Local Density Research Articles

Absolute energy-dependent scintillating screen calibration for real-time detection of laser-accelerated proton bunches.

Laser-plasma accelerators (LPAs) can deliver pico- to nanosecond long proton bunches with ≳100 nC of charge dispersed over a broad energy spectrum. Increasing the repetition rates of today's LPAs is a necessity for their practical application. This, however, creates a need for real-time proton bunch diagnostics. Scintillating screens are one detector solution commonly applied in the field of electron LPAs for spatially resolved particle and radiation detection. Yet their establishment for LPA proton detection is only slowly taking off, also due to the lack of available calibrations. In this paper, we present an absolute proton number calibration for the scintillating screen type DRZ High (Mitsubishi Chemical Corporation, Düsseldorf, Germany), one of the most sensitive screens according to calibrations for relativistic electrons and x rays. The presented absolute light yield calibration shows an uncertainty of the proton number of 10% and can seamlessly be applied at other LPA facilities. For proton irradiation of the DRZ High screen, we find an increase in light yield of >60% compared to reference calibration data for relativistic electrons. Moreover, we investigate the scintillating screen light yield dependence on proton energy since many types of scintillators (e.g., plastic, liquid, and inorganic) show a reduced light yield for increased local energy deposition densities, an effect termed ionization quenching. The ionization quenching can reduce the light yield for low-energy protons by up to ∼20%. This work provides all necessary data for absolute spectral measurements of LPA protons with DRZ High scintillating screens, e.g., when used in the commonly applied Thomson parabola spectrometers.

Charge exchange recombination spectroscopy on the alkali beam of Wendelstein 7-X.

Measurements of ion temperature profiles are required to assess the energy and particle transport processes in the Wendelstein 7-X stellarator. This device is equipped with a diagnostic alkali beam, which can be utilized to determine local impurity temperatures and densities by Charge Exchange Recombination Spectroscopy (CXRS). It could provide such profiles in the edge plasma, where other diagnostics are less efficient. With this contribution, first results of CXRS measurements on the sodium beam from the scientific operation phase OP2.1 are presented. The spectroscopic system was in commissioning phase lacking some of the final optical components. Thus, the aim of the diagnostics during this campaign was to explore the measurement capabilities. Based on the processed spectra, the prospects of C5+ and C6+ ion temperature and concentration measurements are discussed. The results indicate that with the final optical setup under installation, the diagnostics could provide ion temperature profiles in the edge with 3mm radial resolution and at least 1s temporal resolution.

Modelling wild boar abundance at high resolution

Abstract By using the latest available data, we provide estimates of wild boar (Sus scrofa) distribution and abundance pre‐African Swine Fever (ASF) based on occurrence data in Europe. Secondly, as a basis for the calibration model output into densities, we used the predictions of relative abundance, and hunting yield‐based model (hunted individuals per km2), at 2x2 km for wild boar (by ENETWILD Consortium) and local wild boar densities (individuals per km2) considered reliable and obtained in the framework of the European Observatory of Wildlife (EOW), as well as some from recent literature (2015 onwards). Hunting yield predictions were considered at different spatial scales namely 5, 10 and 15 km radii buffer around localities with density estimations. The calibration of hunting yield‐based model into densities are a better fit for 15 km radius buffer and a significant relationship between model predictions of hunting yield and reliable density values at European level. This calibration of wild boar hunting yield‐based model into densities will offer the possibility to predict density values of wild boar. This will be useful to incorporate into risk factor analyses for African Swine Fever at the selected spatial range. This is the first time that absolute density estimates have been made using these two approaches for Europe, which demonstrates the added value of the observatory approach (a number of study areas where reliable density values are obtained, such as from the EOW) to generate novel information of high value for epidemiological assessment. During an ASF outbreak hunting effort will change dramatically and will take a few years to return to similar pre‐ASF levels, so post‐ASF estimates of density would be limited to areas where ASF has been present for a while. However, there will be relatively limited effect on sighting data as these rely on a number of different actors, many of whom may be expected to return to normal activities relatively soon after ASF arrives. Thus, relative post‐ASF wild boar density may be more reliable in the short term. These relative post‐ASF densities were calculated but with the limited sighting data available at the chosen locations the uncertainty was high. We advocate for the developing this nework of wildlife monitoring across Europe, and in general, harmioized wildlife monitoring programs, ensuring standardisation and consistency in the data generated and collected, which is essential for assessing management and risks related not only to ASF but other wildlife diseases.

