Search Results (4,721)

Fine dust generated during mining operations has become a key factor restricting the sustainable development of mines. The wet chord grid water film (WCGWF) dust removal technology, based on its unique dust–water interaction mechanism, has shown superior performance in removing coarse dust particles. Nevertheless, its dust removal efficiency for fine dust and the corresponding optimization approaches remain unclear. In this paper, experimental dust with a mean particle size of 10.32 μm was prepared. A WCGWF dust removal experimental platform was established. The effects of nozzle atomization characteristics, dust generation rate, chord grid position, and water supply pressure on the total dust removal efficiency of fine dust were systematically investigated. The results show that the hollow-cone nozzle has lower water consumption and a smaller droplet size than the solid-cone nozzle. The total dust removal efficiency of WCGWF remained stable under different dust generation rates (7.0–19.5 g/min). As the distance between the chord grid plate (CGP) and the nozzle outlet increased from 450 mm to 950 mm, the total dust removal efficiency of WCGWF increased from 66.7% to 73.6%. With the water supply pressure rising from 0.3 MPa to 0.7 MPa, the mean Sauter mean diameter (SMD) of the hollow-cone nozzle in the downstream region decreased from 138.9 μm to 90.5 μm. Meanwhile, the spray dust removal efficiency (from 48.1% to 59.6%) and the second-stage collection efficiency of the CGP (from 32.6% to 38.0%) both increased simultaneously. The findings validate the effectiveness of WCGWF dust removal technology as an efficient and environmentally friendly method for fine dust control. Full article

Hydrogen sulfide (H₂S), a high-volume by-product of the hydrodesulfurization of fossil fuels, can be valorized by thermolysis to recover both molecular hydrogen and elemental sulfur, rather than being oxidized as in the conventional Claus process. The viability of this route depends on quantitative knowledge of the reaction mechanism and of the energy costs of dissociation, which are difficult to obtain experimentally at the temperatures involved. Here we study H₂S thermolysis by reactive molecular dynamics (RMD) with the ReaxFF potential for systems of 1000 H₂S molecules at 1 atm, addressing three coupled questions: the simulation parameters required for dilute gases, the energetics of dissociation, and the elementary reaction mechanism. The interaction cutoff radius proved critical: the original 10 Å value, parametrized for condensed systems, misses about 23 eV of attractive non-bonded interaction energy in the gaseous system at 298.15 K (≈0.023 eV per molecule) and fails to capture dissociation at 3000 K within 20 ns, whereas radii of 30–40 Å converge. Using a 40 Å cutoff at 2500, 3000 and 3500 K, atom-resolved species-transition records reveal a free-radical chain mechanism built from the same set of elementary steps at the three temperatures, whose relative contributions shift with temperature: S–H homolysis initiates the chain, hydrogen abstraction (H• + H₂S → H₂ + HS•) is essentially the exclusive source of H₂ (persistent H• + H• recombination contributed only 1, 13 and 17 events, below 0.5% of the abstraction count), and a slow sulfur-condensation stage (S₂ → S₃ → S₄) limits the net conversion, which reached 9.3 ± 0.9%, 26.3 ± 1.4% and 46.7 ± 1.6% within the simulated windows (single-trajectory counting resolution)—kinetically limited values, not equilibrium conversions. The enthalpy of the system rises linearly with the number of H₂S molecules consumed (R² ≥ 0.99), defining energy costs of 2.46 ± 0.04, 3.10 ± 0.08 and 3.95 ± 0.18 eV per molecule that increase with temperature by ≈1.48 eV per 1000 K; at 3500 K the cost lies between the 0 K complete-dissociation limit D₀ = 3.90 eV derived from the experimental H–SH bond energy and the Kirchhoff-corrected complete-dissociation enthalpy at that temperature (4.11–4.12 eV), statistically indistinguishable from the latter (a 0.9σ difference). These results provide a thermochemically validated, molecular-level basis for engineering the valorization of residual H₂S as a source of green hydrogen. Full article

