Search Results (538)

For investigating and modeling the swelling potential of anhydrite rocks, it is important to define a fast but accurate, reliable, and repeatable procedure for mineral identification and quantification of anhydrite mineral in rock samples. We propose a quantitative evaluation of the applicability of two different SEM-based approaches (namely, image analysis and the use of the O/S atomic ratio) for the identification and quantification of anhydrite in polished slices of rock. We compare the results obtained with the bulk densities of the samples and with the outcomes of thermogravimetric analyses, demonstrating high convergence between the different data. We eventually propose a critical comparison between the proposed approaches and the existing methods, overall providing a practical guide for the selection of the best analytical procedure for the quantification of anhydrite content in rocks and, consequently, for the correct estimation of swelling potential. Full article

This study investigates the vibrational characteristics of multi-layered graphene sheets with variable thickness (VTGSs) by using molecular dynamics (MD) simulations. It is aimed to determine how the natural frequencies and vibration damping ratios of variable-thickness graphene change with respect to temperature. Atomistic models for six distinct geometries (1L, 3LT, 3LTB, 5LT, 5LTB, and 9LTB) were generated to analyze the influence of structural design and temperature on their natural frequencies. The simulations were performed using the Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) with an AIREBO potential to represent interatomic carbon interactions. Natural frequencies of all atomistic models were extracted by applying the Fast Fourier Transform (FFT) method to the Velocity Autocorrelation Function (VACF) data obtained from the simulations. In addition, the analysis was conducted at three different temperatures: 250 K, 300 K, and 350 K. Key findings reveal that an increase in the number of graphene layers results in a decrease in the fundamental natural frequency due to the increased mass of the structure. Moreover, it was noted that natural frequencies decrease with increasing temperature. It is attributed to the reduction in structural rigidity at higher thermal energies. These results provide critical insights into how geometric and thermal variations affect the dynamic behavior of complex multi-layered graphene structures. Full article

The blocking layer is crucial for inhibiting recombination processes in photovoltaics that utilize oxide semiconductors, such as dye-sensitized solar cells (DSSCs), quantum-dot-sensitized solar cells (QDSSCs), and perovskite solar cells. However, its effectiveness strongly depends on the chosen deposition method. This study systematically evaluates the most suitable approach for obtaining a uniform, pinhole-free titanium dioxide (TiO₂) blocking layer by using three deposition methods: radio-frequency sputtering, spin-coating, and chemical bath deposition. The electrochemical, optical, and morphological properties of blocking layers were characterized using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), UV-VIS spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and Kelvin probe force microscopy (KPFM). KPFM analysis, together with CV and EIS, revealed that the lower R_ct values and higher CV currents observed in spin-coated (SC_11-33) and vertically deposited CBD films (CB_5, CB_6) resulted from incomplete FTO coverage. In contrast, sputtered (SP_21-24) and horizontally deposited CBD films (CB_1, CB_2) demonstrated significantly higher R_ct values and improved surface coverage. Full DSSCs fabricated with SP_23, SC_33, and CB_2 confirmed the correlation between interfacial properties and photovoltaic performance. This combined approach offers a fast, material-efficient, and environmentally conscious screening method for optimizing blocking layers in solar cell technologies. Full article

In this study, novel Al₆₀₆₁-(30-x)B₄C-xSm₂O₃ (x = 0, 1, 3, 5, 7, and 9 wt%) composites were fabricated using high-energy ball milling followed by cold pressing and sintering. The aim was to improve both the mechanical performance and radiation-shielding capabilities by integrating Sm₂O₃ as a reinforcement phase. Microstructural analyses via XRD and SEM-EDX revealed that the addition of Sm₂O₃ significantly enhanced phase uniformity, reduced porosity, and improved interfacial bonding, especially by mitigating the inherent poor wettability between Al₆₀₆₁ and B₄C. As a result, the relative density, hardness, and wear resistance were considerably improved with an increasing Sm₂O₃ content. Monte Carlo simulations (MCNP6.2) demonstrated that while thermal neutron shielding showed a slight decline due to the reduced boron content, fast neutron and gamma-ray attenuation were substantially enhanced owing to the high atomic number and density of Sm₂O_3. The results demonstrate that the mechanical performance and superior neutron-shielding properties contribute to new visions in material design and applications and have the potential to provide safer and more effective radiation-protection solutions that are environmentally sustainable. Full article