A Numerical Study of the High Latitudinal Ion‐Neutral Coupling Time Scale Under Disturbed Conditions

AbstractWhen solar wind and interplanetary magnetic field (IMF) disturb, thermospheric winds change accordingly. Among the momentum forces driving high‐latitude thermospheric winds, ion drag is supposed to greatly affect wind variations through ion‐neutral coupling when abrupt and strong changes in ion drifts occur. However, due to the great inertia of thermospheric winds it needs a certain period of time for the wind changes to be prominent both in speed and direction. How long the neutral winds take to change from one steady state to another through the ion‐neutral coupling process is currently still a controversial issue. In this paper, we examine the high latitudinal ion‐neutral coupling time scale based on the Thermosphere Ionosphere Electrodynamics General Circulation Model simulations, which can determine whether wind variations are dominantly driven by ion drag by analyzing the relative contribution of each momentum force. It is found that the spatial variation of ion‐neutral coupling time scale is primarily determined by local electron density, but also varies with neutral density and ion‐neutral collision frequency. Simulations during periods of medium solar activity at ∼250 km altitude show that the ion drag‐dominated region is generally located at the dayside convection inverse boundary and the coupling time scale (e‐folding time) is ∼1 hr when IMF By is the dominant component of the IMF and changes direction. Meanwhile, the southward component of IMF Bz enlarges the ion drag‐dominated region. When IMF Bz is southward with a large magnitude, ion drag‐dominated region is primarily located in the nightside auroral oval with ∼2 hr coupling time scale.

Copper silicate nanoneedle arrays on reduced graphene oxide like “shelter forest” guiding Zn gradient deposition

With the sustainable and efficient development of aqueous zinc ion batteries (AZIBs), the research on addressing the issues of the adaptability and durability of zinc anodes has been hot-topic and is still of great challenge. In this work, inspired by the sand treatment and afforestation of the Gobi Beach in Northwest China to ameliorate the problem of wind and sand encroachment, we propose a material with a morphology similar to that of a “shelter forest”, CuSiO3 nanoneedles arrays grown on both sides of reduced graphene oxide (rGO@CuSi), as a coating layer on the zinc metal surface to guide Zn gradient deposition. The presence of rGO improves the electrical conductivity of CuSiO3, and the finite element simulation of the electric field and Zn2+ concentration proves that the electric field distribution can be effectively homogenized and the local current density can be reduced for the rGO@CuSi-Zn electrode with the surface presenting the shape of a protective forest. This is due to the abundant pores between the nano-needle array structures on the surface of the electrode, which provides high electron and ion transport paths, and are conducive to achieve uniform Zn deposition, like the principle of wind-sand stabilization by protective forest. Both electrochemical experiments and density functional theory calculations show that the negatively charged surface of rGO@CuSi with good Zn affinity is more capable of guiding Zn2+ transport. Thanks to its inherent material and structural characteristics, the rGO@CuSi-Zn anode has a high specific capacity and good cycling stability. This study provides an insight for interface engineering like protective forest to accelerate the commercialization of high-performance Zn-based batteries.

Ion-Selective Transport Promotion Enabled by Angstrom-Scale Nanochannels in Dendrimer-Assembled Polyamide Nanofilm for Efficient Electrodialysis.

