The European Physical Journal Plus最新文献

Quantum sensing is a rapidly growing branch of research within the area of quantum science and technology offering key resources, beyond classical ones, with potential for commercialization of novel (quantum) sensors. The exploitation of quantum resources offered by photons can boost the performance of quantum sensors for innovative and challenging applications. In this paper, we build on the idea that quantum ghost spectroscopy (QGS), i.e. the counterpart in the frequency domain of quantum ghost imaging (QGI), can target specific applications in the detection of possible threats. This is implemented by exploiting the opportunities offered by quantum optics, i.e. the generation of photon pairs characterized by spectral correlations. We will discuss our main results obtained with pure QGS experiments showing that it is possible to assess the presence of a target dealing with a low resources measurement. The time-frequency domain reveals a huge potential for several applications, and frequency correlations represent a versatile tool that can be exploited to enable the spectral analysis of objects where a direct measurement would not be feasible (e.g. due to security). The use of non-degenerate sources of correlated photons allowed to reveal spectral features in the near-infrared wavelengths employing the usual detectors for the visible region, showing the effectiveness of this technique.

‘The Saint Vincent panels’ are produced by the painter Nuno Gonçalves, and it is a fifteenth century polyptych consisting of six panels. The uniqueness of the work, together with the documentation scarcity about Nuno Gonçalves, highlights the importance of the research of characterizing the colour palette. Raman spectroscopy, both in situ and laboratory instrumentation, was used for this. The mobile Raman spectroscopy campaign is part of the multidisciplinary research project ‘Study, Conservation and Restoration of Saint Vincent Panels’. A mobile EZRaman-I dual Raman analyser (785 and 532 nm) was used during the opening hours of the museum to investigate the panels and their pigments. The polyptych was heavily varnished and as such, the 785 nm laser was preferred for the characterization. It proved to be efficient in characterizing most of the pigments: vermilion, lead tin yellow type I, lazurite, carbon black, gypsum, lead white and calcite were identified. Intervention areas were characterized by the presence of titanium dioxide. Only for a few colours (blue, pink/purple and green), identification with the 785 nm laser was ambiguous and additional characterization with the 532 nm laser was hampered by the strong fluorescing varnish. As a result, micro-samples of these regions were collected for further analysis with benchtop micro-Raman instrumentation. Next to the confirmation of the in situ results, azurite and copper resinate were identified. As such, the combination of both approaches was successful in unravelling the colour palette of the Saint Vincent panels.

Graphical Abstract

Energy crisis and greenhouse effects are reaching alarming levels, the development of active materials that are both environment friendly and economically viable is essential for energy storing technologies. Currently, supercapacitors (SC_s) are a best type of energy storage devices that attained significant attention from scientists. The fabrication of composites using transition metal with chalcogenides possessed high specific capacitance, structural integrity, maximum energy efficiency, low cost, higher power density and energy density. The hydrothermal route was utilized to developed niobium telluride (NbTe₂) and silver-doped niobium telluride (Ag-NbTe₂). The Ag-NbTe₂ nanoflakes were examined through scanning electron microscopy (SEM) to identify structural morphology of NbTe₂ nanoparticles incorporated inside transition metal (Ag) which demonstrated the nanoflakes morphology. The increased surface area of Ag-NbTe₂ was confirmed through the BET as computed value of pristine NbTe₂ was 21 cm² g⁻¹ and with silver doped (Ag-NbTe₂) was 51 cm² g⁻¹. The examination on energy storing devices by using 3 M KOH electrolyte to conduct electrochemical impedance spectroscopy (EIS), galvanic charge–discharge and cyclic voltammetry experiments. Moreover, the fabricated material Ag-NbTe₂ nanoflakes displayed exceptional charge–discharge cycling characteristics, with specific capacitance (C_s) 1774 F g⁻¹ at current density (j_d) 1 A g⁻¹. By analyzing the EIS graph successfully identified the solution resistance (R_s) as 2.34 Ω with charge transfer resistance (R_ct) as 0.77 Ω. Further, results of our research provide a cost-efficient, highly effective and easily expandable approach for producing nanocomposites by hydrothermal techniques. This fabricated material exhibited enhanced electrochemical performance, making them highly suitable for utilization in supercapacitors (SC_s) and other energy storage devices.

With the assistance of molecular dynamics simulations and non-local theories of continuum mechanics, we have captured the size-dependent effects of nanostructures. Continuum models are commonly utilized to study structures' mechanical properties at macro-scales. However, these models are incapable of being employed to determine the mechanical characterization of nanomaterials. In contrast, atomistic simulations, such as molecular dynamics models, are widely accepted for studying the behavior of materials in nano-scaled systems. However, these atomic simulation techniques suffer from high computational costs. In this study, we propose that hybrid atomistic-continuum models are suitable for studying these systems' mechanical and vibrational properties. Hence, free vibrations of FCC metals nanobeams, aluminum, and silver are investigated through non-local elasticity models (Eringen differential and stress-driven models), and strain gradient models are formulated for Euler–Bernoulli and Timoshenko nanobeam. For the first time, atomistic simulation results are utilized in conjunction with the Bees algorithm optimization technique to calibrate the size parameter values for the non-classical continuum models. In this manner, the effects of size parameters on the vibration behavior of metallic nanobeams are examined. Our simulations revealed that aluminum metallic nanobeams exhibit softening and stiffening behaviors, while silver nanobeams show only softening behavior, which is one of the most significant findings of our research. Moreover, we have demonstrated that calibrated continuum models are capable of accurately predicting the mechanical vibrational behavior of nanobeams with only minimal errors.

