Search Results (217)

Highly scattering media have garnered significant interest in recent years, ranging from potential applications in solar cells, photocatalysis, and other novel photonic devices to research on fundamental topics such as topological photonics, enhanced light–matter coupling and light confinement. Here, we report measurements of spectrally and time-resolved delayed luminescence (DL) in highly scattering rutile TiO₂ films. The complex emission kinetics manifests in the non-exponential decay of photon density and the temporal evolution of the spectral composition. We found that while the energy levels of TiO₂ nanoparticles broadly set the spectral regions of excitation and emission, our results demonstrate that the DL intensity and duration are strongly influenced by the inherent multiple elastic and inelastic processes determined by the mesoscale inhomogeneous structure of random media. We show that the lifetime of DL increases up to 6 s for the largest redshift detected, which is associated with multiple reabsorption processes. We outline a simple model for spectrally resolved DL emission from dense scattering media that can guide the design and characterization of composite materials with specific spectral and temporal properties. Full article

Both ZnO and BeO semiconductors crystallize in the hexagonal wurtzite (wz), cubic rock salt (rs), and zinc-blende (zb) phases, depending upon their growth conditions. Low-dimensional heterostructures ZnO/Be_xZn_1-xO and Be_xZn_1-xO ternary alloy-based devices have recently gained substantial interest to design/improve the operations of highly efficient and flexible nano- and micro-electronics. Attempts are being made to engineer different electronic devices to cover light emission over a wide range of wavelengths to meet the growing industrial needs in photonics, energy harvesting, and biomedical applications. For zb materials, both experimental and theoretical studies of lattice dynamics ${\mathsf{\omega }}_{\mathrm{j}}\left(\overrightarrow{\mathrm{q}}\right)$ have played crucial roles for understanding their optical and electronic properties. Except for zb ZnO, inelastic neutron scattering measurement of ${\mathsf{\omega }}_{\mathrm{j}}\left(\overrightarrow{\mathrm{q}}\right)$ for BeO is still lacking. For the Be_xZn_1-xO ternary alloys, no experimental and/or theoretical studies exist for comprehending their structural, vibrational, and thermodynamical traits (e.g., Debye temperature ${\mathsf{\Theta }}_{\mathrm{D}}\left(\mathrm{T}\right);$ specific heat ${\mathrm{C}}_{\mathrm{v}}\left(\mathrm{T}\right))$. By adopting a realistic rigid-ion model, we have meticulously simulated the results of lattice dynamics, and thermodynamic properties for both the binary zb ZnO, BeO and ternary Be_xZn_1-xO alloys. The theoretical results are compared/contrasted against the limited experimental data and/or ab initio calculations. We strongly feel that the phonon/thermodynamic features reported here will encourage spectroscopists to perform similar measurements and check our theoretical conjectures. Full article

Proteins are inherently dynamic entities that rely on flexibility across multiple timescales to perform their biological functions. The surrounding environment plays a critical role in modulating protein dynamics by exerting plasticizing or stabilizing effects. In order to characterize the conformational dynamics of Water-Soluble Chlorophyll-Binding Protein (WSCP), we measured Quasielastic Neutron Scattering (QENS) spectra over a wide temperature range between 100 and 300 K. The impact of glycerol, a common stabilizer, is investigated by comparing WSCP dissolved in a glycerol–water-containing buffer (WSCP^W+G) with WSCP in a water-containing buffer (WSCP^W). The results indicate that conformational protein dynamics are widely suppressed below 200 K but increase above this threshold, with the appearance of localized protein motions on the picosecond timescale. Glycerol appears to limit protein mobility between 280 and 300 K due to its high viscosity and hydrogen bonding in contrast to WSCP in water. Inelastic Neutron Scattering (INS) reveals the vibrational dynamics of WSCP with pronounced low-energy protein vibrations observed at about 2.5 and 6 meV. In the presence of glycerol, however, a stiffening of the vibrational motions which shifts the vibrational peaks to higher frequencies is observed. Full article