The ion permeability and selectivity of membranes are crucial in nanofluidic behavior, impacting industries ranging from traditional to advanced manufacturing. Herein, we demonstrate the engineering of ion-conductive membranes featuring angstrom-scale ion-transport channels by introducing ionic polyamidoamine (PAMAM) dendrimers for ion separation. The exterior quaternary ammonium-rich structure contributes to significant electrostatic charge exclusion due to enhanced local charge density; the interior protoplasmic channels of PAMAM dendrimer are assembled to provide additional degrees of free volume. This facilitates the monovalent ion transfer while maintaining continuity and efficient ion screening. The dendrimer-assembled hybrid membrane achieves high monovalent ion permeance of 2.81 mol m-2 h-1 (K+), reaching excellent mono/multivalent selectivity up to 20.1 (K+/Mg2+) and surpassing the permselectivities of state-of-the-art membranes. Both experimental results and simulating calculations suggest that the impressive ion selectivity arises from the significant disparity in transport energy barrier between mono/multivalent ions, induced by the "exterior-interior" synergistic effects of bifunctional membrane channels.

Effect of binder content and sintering time on the microstructure and mechanical properties of gradient cemented carbides with Ni binder

Replacement of Co by alternative Ni binder in gradient cemented carbide is an effective way to reduce the health concerns associated with Co powders. In the present work, gradient cemented carbides with different Ni contents and gradient sintering times were prepared by traditional powder metallurgy with a two-step sintering method. The microstructure of cemented carbide including the gradient layer formation was analyzed by XRD, SEM, EDS, TEM, and EBSD. The thickness of the gradient layer is almost proportional to the square root of sintering time, indicating that the gradient layer formation is a diffusion-controlled process. The atomic migration can be accelerated to form a thicker gradient layer with the increase of the binder content. The coherent interface of the Ti(C, N) core-rim structure for the gradient cemented carbides with Ni binder was revealed. With the increase in binder content, the average grain size of the WC phase is increased. The hardness and fracture toughness of the cemented carbides were also studied and analyzed according to the crack propagation behavior and the distribution of dislocation and stress indicated by KAM and GND. The variation of the hardness and the fracture toughness with the sintering time is mainly related to the density and the grain size of hard phases, while the change of the mechanical properties along with the Ni content probably results from the local dislocation density and the stress in the cemented carbides. The cemented carbide can obtain a good combination of hardness and fracture toughness with 10 wt% Ni gradient sintered for 2h.

An energy efficient clustering algorithm based on density and fitness for mobile crowd-sensing network

Mobile crowd-sensing (MCS) is a cutting-edge paradigm that gathers sensory data and generates valuable insights for a multitude of users by utilizing built-in sensors and social applications in mobile devices. This enables a broad spectrum of Internet of Things (IoT) services. We introduce a novel MCS algorithm, Mobile Crowd-sensing Low Energy Clustering (MCLEC), which employs advanced clustering techniques to address issues of data oversampling and energy inefficiency prevalent in MCS networks. MCLEC innovatively adjusts clustering radii based on local node density and the proximity of nodes to the cloud server, thus optimizing data transmission paths and reducing energy consumption. A pivotal enhancement in MCLEC is its cluster head election strategy, which prioritizes leaders based on their energy levels and mobility, thereby enhancing network stability and minimizing the frequency of head re-elections. Our comparisons with established algorithms such as LEACH, LEACH-C, LEACH-M, DEEC, and SEP show that MCLEC significantly improves energy efficiency, reduces server load, and prolongs the lifespan of network nodes, establishing it as an effective solution for IoT applications dependent on MCS. Additionally, MCLEC was compared with other novel clustering algorithms including E-FLZSEPFCH, DFLC, ECPF, ACAWT, UCR, CHEF, and Gupta's algorithm. The results indicate that MCLEC also surpasses most of these algorithms in terms of energy consumption and network lifetime.

Do Varroa destructor (Acari: Varroidae) mite flows between Apis mellifera (Hymenoptera: Apidae) colonies bias colony infestation evaluation for resistance selection?

