure the temperature dependence of the relaxation time of protons charge fluctuations. These fluctuations are associated to the dynamics of the HB network of water molecules adsorbed on the protein surface. With Monte Carlo (MC) simulations and mean--field (MF) calculations we study the dynamics and thermodynamics of the model. In both experimental and model analyses we find two dynamic crossovers: (i) one at about 252 K, and (ii) one at about 181 K. The agreement of the experiments with the model allows us to relate the two crossovers to the presence of two specific heat maxima at ambient pressure. The first is due to fluctuations in the HB formation, and the second, at lower temperature, is due to the cooperative reordering of the HB network

Comparison of fully non-stationary artificial accelerogram generation methods in reproducing seismicity at a given site

Seismic input modelling is a crucial step when Non-Linear Time-History Analyses (NLTHAs) are performed, the seismic response of structures being highly responsive to the input employed. When natural accelerograms able to represent local seismicity are not available, the use of generated accelerograms is an efficient solution for input modelling. The aim of the present paper is to compare four methods for generating fully non-stationary artificial accelerograms on the basis of a target spectrum, identified using seven recorded accelerograms registered in the neighbourhood of the construction site during a single event, assumed as target accelerograms. For each method, seven accelerograms are generated and used to carry out NLTHAs on three RC structures, having irregular mass and stiffness distributions. The generation methods are evaluated in terms of both input modelling and seismic response of three RC structures. The results point out that maximum interstorey drift ratios are well reproduced only by generation methods based on spectrum-compatible criterion, while energy contained by the target set is only simulated by methods based on records of natural signals. Moreover, none of the method here investigated is able to reproduce the hysteretic energy dissipated by the structures subjected to the target accelerograms, in terms of both total amount and cumulative trend over the duration

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

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

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

Dynamically Slow Processes in Supercooled Water Confined Between Hydrophobic Plates

We study the dynamics of water confined between hydrophobic flat surfaces at low temperature. At different pressures, we observe different behaviors that we understand in terms of the hydrogen bonds dynamics. At high pressure, the formation of the open structure of the hydrogen bond network is inhibited and the surfaces can be rapidly dehydrated by decreasing the temperature. At lower pressure the rapid ordering of the hydrogen bonds generates heterogeneities that are responsible for strong non-exponential behavior of the correlation function, but with no strong increase of the correlation time. At very low pressures, the gradual formation of the hydrogen bond network is responsible for the large increase of the correlation time and, eventually, the dynamical arrest of the system and of the dehydration process.Comment: 14 pages, 3 figure

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

The chemical-physical knowledge before the restoration: The case of "The Plague in Lucca", a masterpiece of Lorenzo Viani (1882-1936)

Background: "The Plague in Lucca", a masterpiece of the contemporary painter Lorenzo Viani, was studied by multianalytical techniques (Multiband, IR and UV fluorescence imaging, micro-Raman spectroscopy, direct exposure-mass spectrometry, gas chromatography-mass spectrometry and energy dispersive X-ray fluorescence) in view of its restoration at the Gallery of Modern and Contemporary Art (GAMC) of Palazzo delle Muse in Viareggio (Lucca, Italy). The analysis allowed to obtain a better understanding of the artistic technique of the painter and to underline critical conservation aspects. Results: At first, non-invasive techniques, such as the Multiband Imaging, Infrared Reflectometry, UV Fluorescence and X-ray Fluorescence, have been applied in order to characterize the conservation state of the painting surface and determining the more representative zones of the painting for the taking of micro-samples to be analysed in the laboratory. The destructive chemical analysis of these micro-samples, performed using mass (DEMS and GC/MS) and infrared spectroscopy (micro-Raman), permitted to reveal the nature of the organic and inorganic materials present in the painting. Conclusions: The use of different physical and chemical diagnostic techniques allowed us to obtain precious information about the palette and the technique used by Lorenzo Viani for the realization of "La Peste a Lucca". Furthermore, this approach permit to characterize paintings, to understand the nature and origin of materials used by the artist and to develop the appropriate restoration procedure