In this work, the structures of the isolated anion and anhydrous and monohydrated sodium salts of alizarin red S (ARS) have been theoretically investigated within the density functional theory framework (B3LYP/6-311++G** calculations). The combination of calculations with the scaled quantum mechanics force field (SQMFF) methodology has allowed the assignment of the experimental infrared spectrum of ARS in the solid phase and the determination of the corresponding force constants. The structural analysis also included the investigation of the NMR and UV-visible spectra of the compound in solution in light of the undertaken quantum chemical calculations, the obtained theoretical data being in good agreement with the corresponding experimental ones. The impact of the presence of the Na⁺ counterion and hydration water on the properties of the organic ARS⁻ fragment was evaluated. Atoms in molecules theory (AIM) analysis was also undertaken to obtain further details on the electronic structure of the investigated species, and the HOMO-LUMO gap was determined to evaluate their relative reactivity. Globally, the results obtained in this work extend the available information on alizarin red S and may also be used for the fast identification of the three studied species of the compound investigated (anhydrous and monohydrated sodium salts and isolated anion). Full article

In this study, the neutron and gamma radiation-shielding properties of serpentinites from the Guleman ophiolite complex were investigated, and results were evaluated in comparison with rare earth element (REE) content. The linear and mass attenuation coefficients (LAC and MAC), half-value layer (HVL), mean free path (MFP), and effective atomic numbers (Z_eff) of serpentinite samples were experimentally measured in the energy range of 80.99–383.85 keV. Theoretical MAC values were calculated. Additionally, fast neutron removal cross-sections, as well as thermal and fast neutron macroscopic cross-sections, were theoretically determined. The absorbed equivalent dose rates of serpentinite samples were also measured. The radiation protection efficiency (RPE) for gamma rays and neutrons were determined. It was observed that the presence of rare earth elements within serpentinite structure has a significant impact on thermal neutron cross-sections, while crystalline water content (LOI) plays an influential role in fast neutron cross-sections. Moreover, it has been observed that the concentration of gadolinium exerts a more substantial influence on the macroscopic cross-sections of thermal neutrons than on those of fast neutrons. The research results reveal the mineralogical, geochemical, morphological and radiation-shielding properties of serpentinite rocks contribute significantly to new visions for the use of this naturally occurring rock as a geological repository for nuclear waste or as a wall-covering material in radiotherapy centers and nuclear facilities instead of concrete. Full article

A simple and fast analytical method was developed and applied to assess the effect of two forms of zinc fertilization on a pecan tree cultivar in Uruguay: fertigation and foliar application with a specially formulated fertilizer. Zinc content was determined in 36 leaf samples from two crop cycles: 2020–2021 and 2021–2022. Fresh samples were dried, ground, and sieved. Analytical determinations were performed by flame atomic absorption spectrometry (FAAS, considered a standard method) and energy dispersive X-ray spectrometry (EDXRF, the proposed method). In the first case, sample preparation was carried out by microwave-assisted digestion using 4.5 mol L⁻¹ HNO₃. In the second case, pellets (Φ 13 mm, 2–3 mm thick) were prepared by direct mechanical pressing. Figures of merit of both methodologies were adequate for the purpose of zinc monitoring. The results obtained from both methodologies were statistically compared and found to be equivalent (95% confidence level). Based on the principles of Green Analytical Chemistry, both procedures were evaluated using the Analytical Greenness Metric Approach (AGREE and AGREEprep) tools. It was concluded that EDXRF was notably greener than FAAS and can be postulated as an alternative to the standard method. The information emerging from the analyses aided decision-making at the agronomic level. Full article