Since the global invasion of the ectoparasitic mite Varroa destructor (Anderson and Trueman), selection of mite-resistant honey bee (Apis mellifera L.) colonies appears challenging and has to date not broadly reduced colony mortality. The low published estimated heritability values for mite infestation levels could explain the limited genetic progresses obtained so far. We hypothesize that intercolonial horizontal mite transmission could differentially affect the single colonies located in a given apiary and therefore invisibly bias colony infestation phenotypes. This bias may be lower in regions with lower colony density, providing suitable conditions to set up evaluation apiaries. To verify these hypotheses, we monitored mite infestation and reinvasion in experimental colonies, as well as infestationin neighboring colonies belonging to beekeepers in three areas with variable colony densities in the canton of Bern, Switzerland during three consecutive beekeeping seasons. Mite immigration fluctuated between apiaries and years and significantly contributed to colony infestation level. Depending on apiary and year, 17-48% of the mites present in the experimental colonies at the time of the summer oxalic acid final treatment potentially derived from mite immigration that had occurred since mid-spring. Mite immigration was not linked to local colony density or the infestation levels of beekeepers' colonies located within 2 km. Our results do not prove that apiaries for colony evaluation should necessarily be established in areas with low colony density. However, they highlight the high impact of beekeeping management practices on mite colony infestation levels.

3D Porous Fibers with Spatial Traps and Excellent Zn2+ Transport Kinetics Enable Stable Zn‐Based Aqueous Battery

AbstractAdverse side reactions and uncontrolled Zn dendrites growth are the dominant factors that have restricted the application of Zn ion batteries. Herein, a 3D self‐supporting porous carbon fibers (denoted as PCFs) host is developed with “trap” effect to adjust the Zn deposition. The unique open structural design of N‐doped carbon can act as the zincophilic sites to induce uniform deposition and inhibit adverse side reactions. More importantly, the porous hollow PCFs host with “trap” effect can induce Zn deposition in the fiber by adjusting the local electric field and current density, thereby increasing the specific energy density of the battery and inhibiting dendrite growth. In addition, the 3D open frameworks can regulate Zn2+ flux to enable outstanding cycling performance at ultra‐high current densities. As expected, the PCFs framework guarantees the uniform Zn plating and stripping with an outstanding stability over 6000 cycles at the current density of 40 mA cm−2. And the Zn@PCFs||MnO2 full battery shows an excellent lifespan over 1300 cycles at 2000 mA g−1.

Fuel starvation in automotive PEMFC stacks: hydrogen stoichiometry and electric cell-to-cell interaction

Fuel gross starvation (FGS) in a polymer electrolyte membrane fuel cell is an error state, during which the supplied amount of fuel is insufficient to sustain the requested electrical current. A novel experimental technique was developed to intentionally provoke well-controlled fuel starvation situations of one single cell in a multi-cell fuel cell stack. This modification was implemented in a 20 cell stack of automotive-sized cell geometry and carbon composite bipolar plates (BP). The intentional fuel starvation situation was analyzed using a printed circuit board to measure the current density distribution (CDD) in addition to a multipoint cell voltage monitoring (CVM) to measure local cell voltages. The provoked detrimental subsidiary reactions of the anode were found to take place spatially separated from the normal hydrogen oxidation reaction. It was therefore possible to determine and intentionally vary the hydrogen stoichiometry of the fuel starved cell. This error state caused intense distortions of the starved cells CDD and local cell voltages. The maximum difference obtained between outlet and inlet voltage of the modified cell was 1.4 V. Compared to the average current density, a more than 4-times higher maximum local current density was measured in the affected cell. Adjacent cells were also affected via electric cell-to-cell interaction. Characteristic patterns therefore became visible in the cell voltage distribution, measured by the inlet and outlet CVM. The use of carbon composite BP is favoring the occurrence of these patterns due to their relatively high electric sheet resistance. Using the new hardware setup, we could investigate the relation between the hydrogen stoichiometry of the affected cell during FGS and the observed irregular redistribution of current density and local cell voltages.

Mid- to long-term outcomes of proximal humerus fractures treated with open reduction, plate fixation, and iliac bone autograft augmentation.