This study presents a comprehensive uncertainty and sensitivity analysis of the effective neutron multiplication factor ($k_{\mathrm{eff}}$) in a large-scale sodium-cooled fast reactor (SFR) modeled after the European Sodium Fast Reactor. Utilizing the Serpent Monte Carlo code and the ENDF/B-VII.1 cross-section library, this research investigates the impact of cross-section perturbations in key isotopes (²³⁵U, ²³⁸U, and ²³⁹Pu for both mixed oxide (MOX) and metal fuels. Particular focus is placed on the capture, fission, and inelastic scattering reactions, as well as the effects of fuel temperature on reactivity through Doppler broadening. The findings reveal that reactivity in MOX fuel is highly sensitive to the fission cross sections of fissile isotopes (²³⁹Pu and ²³⁸U, while capture and inelastic scattering reactions in fertile isotopes such as ²³⁸U play a significant role in reducing reactivity, enhancing neutron economy. Additionally, this study highlights that metal fuel configurations generally achieve a higher ($k_{\mathrm{eff}}$) compared to MOX, attributed to their higher fissile atom density and favorable thermal properties. These results underscore the importance of accurate nuclear data libraries to minimize uncertainties in criticality evaluations, and they provide a foundation for optimizing fuel compositions and refining reactor control strategies. The insights gained from this analysis can contribute to the development of safer and more efficient next-generation SFR designs, ultimately improving operational margins and reactor performance. Full article

Our objective is to test the published models of partonic energy loss, particularly those describing the energy loss mechanisms of quarks traversing nuclear matter, within the framework of semi-inclusive deep inelastic scattering. Our methodological approach focuses on quantifying the quark energy loss in cold matter by analyzing the positive pions (${\pi }^{+}$) produced in various nuclear targets, including deuterium, carbon, iron and lead, while our first approach only includes deuterium and carbon. Before normalizing the pions’ energy distribution to unity to perform a shape analysis, acceptance corrections were performed to account for the detector’s efficiency and ensure accurate comparisons of the spectra. By normalizing the energy spectra of ${\pi }^{+}$ produced from these distinct targets and based on the Baier–Dokshitzer–Mueller–Peigné–Schiff theory, which posits that quark energy loss depends only on nuclear size, it is assumed that the energy distributions of the targets will exhibit similar behavior. For this normalization, an energy shift between these distributions, corresponding to the quark energy loss, is identified. To ensure accuracy, statistical techniques such as the Kolmogorov–Smirnov test are used. The data used to test and explore the analysis technique and method were from the CLAS6 EG2 dataset collected using Jefferson Lab’s CLAS detector. Full article

Three-dimensional (3D) cellular models, such as spheroids, serve as pivotal systems for understanding complex biological phenomena in histology, oncology, and tissue engineering. In response to the growing need for advanced imaging capabilities, we present a novel multi-modal Raman light sheet microscope designed to capture elastic (Rayleigh) and inelastic (Raman) scattering, along with fluorescence signals, in a single platform. By leveraging a shorter excitation wavelength (532 nm) to boost Raman scattering efficiency and incorporating robust fluorescence suppression, the system achieves label-free, high-resolution tomographic imaging without the drawbacks commonly associated with near-infrared modalities. An accompanying Deep Image Prior (DIP) seamlessly integrates with the microscope to provide unsupervised denoising and resolution enhancement, preserving critical molecular details and minimizing extraneous artifacts. Altogether, this synergy of optical and computational strategies underscores the potential for in-depth, 3D imaging of biomolecular and structural features in complex specimens and sets the stage for future advancements in biomedical research, diagnostics, and therapeutics. Full article

Understanding the interaction of charged particles with polymers is crucial for applications in materials science, radiation physics, and electron spectroscopy. This study investigates the differences in the elastic scattering spectra of electrons and positrons in polyethylene, focusing on the underlying mechanisms that influence the spectral features. The analysis isolates key factors such as recoil energy, Doppler broadening, and the interplay between elastic and inelastic mean free paths. Using Monte Carlo simulations, we analyze the effects of the elastic and inelastic mean free paths on the intensity of the elastic peaks in an energy range from 1000 eV to 3000 eV. The results show that the elastic peaks are consistently more intense for electrons than for positrons, correlating with the differences in the respective elastic scattering cross sections. In addition, we evaluate the effects of different inelastic mean free path models on spectral variations and compare the simulated data showing how variations in inelastic mean free path values affect the intensity of elastic peaks and the elastic reflection coefficient of polyethylene. The percentage difference in the elastic reflection coefficients of electrons and positrons in polyethylene decreases from 49% to 24% when the incident particle energy increases from 1000 eV to 3000 eV. These findings contribute to a refined understanding of the interactions of electrons and positrons with polymers, improve the accuracy of Monte Carlo simulations, and promote methods for material characterization. Full article