An algorithm for large-scale correlated calculations on atoms is presented that significantly reduces the scaling of these calculations with the number of single-particle functions used to construct the N-particle states. The reduction is provided in the stage in which the Hamiltonian matrix is contracted with the coefficients or amplitudes of the basis states in an iterative procedure such as the Davidson method. The algorithm relies on the representation of the radial one-particle functions on a grid, and it makes use of the multipole expansion of the electron–electron interaction in a sequence of transformations on the spinors, coefficients, and potentials. It also uses prototyping for the angular integrals and evaluation of recoupling coefficients for the configuration state functions (CSFs) separately rather than for pairs of CSFs. The scaling is verified with calculations on two-electron atoms and analyzed in terms of the number of operations required for each stage of both the proposed algorithm and the conventional methods. Full article

Measurements of charge-changing cross-sections were developed as a method for determining proton radii, particularly for unstable, short-lived nuclei. Such cross-sections must be measured with high precision to determine the precise charge radii. However, there are complexities in the experimental method leading to uncertainties in determining precise nuclear radii. Therefore, good models describing the complex physics of charged particle interactions are needed in order to validate the experimental method and to estimate the contribution of systematic uncertainties. GEANT4 is a Monte Carlo simulation code widely used to describe interactions in heavy-ion collisions over a broad energy range, ranging from atomic physics to cosmic-ray energies. Experimental measurements of charge-changing reactions for carbon isotopes ^10,12C on different secondary targets were performed. In the present work, the experimental detector geometry, beam profile, and detector configuration were implemented in GEANT4 simulations in order to reproduce the experimental conditions as closely as possible. The experimentally obtained spectra are compared with the corresponding GEANT4 simulations to validate the interpretation of the measured spectra and assess systematic effects. Also, the secondary particle yield ratio is deduced and compared with GEANT4 results. Full article

Lonicerae japonicae flos (LJ), derived from Lonicera japonica Thunb., is a classic medicinal and edible plant traditionally used to clear heat, detoxify, and disperse wind-heat. It is widely consumed as a health tea or food additive and played a significant role during the COVID-19 pandemic. Its closely related species, Lonicerae flos (LFS), derived from L. macranthoides, L. hypoglauca, L. confusa, and L. fulvotomentosa, share similar functions. Distinguishing between these two is crucial to minimizing medication-related risks; however, studies on their differences in inorganic elements are currently insufficient. This study investigated the content differences in ten inorganic elements in 97 samples using inductively coupled plasma mass spectrometry and inductively coupled plasma atomic emission spectrometry. LJ exhibited significantly higher iron (Fe) content and considerably lower manganese (Mn) content than LFS. Fe, Mn and Na were identified as key discriminatory elements through orthogonal partial least squares-discriminant analysis, and cluster analysis based on the Fe/Mn ratio also achieved clear separation between the two groups. Network pharmacology and pathway enrichment analyses were subsequently conducted to explore the potential biological relevance of Fe- and Mn-associated differences. Additionally, molecular docking provided exploratory computational assessments of theoretical interactions between Fe/Mn and selected target proteins under simplified conditions. It is important to note that these computational results should not be interpreted as direct evidence of biological activity, since no in vitro or in vivo validation was performed. Overall, this study provides elemental profiling data to differentiate between LJ and LFS and highlights the potential value of the Fe/Mn ratio as a complementary chemical indicator for the authentication and quality evaluation of Lonicera medicinal materials. Full article

Correlated electronic phenomena in magic-angle twisted bilayer graphene have garnered widespread research interest in two-dimensional materials science. As a powerful multiscale framework bridging atomic-scale resolution and mesoscopic structural evolution, the structural phase field crystal method has been widely adopted for graphene system studies. In this work, we develop a self-consistent XPFC model specifically for twisted bilayer graphene (tBLG) simulations. By globally optimizing the core free-energy functional parameters via a genetic algorithm, the proposed model achieves a marked improvement in consistency between the equilibrium density field and the first-principles generalized stacking fault energy surface. We further introduce a self-consistent dynamic interlayer interaction potential to replace the conventional fixed-substrate approximation, which captures the bidirectional coupling and mutual relaxation between adjacent graphene layers in a self-consistent manner. We calibrate the precise magnitude of the interlayer potential using the widths of stacking domain boundaries between distinct stacking configurations as a key metric, with the results benchmarked against atomistic simulation data. When applied to the 1.1° magic-angle tBLG system, the model uncovers spontaneous structural relaxation driven by interlayer van der Waals interactions: low-energy AB–BA stacking domains expand significantly, while high-energy AA domains shrink correspondingly. Full article