The short-term scheduling of pumped-storage hydropower plants is characterised by high dimensionality and nonlinearity and is subject to multiple operational constraints. This study proposes an intelligent scheduling framework that integrates an Atomic Orbital Search (AOS)-optimised Long Short-Term Memory (LSTM) network with the Deep Deterministic Policy Gradient (DDPG) algorithm to minimise water consumption during the generation period while satisfying constraints such as system load and safety states. Firstly, the AOS-LSTM model simultaneously optimises the number of hidden neurons, batch size, and training epochs to achieve high-precision fitting of unit flow–efficiency characteristic curves, reducing the fitting error by more than 65.35% compared with traditional methods. Subsequently, the high-precision fitted curves are embedded into a Markov decision process to guide DDPG in performing constraint-aware load scheduling. Under a typical daily load scenario, the proposed scheduling framework achieves fast inference decisions within 1 s, reducing water consumption by 0.85%, 1.78%, and 2.36% compared to standard DDPG, Particle Swarm Optimisation, and Dynamic Programming methods, respectively. In addition, only two vibration-zone operations and two vibration-zone crossings are recorded, representing a reduction of more than 90% compared with the above two traditional optimisation methods, significantly improving scheduling safety and operational stability. The results validate the proposed method’s economic efficiency and reliability in high-dimensional, multi-constraint pumped-storage scheduling problems and provide strong technical support for intelligent scheduling systems. Full article

This study presents a hybrid computational investigation into the radiation shielding behavior of Fe-enriched Al-based alloys (Al-Fe-Mo-Si-Zr) for potential use in nuclear applications. Four alloy compositions with varying Fe contents (7.21, 6.35, 5.47, and 4.58 wt%) were analyzed using a combination of Monte Carlo simulations, machine learning (ML) predictions based on multilayer perceptrons (MLPs), EpiXS, and SRIM-based charged particle transport modeling. Key photon interaction parameters—including mass attenuation coefficient (MAC), half-value layer (HVL), buildup factors, and effective atomic number (Z_eff)—were calculated across a wide energy range (0.015–15 MeV). Results showed that the 7.21Fe alloy exhibited a maximum MAC of 12 cm²/g at low energies and an HVL of 0.19 cm at 0.02 MeV, indicating improved gamma attenuation with increasing Fe content. The ML model accurately predicted MAC values in agreement with Monte Carlo and XCOM data, validating the applicability of AI-assisted modeling in material evaluation. SRIM calculations demonstrated enhanced charged particle shielding: the projected range of 10 MeV protons decreased from ~55 µm (low Fe) to ~50 µm (high Fe), while alpha particle penetration reduced accordingly. In terms of fast neutron attenuation, the 7.21Fe alloy reached a maximum removal cross-section (Σ_R) of 0.08164 cm⁻¹, showing performance comparable to conventional materials like concrete. Overall, the results confirm that Fe-rich Al-based alloys offer a desirable balance of lightweight design, structural stability, and dual-function radiation shielding, making them strong candidates for next-generation protective systems in high-radiation environments. Full article

Rapid advancement in the nanotechnology and semiconductor industries has driven the demand for fast, precise measurement systems. Atomic force microscopy (AFM) is a standout metrology technique due to its high precision and wide applicability. However, when operated at high speeds, the quality of AFM images often deteriorates, especially in areas where sharp topographic features are present. This occurs because the feedback speed of the Z-scanner cannot keep up with the sample height changes during raster scanning. This study presents a simple variable scan speed control strategy for improving AFM imaging speed while maintaining the image quality obtained at low scan speeds. The proposed strategy aims to leverage the similarity in the height profiles between successive scan lines. The topographic information collected from the previous line scan is used to assess the surface complexity and to adjust the scan speed for the following line scan. The AFM system with this variable speed control algorithm was found to reduce the scan time needed for one AFM image by over 50% compared to the fixed-speed scanning while maintaining the similar level of accuracy. The calculated mean square errors (MSEs) show that the combination of speed adjustments and preemptive surface topography prediction has successfully allowed us to suppress the potential oscillations during the speed adjustment process, thereby enhancing the stability of the adaptive AFM system as well. Full article

Laser nanostructuring via Laser-Induced Periodic Surface Structures (LIPSS), generated using femtosecond laser pulses, has been investigated as a method for precisely modifying titanium surfaces. By adjusting parameters such as the fluence and pulse number of the laser beam, it is feasible to tailor the surface morphology, roughness, and oxidation states of species that can significantly influence the properties and surface bioactivity of the material. In this study, the LIPSS was applied to commercially pure titanium and evaluated for its ability to support calcium phosphate nucleation and growth in Simulated Body Fluid (SBF). Scanning Electron Microscopy (SEM) and Fast Fourier Transform (FFT) analysis confirmed the formation of well-defined periodic structures. Additional characterizations performed by Atomic Force Microscopy (AFM) and X-ray Photoelectron Spectroscopy (XPS) revealed, after laser treatment of titanium, its increased surface roughness and oxidation levels, respectively. These features, when assessed after immersion in SBF, were associated with an improved potential biological performance of the nanostructured surface of the investigated material. The results demonstrated that LIPSS-treated titanium effectively promoted calcium phosphate growth, indicating its enhanced potential bioactivity. Overall, LIPSS nanostructuring presents a scalable and cost-effective strategy for engineering titanium surfaces with potential bioactive properties, supporting their promising application in advanced biomedical implants. 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