Open reduction and internal fixation (ORIF) using locking plates is a widely adopted treatment for displaced proximal humerus fractures. Various augmentation techniques have been developed to enhance the stability of plate fixation. Among these, iliac bone autograft is notable for its advantages over allografts, such as ready availability and the elimination of costs and risks associated with disease transmission. Despite its potential benefits, data on the outcomes of iliac bone autograft augmentation (IBAA) are still limited. This study aims to present the mid- to long-term results of treating proximal humerus fractures with ORIF using locking plates and IBAA. The study included 15 patients treated with ORIF and IBAA. We classified fracture patterns using the Neer classification and estimated local bone density via the deltoid tuberosity index. We measured the neck shaft angle (NSA) and humeral head height (HHH) on both immediate postoperative and most recent X-ray images to assess the maintenance of reduction. Clinical outcomes were evaluated using the DASH (Disabilities of the Arm, Shoulder, and Hand) and Constant scores. The average follow-up duration was 59.56 months, ranging from 24 to 93 months. A majority of fractures were classified as four-part (53%). The average immediate and late postoperative NSAs were 132.6±8.19 and 131.6±7.32 degrees, respectively. The average HHH on the immediate postoperative and latest follow-up images were 16.46±6.07 and 15.10±5.34, respectively. None of the patients exhibited any radiological signs of avascular necrosis or loss of reduction at the latest follow-up. The mean postoperative Constant and DASH scores at the latest follow-up were 79.6 and 11.5, respectively. Our findings suggest that ORIF with IBAA is an effective method for managing three- or four-part proximal humerus fractures, yielding excellent outcomes.

Deltoid tuberosity index for proximal humerus fracture: reliability and a predictor of systemic osteoporosis in an Asian population

Our study investigates the reliability of deltoid tuberosity index (DTI) and DTI as a predictor of systemic osteoporosis. The proximal humerus is a common fragility fracture. Current literature suggests that poor local bone density is a significant predictor for surgical fixation failure. The DTI is a simple radiographical tool that is strongly correlates with local humeral BMD aiding surgical planning to consider adjuncts or arthroplasty. However, there is a lack of data in the reliability of assessment of DTI, as well as its correlation to systemic osteoporosis. Respective cohort of patients with PHF treated at a trauma center in Singapore from August 2017 to July 2018 were recruited. Four raters at different levels of varying clinical seniority measured DTI using shoulder radiographs. The dual energy X-ray Absorptiometry (DEXA) bone mineral density (BMD) scan of the hip and lumbar spine was used to diagnose osteoporosis. Area under receiver operating characteristics (AUROC) analysis was conducted to study the diagnostic utility of DTI to predict the risk of osteoporosis. Our study had 87 patients consisting 18 males and 69 females, mainly of Chinese ethnicity (84%) and mean age of 69.7 years (SD 9.52, range 39-92yrs). For assessment of DTI, there was good intra-rater reliability amongst four raters (correlation coefficient range 0.805- 0.843) and excellent inter-rater reliability between al raters (intraclass correlation coefficient = 0.898; 95% CI 0.784-0.950, p-value <0.001). Based on BMD, 55.2% (n=48) were osteoporotic using T-score <-2.5. The highest correlation of DTI to BMD was with femoral neck density at 0.580. The DTI cut-off of 1.6 had the highest combined sensitivity and false positive rate, with area under curve (AUC) = 0.682 (95% CI, 0.564-0.799) for the overall population and AUC =0.706 (95% CI, 0.569-0.842) for patients <75 years. The DTI is a simple and reliable tool, strengthening its applicability in clinical practice to enhance preoperative planning in the surgical fixation of PHF. DTI with a cut off of 1.6 may be helpful tool prompting clinicians to workup and manage underlying osteoporosis.

Modeling of Li-Ion Battery Electrodes Accounting for Microstructure Properties: The Newman’s Model Revisited

The most established lithium-ion battery (LIB) porous-based model is the Newman's pseudo-two-dimensional (P2D) model used as a good trade-off between numerical computational cost and physics precision. However, this model does not resolve the local fluctuations of physical quantities on the microstructure and can give inaccurate results especially at high C-rate. In this work, we revisit the P2D model by applying the method of volume averaging to mass and charge transport equations of LIB microstructure models. The outcome is a non-classical homogenized model where the effective properties do not only depend on geometry, but are shown to be functions of the local current density. The model reduces to the classical P2D at low C-rate, but extends the validity range of the P2D at high C-rate for complex microstructures. Moreover, the new model allows to reconstruct the local fluctuations from the averaged variables, whereas this information is not available from the classical P2D model.