Herein, we report an unexpected pseudo-multicomponent transformation discovered during attempts to selectively nitrate the pyridine core of 3-acetyl-2,4,6-trimethylpyridine (3). Despite employing standard nitration conditions, including KNO₃–H₂SO₄ and HNO₃–H₂SO₄ mixtures, electrophilic substitution of the aromatic ring did not occur. Instead, the reaction sequence promoted an in situ nitrozation, dehydration to nitrile oxide intermediates, and subsequent [3+2]-cycloaddition involving two substrate molecules. This process yielded a novel, highly functionalized furoxan derivative, precisely identified as 3,4-bis(2,4,6-trimethylnicotinoyl)-1,2,5-oxadiazole 2-oxide (5). The molecular architecture of compound 5 was established by ¹H and ¹³C NMR spectroscopy, mass spectrometry, elemental analysis, and single-crystal X-ray diffraction (XRD) analysis. To elucidate the stereochemical and electronic features governing compound 5, DFT calculations were performed at the ωB97X-D/6-311++G(d,p) level of theory. The experimental crystallographic disorder of the N-oxide oxygen atom was computationally rationalized by the thermodynamic near-degeneracy (ΔG < 0.63 kcal/mol) of two orientational isomers (5a and 5b). Furthermore, frontier molecular orbital analysis within the framework of perturbation theory accounted for the head-to-tail regioselectivity during cyclization, while wide energy gaps (ΔE = 8.13–8.27 eV) and high chemical hardness (η = 4.07–4.14 eV) underscored the kinetic stability of the heterocycle. Phenotypic and target-specific in silico profiling using PASS Online identified Matrix Metalloproteinase-9 (MMP-9) as a relevant target for potential hemorheological and cardioprotective applications. Validated molecular docking simulations across three human MMP-9 crystallographic domains (PDB: 8K5Y, 6ESM, 4XCT) demonstrated competitive binding affinities and balanced Ligand Efficiency metrics (LE = 0.26–0.29 kcal/mol/heavy atom), anchoring compound 5 within the catalytic pocket via conventional hydrogen bonds and π-mediated interactions. Finally, in vitro evaluations using a blood hyperviscosity model confirmed significant hemorheological efficacy, as compound 5 effectively prevented the rise in blood viscosity, outperforming the reference drug pentoxifylline. The convergence of computational insights and experimental functional activity establishes this novel bis(nicotinoyl)furoxan framework as a promising candidate for further hemorheological and cardioprotective applications. Full article

Relativistic interaction of ultra-intense laser pulses with cluster targets is of particular interest for high-energy-density physics, compact X-ray source development, and laboratory astrophysics. Understanding the dynamics of such plasmas requires precise control of their parameters, in particular temperature, on subpicosecond timescales. In this study, X-ray spectral methods were used to diagnose the laser plasma of krypton cluster targets, created at laser pulse intensities of the order of 10²⁰–10²¹ W/cm². The use of a time-dependent detailed radiation-collisional kinetic model made it possible to describe the results of the observed X-ray spectra in the femtosecond laser plasma of a cluster target. We present a method for diagnosing the non-stationary plasma of high-atomic-number (krypton) clusters using resonance spectral lines 1s²2s²2p⁵3s ¹P₁–1s²2s²2p^{6 1}S₀ and 1s²2s²2p⁵3s ³P₁–1s²2s²2p^{6 1}S₀ of the Ne-like Kr XXVII ion, allowing one to determine the plasma temperature at the moment of “plasma channel” formation. In the experiment, this temperature was shown to be 55 ± 5 eV. The same spectroscopic approach can be extended to other cluster species (for example, Ar, Xe) for non-stationary plasma diagnostics in the relativistic regime. Full article