We present a theoretical investigation of the inelastic scattering of vortex electrons by many-electron atoms embedded in a solid-state environment. Special emphasis is placed on the probability of exciting a target atom and on the relative population of its magnetic substates as described by the set of alignment parameters. These parameters are directly related to the angular distribution of the subsequent radiative decay. To demonstrate the application of the developed theoretical approach, we present calculations for the $3s^2 {}^{1}S_0\to 3s3p {}^{3}P_1$ excitation of a Mg atom and its subsequent $3s3p {}^{3}P_1\to 3s^2 {}^{1}S_0$ radiative decay. Our results highlight the significance of the orbital angular momentum (OAM) projection as well as the relative position of the vortex electron with respect to the target atom. Full article

When examined at the nanometer length scale, metallic liquids exhibit extensive ordering. Bonding enthalpies are balanced against entropic tendencies resulting in a rich complicated behavior that leads to clustering that depends on temperature but evolves on picosecond time scales. The structural organization of metallic liquids affects their thermophysical properties, such as viscosity and density, thus influencing the ability of a metallic liquid to form useful technological phases, such as metallic glasses. The time-dependent pair correlation function (the Van Hove function) was determined for metallic-glass forming Cu₄₉Zr₄₅Al₆ at 1060 °C from time-of-flight inelastic neutron scattering measurements made using the Neutron Electrostatic Levitation facility at the Spallation Neutron Source. The time for changes in local atomic connectivity, which is the timescale of atomic ordering, was determined by examining the decay of the nearest neighbor peak. The results of rigorous statistical analyses were used to distinguish between competing models of ordering, suggesting that a stretched exponential model of coordination number change is valid for this system. Full article

The gut microbiota, a complex community of microorganisms, plays a crucial role in gastrointestinal (GI) health, influencing digestion, metabolism, immune function, and the gut–brain axis. Dysbiosis, or an imbalance in microbiota composition, is associated with GI disorders, including irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and colorectal cancer (CRC). Conventional microbiota analysis methods, such as next-generation sequencing (NGS) and nuclear magnetic resonance (NMR), provide valuable insights but are often expensive, time-consuming, and destructive. Raman spectroscopy (RS) is a non-invasive, cost-effective, and highly sensitive alternative. This analytical technique relies on inelastic light scattering to generate molecular “fingerprints”, enabling real-time, marker-free analysis of microbiota composition and metabolic activity. This review explores the principles, sample preparation techniques, and advancements in RS, including surface-enhanced Raman spectroscopy (SERS), for microbiota research. RS facilitates identifying microbial species, analysing key metabolites like short-chain fatty acids (SCFA), and monitoring microbiota responses to dietary and therapeutic interventions. The comparative analysis highlights RS’s advantages over conventional techniques, such as the minimal sample preparation, real-time capabilities, and non-destructive nature. The integration of RS with machine learning enhances its diagnostic potential, enabling biomarker discovery and personalised treatment strategies for GI disorders. Challenges, including weak Raman signals and spectral complexity, are discussed alongside emerging solutions. As RS technology advances, mainly through portable spectrometers and AI integration, its clinical application in microbiota diagnostics and personalised medicine is poised to transform GI healthcare, bridging microbiota research with practical therapeutic strategies. Full article