: Predicting the mechanical response of industrial alloys is crucial for optimizing manufacturing processes and improving material performance. Traditional, solely experimental approaches, though effective, are inefficient as they are resource-intensive, requiring extensive laboratory testing and the iterative calibration of processing conditions. These costs can be avoided through computational/virtual experiments based on a multiscale hierarchical framework that integrates macroscopic approaches, mesoscale modelling as well as atomic level and advanced thermodynamical simulations to study and predict the mechanical response of metallic systems. In the context of this work, a framework for studying the effect of forming on metallic materials is proposed, applied, and validated on the hot extrusion of AA6063. Coupling thermodynamic simulations (including Phase Field) results with literature data establishes a microstructurally accurate representative volume element (RVE) design. This way, the phase fraction and the grain size of the RVE are determined by thermodynamic simulations (ThermoCalc, MICRESS), which can be validated via microstructure characterization. It is known that the mechanical properties of the individual phases affect the macroscopical properties of the material. Using atomic level simulations (i.e., molecular dynamics), the dislocation density of the material is calculated and utilized as an input for a Crystal Plasticity Fast Fourier Transformation simulation. This iterative process can be applied to match all stages of manufacturing processes. The hierarchical and systematic integration of these computational methodologies enables a rigorous analysis of the effect that processing parameters have on the microstructure. This work contributes to the broader effort of creating experiment-free workflows for designing materials and processes by leveraging a multiscale modeling approach. Coupled with experimental data, the predictive accuracy of the mechanical behavior can be further enhanced. Full article

The development of fast-charging lithium-ion batteries urgently requires high-performance anode materials. In this paper, through an ultrafast carbothermal shock (CTS) strategy, titanium niobium oxide (TiNb₂O₇, TNO) with an optimized structure was successfully synthesized within 30 s. By regulating the synthesis temperature to 1200 °C, the TNO-1200 material was obtained. Its lattice parameters (a-axis: 17.6869 Å) and unit-cell volume (796.83 ų) were significantly expanded compared to the standard structure (a-axis: 17.51 Å, volume ~790 ų), which widened the lithium-ion migration channels. Rietveld refinement and atomic position analysis indicated that the partial overlap of Ti/Nb atoms and the cooperative displacement of oxygen atoms induced by CTS reduced the lithium-ion diffusion energy barrier. Meanwhile, the cation disorder suppressed the polarization effect. Electrochemical tests showed that after 3000 cycles at a current density of 10 C, the specific capacity of TNO-1200 reached 125 mAh/g, with a capacity retention rate of 98%. EDS mapping confirmed the uniform distribution of elements and the absence of impurity phases. This study provides an efficient synthesis strategy and theoretical basis for the design of high-performance fast-charging battery materials through atomic-scale structural engineering. Full article

Electrostatic detection is a highly accurate way to monitor system performance failures at an early stage. However, due to the weak electrostatic signal, it can be easily interfered with under complex real-world conditions, leading to a reduction in its monitoring capability. During the electrostatic monitoring of rolling bearings, noise can easily drown out the effective signal, making it difficult to extract fault characteristics. In order to solve this problem, a sparse representation based on cluster-contraction stagewise orthogonal matching pursuit (CcStOMP) is proposed to extract the fault features in the electrostatic signals of rolling bearings. The method adds a clustering contraction mechanism to the stagewise orthogonal matching pursuit (StOMP) algorithm, performs secondary filtering based on atom similarity clustering on the selected atoms in the atom search process, updates the support set, and finally solves the weights and updates the residuals, so as to reconstruct the original electrostatic signals and extract the fault feature components of rolling bearings. The method maintains fast convergence while analysing the extraction effect by comparing the measured signals of rolling bearing outer ring and bearing roller faults with the traditional StOMP algorithm, and the results show that the CcStOMP algorithm has obvious advantages in accurately extracting the fault features in the electrostatic monitoring signals of rolling bearings. Full article