Background/Objectives: Cancer remains one of the leading causes of death worldwide. Although chemotherapy is widely used, it is associated with severe side effects, including myelosuppression and systemic toxicity. Nanoparticles have emerged as promising candidates for modulating drug activity. In this study, we investigated whether platinum nanoparticles (PtNPs) of various sizes interact with idarubicin (IDA), an anthracycline anticancer drug used primarily to treat acute leukaemia. Methods: Interactions between PtNPs and IDA were analysed using dynamic light scattering (DLS), atomic force microscopy (AFM), fluorescence spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and near-infrared (NIR) spectroscopy. Thermodynamic and thermal properties were assessed using isothermal titration calorimetry (ITC) and differential scanning calorimetry (DSC). Biological effects were evaluated using the Ames mutagenicity assay on the Salmonella enterica serovar Typhimurium TA98 strain and cytotoxicity assays on SK-BR-3 and MCF-7 cell lines. Results: DLS demonstrated changes in the hydrodynamic diameter of PtNPs following IDA addition, which were further supported by AFM imaging. PtNPs significantly quenched IDA fluorescence, indicating close molecular interactions, which were further supported by FTIR and NIR. ITC revealed that the interactions were endothermic, with enthalpy values ranging from 1.2 to 3.6 kcal/mol, and DSC demonstrated that the PtNP-IDA combination altered the melting temperature of IDA. Biological assays revealed that all examined PtNP sizes influenced IDA mutagenicity in the Salmonella enterica serovar Typhimurium TA98 strain. Furthermore, PtNPs modulated the cytotoxicity of IDA in SK-BR-3 and MCF-7 cell lines in a dose-dependent manner. Conclusions: These findings demonstrate that PtNPs interact with IDA and modulate its biological activity. However, in this study no non-cancerous cell lines were examined; therefore, the observed interactions and biological effects support further investigation of the PtNP-IDA combination in the context of nanoparticle-assisted anticancer therapy on a broader range of in vitro cell lines. Full article

Protein–ligand interactions (PLIs) play a crucial role in drug discovery, and accurately predicting protein–ligand binding affinity (PLA) remains a central challenge in computer-aided drug design. Although graph neural networks (GNNs) have demonstrated considerable potential in molecular modeling, existing methods still face several limitations, including excessive reliance on hand-crafted chemical features, loss of spatial information, and difficulties in integrating heterogeneous affinity labels, which restrict their generalization capability in PLA prediction. To address these challenges, we propose GAMT-GINE, a graph isomorphism network that integrates continuous spatial awareness with multi-task learning. The model employs minimalist atomic features and a batch-normalization-free mechanism, together with a multi-task branch that uses a large amount of half-maximal inhibitory concentration (IC₅₀) data as an auxiliary prediction target. Experimental results show that GAMT-GINE achieves a Pearson’s correlation coefficient (R_p) of 0.791 and a root mean square error (RMSE) of 1.403 on the CASF-2013 benchmark dataset. In the generalization evaluation on CASF-2016, R_p further increases to 0.831, while RMSE decreases to 1.227, demonstrating performance comparable to that of current State-of-the-Art models. Furthermore, comprehensive evaluations, including ablation studies, feature importance analysis, analysis of the effects of data filtering on model performance and data composition, and analysis of the influence of training–test data similarity on prediction results, indicate that GAMT-GINE can effectively utilize continuous spatial information and heterogeneous affinity labels, achieving good predictive accuracy and cross-dataset generalization capability. Full article

Polyphenylene sulfide (PPS) is a high-performance thermoplastic engineering material known for its excellent chemical resistance, thermal stability, and flame retardancy. In this work, the interfacial mechanical behavior of short-cut Kevlar fiber-reinforced PPS composites was systematically investigated by all-atom molecular dynamics (MD) simulations. By constructing a full-atom interface model between an amorphous PPS matrix and a Kevlar crystal, interfacial normal tension and tangential shear simulations were performed to reveal the mechanisms of load transfer, damage initiation, and damage evolution at the molecular scale. The results show that the interfacial normal tensile strength (approximately 245 MPa) is lower than the bulk tensile strength of pure PPS (approximately 270 MPa), which is attributed to the stiffness mismatch at the interface induced by the high modulus of Kevlar fibers, promoting the preferential initiation and propagation of voids near the geometrical interface. The tangential shear process exhibits pronounced stick-slip characteristics, with the interfacial binding energy fluctuating periodically with shear displacement, corresponding to the alternating establishment and rupture of non-bonded interactions between molecular chains. This study provides a theoretical basis for the micromechanical design of high-performance thermoplastic composite interfaces and identifies molecular-level optimization directions for future interfacial modification strategies of Kevlar/PPS systems. Full article