Helical close-packing of anisotropic tubes

Helically close-packed states of filaments are common in natural and engineered material systems, ranging from nanoscopic biomolecules to macroscopic structural components. While the simplest models of helical close-packing, described by the ideal rope model, neglect anisotropy perpendicular to the backbone, physical filaments are often quite far from circular in their cross-section. Here, we consider an anisotropic generalization of the ideal rope model and show that cross-section anisotropy has a strongly non-linear impact on the helical close-packing configurations of helical filaments. We show that the topology and composition of the close-packing landscape depends on the cross-sectional aspect ratio and is characterized by several distinct states of self-contact. We characterize the local density of these distinct states based on the notion of confinement within a ‘virtual’ cylindrical capillary, and show that states of optimal density vary strongly with the degree of anisotropy. While isotropic filaments are densest in a straight configuration, any measure of anisotropy leads to helicity of the maximal density state. We show the maximally dense states exhibit a sequence of transitions in helical geometry and cross-sectional tilt with increasing anisotropy, from spiral tape to spiral screw packings. Furthermore, we show that maximal capillary density saturates in a lower bound for volume fraction of π/4 in the large-anisotropy, spiral-screw limit. While cross-sectional anisotropy is well-known to impact the mechanical properties of filaments, our study shows its strong effects to shape the configuration space and packing efficiency of this elementary material motif.

A Comprehensive Density Functional Theory Analysis on Structural, Electronic, and Optical Properties of BiOF

Based on density functional theory (DFT), the electronic, structural, and optical properties of bismuth oxyfluoride (BiOF) are investigated by using various exchange–correlation functionals. The local density approximation (LDA), Perdew-Burke-Ernzerhof generalized gradient approximation (PBE-GGA), Perdew-Burke-Ernzerhof generalized gradient approximation for solids (PBEsol), and Wu-Cohen (WC) functionals are implemented in Wien2k software. Modified Becke-Johnson (mBJ) and unmodified Becke-Johnson (umBJ) potentials are also applied to obtain an enhanced band gap. Spin–orbit coupling effect (SOC) is also taken into consideration due to the heavy Bi atom. When employing the PBE+umBJ potential, BiOF exhibits the most enhanced band gap energy, with a direct band gap energy of 3.72 eV. Moreover, optical properties such as dielectric functions, absorption coefficients, and optical conductivities are also calculated for photon energies up to ̴̴ 14 eV. In comparison to other available theoretical and experimental findings, the calculated results are in good agreement.

The adsorption of CO and CO2 gases on (6,4) and (7,7) AlN nanotubes for enhanced sensor applications: A DFT approach

We perform total energy and electronic structure calculations to analyse the adsorption of Carbon dioxide and Carbon monoxide molecules on Si-doped single-walled aluminium nitride nanotubes (AlNNTs) of (7,7) and (6,4) chirality using local density approximation (LDA) in the framework of density functional theory (DFT). The results reveal that doped Si-(7,7) AlNNT system show highest sensing potential of approximately 80% of gas adsorption for both CO2 and CO. However, Si-(6,4) indicates a recovery time of 1.68 sec, and 6-fold better compared with Si-(7,7). We find that pristine (6,4) adsorbs both gases with longer recovery times, making it unsuitable as gases sensor and suggest that strong bonding exist between them making it difficult to dissociate. These findings demonstrate potential application of Si-doped aluminium nitride nanotubes as highly effective sensor for detecting CO2 and CO greenhouse gases and paving the way for the development of advance sensing technologies at the nanoscale.