High-resolution imaging using Transmission Electron Microscopy (TEM) is essential for applications such as grain boundary analysis, microchip defect characterization, and biological imaging. However, TEM images are often compromised by electron energy spread and other factors. In TEM mode, where the objective and projector lenses are positioned downstream of the sample, electron–sample interactions cause energy loss, which adversely impacts image quality and resolution. This study introduces a simulation tool to estimate the electron energy loss spectrum (EELS) as a function of sample thickness, covering electron beam energies from 300 keV to 3 MeV. Leveraging recent advances in MeV-TEM/STEM technology, which includes a state-of-the-art electron source with 2-picometer emittance, an energy spread of $3\times {10}^{-5}$, and optimized beam characteristics, we aim to minimize energy spread. By integrating EELS capabilities into the BNL Monte Carlo (MC) simulation code for thicker samples, we evaluate electron beam parameters to mitigate energy spread resulting from electron–sample interactions. Based on our simulations, we propose an experimental procedure for quantitively distinguishing between elastic and inelastic scattering. The findings will guide the selection of optimal beam settings, thereby enhancing resolution for nanoimaging of thick biological samples and microchips. Full article

Decision support systems based on machine learning (ML) techniques are already empowering neuro-oncologists. These systems provide comprehensive diagnostics, offer a deeper understanding of diseases, predict outcomes, and assist in customizing treatment plans to individual patient needs. Collectively, these elements represent artificial intelligence (AI) in neuro-oncology. This paper reviews recent studies which apply machine learning algorithms to optical spectroscopy data from central nervous system (CNS) tumors, both ex vivo and in vivo. We first cover general issues such as the physical basis of the optical-spectral methods used in neuro-oncology, and the basic algorithms used in spectral signal preprocessing, feature extraction, data clustering, and supervised classification methods. Then, we review in more detail the methodology and results of applying ML techniques to fluorescence, elastic and inelastic scattering, and IR spectroscopy. Full article

Advanced batteries require advanced characterization techniques, and neutron scattering is one of the most powerful experimental methods available for studying next-generation battery materials. Neutron scattering offers a non-destructive method to probe the complex structural and chemical processes occurring in batteries during operation in truly in situ/in operando measurements with a high sensitivity to battery-relevant elements such as lithium. Neutrons have energies comparable to the energies of excitations in materials and wavelengths comparable to atomic distances in the solid state, thus giving access to study structural and dynamical properties of materials on an atomic scale. In this review, a broad overview of selected neutron scattering techniques is presented to illustrate how neutron scattering can be used to gain invaluable information of solid-state battery materials, with a focus on in situ/in operando methods. These techniques span multiple decades of length and time scales to uncover the complex processes taking place fundamentally on the atomic scale and to determine how these processes impact the macroscale properties and performance of functional battery systems. This review serves the solid-state battery research community by examining how the unique capabilities of neutron scattering can be applied to answer critical and unresolved questions of materials research in this field. A thorough and broad perspective is provided with numerous practical examples showing these techniques in action for battery research. Full article

In the present study, we report infrared and Raman spectra in both solution and the solid state, together with a state-of-the art inelastic neutron scattering spectrum, of the unusual molecule pagodane. Periodic DFT calculations have enabled a complete assignment of all the modes. The isolated molecule has D_2h symmetry, which is reduced to C_i in the solid state. However, the preservation of the centre of symmetry means that the selection rules for infrared and Raman spectroscopy are almost unchanged. The exceptions are the D_2hA_u modes that are forbidden in the isolated molecule but become allowed in the solid state. These have been located in the solid-state spectra. Full article

The elastic and inelastic scattering of deuterons on ¹⁰B nuclei and the ¹⁰B(d, t)⁹B reaction were studied at a deuteron energy of 14.5 MeV. In inelastic scattering, differential cross-sections for transitions to ¹⁰B states at excitation energies, E_x, of 0.718 MeV (1⁺), 2.154 MeV (1⁺), and 3.59 MeV (2⁺) were measured. The cross-sections of the (d, t) reaction were measured for the ground (3/2⁻) and excited states of the ⁹B nucleus at E_x = 2.361 MeV (5/2⁻) and 2.79 MeV (5/2⁺). An analysis of the corresponding angular distributions was carried out using the coupled channel method. As a result of the calculations, the values of the quadrupole deformation parameters (β₂ ≈ 0.7 ± 0.1) for various transitions in the ¹⁰B nucleus in inelastic scattering were extracted. From the analysis of the (d, t) reaction, the values of spectroscopic amplitudes (SA = 0.67 and SA = 0.94) for transitions to the states of the ⁹B nucleus were extracted. The results obtained here, taking into account possible measurement errors, are in good agreement with the previously obtained data and the theoretical predictions. Full article