Plant protection and sprinkler irrigation rely on common fluid dynamic processes, including liquid atomization, droplet transport, target interaction, and flow distribution. This review analyses these mechanisms within a multi-scale framework. The analysis starts with droplet–target interactions. It addresses droplet impact and foliar retention in plant protection, alongside droplet kinetic energy and soil-surface responses in irrigation. The discussion then extends to the spatial transport and distribution of sprays. At the device scale, this work examines nozzles and sprinklers from the perspective of fluid mechanics and structural innovation, detailing how nozzle geometry and flow conditions affect macroscopic application performance. Finally, this review addresses advances at the system scale, with a focus on energy consumption and data-driven performance prediction. By connecting fluid behavior across multiple spatial scales, this work links micro-scale droplet dynamics to whole-system performance and identifies directions for improving agricultural spraying and sprinkler irrigation systems. Full article

A smooth window function $♢\left(x\right)\in [0,1]$ that restricts a field-theory action to a finite spacetime domain generates a common conservation structure across diverse experimentally realized finite-time quantum phenomena. Applying the windowed action principle yields windowed Noether identities of the form ${\partial }_{\mu }(♢J^{\mu })=0$: exact conservation of the windowed current, with apparent non-conservation of local currents confined to the boundary layer where ${\partial }_{\mu }♢\ne 0$. This boundary-layer structure is mathematically identical to open-system flux terms in decoherence theory. The formalism is applied to five experimentally established settings: the timelike Unruh effect in trapped-ion detectors, the dynamical Casimir effect in superconducting circuits, quench-induced currents in cold-atom systems, ultrafast coherent control with femtosecond laser pulses, and finite-time scattering theory. In each case, the experimentally specified control window—switching function, drive envelope, quench ramp, pulse envelope, or scattering window—is shown to be an instance of the same formal object ♢, and the windowed Noether identity is derived for each setting in this unified form for the first time. Two results are new: the cross-case identification of all five control functions as instances of ♢ under a single formalism, and the formal consequence that systems with the same ungated Hamiltonian operator content but different temporal control profiles generically produce inequivalent unitary evolutions, formulated here as a structural consequence of explicit domain specification. Here, ♢ is fixed by the experimentally specified control protocol and is neither a new dynamical degree of freedom nor an additional fit function. Although it may be absorbed algebraically into a time-dependent coupling or interaction Hamiltonian, retaining it explicitly exposes the common finite-domain conservation structure across the five settings. In the purely temporal measurement limit, $g\left(t\right)=\lambda ♢\left(t\right)$ reproduces the standard von Neumann system–apparatus coupling, while the action-level extension to $♢\left(x\right)$ permits finite spacetime support and makes the associated boundary-supported current balance explicit. Full article

Although deep learning has transformed protein structure prediction, the controlled generation of functional and experimentally tractable protein structures remains a major challenge in structural bioinformatics. Diffusion models offer a versatile approach to generating protein backbones, motif-conditioned scaffolds, all-atom structures and biomolecular interaction geometries, while accommodating explicit structural and functional constraints. This review focuses on coordinate- and residue-frame-based diffusion approaches for generating protein structures, paying particular attention to geometric equivariance, conditioning strategies, all-atom modelling and interaction-aware design. We compare representative methods derived from RoseTTAFold, frame-diffusion architectures, and oriented-residue-cloud representations according to their molecular representation, generative objective, and validation strategy. We examine the criteria used to evaluate generated proteins, such as stereochemical quality, structural consistency, designability, novelty, diversity, computational efficiency, and experimental performance. Particular attention is given to the distinction between learned structural distributions and condition-dependent thermodynamic ensembles. Future progress will depend on the integration of generative models with molecular mechanics, conformational sampling, uncertainty estimation, free-energy methods, and experimental design–build–test–learn cycles. Within this framework, diffusion models offer candidate generation and constraint satisfaction capabilities within broader protein engineering workflows. Full article

Photocatalytic water splitting has emerged as a promising strategy for sustainable hydrogen production using solar energy. In this work, we investigate the photocatalytic performance of the C₂N monolayer under O₂ and O₃ exposure. Upon adsorption on C₂N, both molecules form weakly interacting states, resulting in a metallic solution. However, after dissociation into atomic oxygen, the band gap of the oxidised monolayer increases relative to the pristine C₂N, indicating a strong hybridisation of the C-O bond. These oxidised configurations exhibit band-edge positions that span the water redox potential, thereby reducing the likelihood of charge recombination and enhancing their separation. Interestingly, the optical absorption spectra show a blue shift relative to the pristine sample and lie in the visible region. These findings highlight the potential of oxygen- and ozone-modified C₂N monolayers for applications in photocatalytic water splitting and sustainable hydrogen production. Full article