The hierarchical cosmic web and assembly bias

Accurate modeling of galaxy distributions is paramount for cosmological analysis using galaxy redshift surveys. However, this endeavor is often hindered by the computational complexity of resolving the dark matter halos that host these galaxies. To address this challenge, we propose the development of effective assembly bias models down to small scales, i.e., going beyond the local density dependence capturing non-local cosmic evolution. We introduce a hierarchical cosmic web classification that indirectly captures up to third-order long- and short-range non-local bias terms. This classification system also enables us to maintain positive definite parametric bias expansions. Specifically, we subdivide the traditional cosmic web classification, which is based on the eigenvalues of the tidal field tensor, with an additional classification based on the Hessian matrix of the negative density contrast. We obtain the large-scale dark matter field on a mesh with ~3.9 h -1 Mpc cell side resolution through Augmented Lagrangian Perturbation Theory. To assess the effectiveness of our model, we conduct tests using a reference halo catalogue extracted from the UNIT project simulation, which was run within a cubical volume of 1 h -1 Gpc side. The resulting mock halo catalogs, generated through our approach, exhibit a high level of accuracy in terms of the one-, two- and three-point statistics. They reproduce the reference power-spectrum within better than 2 percent accuracy up to wavenumbers k ~ 0.8 h Mpc-1 and provide accurate bispectra within the scales that are crucial for cosmological analysis. This effective bias approach provides a forward model appropriate for field-level cosmological inference and holds significant potential for facilitating cosmological analysis of galaxy redshift surveys, particularly in the context of projects such as DESI, EUCLID, and LSST.

Structural, electronic, mechanical, thermodynamic and optical properties of oxide perovskite BeZrO3: a DFT study

The geometrical, electronic, mechanical, thermodynamic, and optical aspects of BeZrO3 crystal have been investigated employing Generalized Gradient Approximation (GGA) with Perdew–Burke–Ernzerhof (PBE), Revised Perdew–Burke–Ernzerhof (RPBE), Local density approximation (LDA) with Ceperley Alder and Perdew Zunger (CA-PZ) techniques under density functional theory. The band gap values of BeZrO3 have been reported to be 0.603 eV, 0.623 eV, 0.614 eV and 2.20 eV respectively in PBE, RPBE, LDA and Becke, 3-parameter, Lee–Yang–Parr (B3LYP) methods. Total and partial density analysis was used to determine atomic orbital nature of the Be, Zr, and O atoms in BeZrO3. By estimating the Mulliken population charge, the bonding characteristics of BeZrO3 have been elucidated. Using the Born mechanical stability criterion, it was determined that BeZrO3 crystal is mechanically stable. The evaluation of ductile strength was expressed by using Poisson and Pugh’s critical ratios, revealing the inherent elastic anisotropy features. The optical characteristics have been conducted using various methodologies, concluded that BeZrO3 exhibits remarkable efficacy in absorbing ultraviolet and visible light.

Density peaks clustering based on Gaussian fuzzy neighborhood with noise parameter

Density peak clustering (DPC) is an effective clustering method known for its robustness, non-iterative nature, and hybrid approach. However, it is not without limitations: (a) the determination of the cutoff distance (dc) relies on human experience, which can significantly impact the clustering outcome; (b) DPC does not take into account the local structure of the data when computing local densities; (c) it employs a crisp kernel for density computation; (d) the performance of DPC is affected by chain reactions; and (e) DPC often struggles to handle noisy data. In order to address these limitations, this paper proposes a novel approach called DPC based on Gaussian fuzzy neighborhood with noise parameter (DPC-GFNN). The proposed method leverages a Gaussian fuzzy kernel to enhance the separation between clusters and mitigates the influence of outliers through an adjustable noise parameter (λ). DPC-GFNN utilizes a k-nearest neighbor graph based on density to label highly dense regions. This technique effectively avoids chain reactions by assigning accurate labels to points in border areas, enabling proper clustering of data with diverse shapes and densities. To evaluate the effectiveness of DPC-GFNN, a series of experiments are conducted on both real-world and synthetic datasets. The experimental results demonstrate that DPC-GFNN exhibits superior robustness and clustering accuracy compared to other modified variants of DPC including DPC based on k-nearest neighbors (DPC-KNN), improved DPC (IDPC), DPC based on density backbone and fuzzy neighborhood (DPC-DBFN), and DPC based on fuzzy weighted k-nearest neighbors (FKNN).