Based on the necessity of understanding the dynamics behind the darkening and degradation phenomena of cobalt blue oil paints observed in Edvard Munch’s paintings, ten industrially produced cobalt blue oil paint tubes from the artist’s studio were investigated. The synergic use of µ-Raman, ATR-FTIR, GC–MS and SEM–EDS techniques led to an overall characterization of the paints. The goal of this research was to further investigate the composition of these industrially produced cobalt blue oil paints and examine their implications in the observed deterioration and darkening phenomena in the blue painted areas in Munch’s artworks. Pigments, binding media admixtures and additives present in the manufactured formulations were assessed. The analysed paints were characterized by complex mixtures, featuring the presence of non-drying or semi-drying oils, metal soaps and preservatives. Additionally, extenders, among others clay minerals and white pigments, and adulteration with other blue pigments were identified. The extensive detection of metal soaps in the analysed paint tubes, together with the specific deterioration patterns observed in Munch’s paintings investigated, led to some preliminary considerations on the role of these components based on the reported literature.

Based on transverse-field Ising model, we investigated the flipping phenomenon of a decorated nanoisland system with spin-1/2 using the decoupling approximation of Fermi-type Green’s function. The results reveal that, under the conditions of relatively weak surface exchange interaction J_S/J and transverse-field Ω/J, the system exhibits spin reversal during the heating process. Decorative exchange interaction J_D/J only affects the details of the phase transition properties, and the temperature at which spin reversal occurs can still be qualitatively analyzed based on the mean-field phase diagram.

The particle dynamics and the electric Penrose process for the five-dimensional weakly charged Schwarzschild black hole are studied. Firstly, the horizon structure and the effective potential for the test particle are explored. The radial profile of the effective potential is plotted for different values of the BH charge. Then, we studied energy efficiency using the conservation laws for energy, angular momentum, and charge of particles. The appropriate plots were obtained and compared with the results for the four-dimensional Schwarzschild BH. Moreover, we obtained the constraints on mass and charge of black hole to accelerate protons of different energies (1-(10^{9}) GeV). Finally, collisions of electrically charged particles near the horizon of the five-dimensional Schwarzschild BH are studied. We demonstrated the radial dependence of the center-of-mass energy for different values of the angular momentum and charge of the particles together with the BH charge.

This paper investigates the propagation characteristics of SH-type waves originating from a point source situated at the interface of a unique structure comprising a functionally graded viscoelastic (FGV) layer of finite depth overlying a functionally graded monoclinic (FGM) half-space. The upper viscoelastic layer exhibits a hyperbolic gradient property in its material constants, while an exponential gradient property characterizes the lower monoclinic half-space. Employing the Fourier transform and Green’s function method to account for surface and interfacial boundary conditions, a dispersion relation for the SH-type waves is derived. The obtained dispersion relation for the gradient layered structures reveals a complex interplay between wave phenomena and material properties. Numerical analysis is performed to illustrate the theoretical results for various gradient parameter values, demonstrating a significant influence on dispersion curves, phase velocity, group velocity, and wave number. This understanding holds paramount importance for seismic imaging, geological resource exploration, and the design of resilient infrastructure, thereby fostering innovation in geophysics and engineering.

The rapid advancements in machine learning have made its application to anomalous diffusion analysis both essential and inevitable. This review systematically introduces the integration of machine learning techniques for enhanced analysis of anomalous diffusion, focusing on two pivotal aspects: single trajectory characterization via machine learning and representation learning of anomalous diffusion. We extensively compare various machine learning methods, including both classical machine learning and deep learning, used for the inference of diffusion parameters and trajectory segmentation. Additionally, platforms such as the anomalous diffusion challenge that serve as benchmarks for evaluating these methods are highlighted. On the other hand, we outline three primary strategies for representing anomalous diffusion: the combination of predefined features, the feature vector from the penultimate layer of neural network, and the latent representation from the autoencoder, analyzing their applicability across various scenarios. This investigation paves the way for future research, offering valuable perspectives that can further enrich the study of anomalous diffusion and advance the application of artificial intelligence in statistical physics and biophysics.

We present our analysis of the identified hadrons ((pi ^+), (K^+), and p) kinetic freeze-out properties in relativistic collisions at (sqrt{s_{NN}} = 200) GeV. We analyze the transverse momentum spectra of these hadrons across various collision systems, such as copper–copper ((Cu-Cu)), zirconium–zirconium ((Zr-Zr)), ruthenium–ruthenium ((Ru-Ru)), uranium–uranium ((U-U)), and gold–gold ((Au-Au)) collisions, in distinct centrality intervals at the same center-of-mass energy using the modified Hagedorn model with embedded flow. The freeze-out parameters, namely the kinetic freeze-out temperature ((T_0)), transverse flow velocity ((beta _T)), and the entropy-related parameter (n), are extracted. Taking (T_0) and (beta _T) as common, it is observed that in all the above collisions, (T_0), (beta _T), and the parameter n diminish toward the periphery and are greater in central collisions. However, (T_0) in central collisions across all the systems remains unchanged, indicating a phase transition from hadronic matter to quark–gluon plasma. Furthermore, the temperature required for the phase transition across various systems is different. Large systems exhibit a shift in the potential start of the phase transition in peripheral collisions, which is intriguing. We also observe a direct relation between the extracted parameters and the system’s size.