Size Dependence Research Articles

Assessing the impact of hard data patterns on Bayesian Maximum Entropy: a simulation study.

This study empirically tested the robustness of Bayesian Maximum Entropy (BME) in predicting spatiotemporal data, with an emphasis on skewness, sample size, and spatial dependency level. Simulated data, both Gaussian and non-Gaussian, were generated using the unconditional sequential simulation method, with sample sizes ranging from 100 to 500 at the interval length of 50 and varying skewness (0, 1, 3, 6 and 9) and spatial dependency levels (weak, moderate, and strong). Findings revealed sample size variations and spatial dependence levels did not significantly influence BME prediction's Mean Square Error (MSE) and bias. While skewness significantly impacted MSE (p-value < 0.001), bias remained unaffected. Moreover, skewness and spatial dependence interactions affected both MSE and bias. Despite this, BME proved robust to sample size and skewness, demonstrating a negligible MSE on the graphical plot (heatmap).

On the Effect of Randomly Oriented Grain Growth on the Structure of Aluminum Thin Films Deposited via Magnetron Sputtering

The microstructure of aluminum thin films, including the grain morphology and surface roughness, are key parameters for improving the thermal or electrical properties and optical reflectance of films. The first step in optimizing these parameters is a thorough understanding of the grain growth mechanisms and film structure. To investigate these issues, thin aluminum films with thicknesses ranging from 25 to 280 nm were coated on SiOx/Si substrates at ambient temperature under high-vacuum conditions and a low argon pressure of 3 × 10−3 mbar (0.3 Pa) using the radio frequency magnetron sputtering method. Quantitative analyses of the surface roughness and nanograin characteristics were conducted using atomic force microscopy (AFM), transmission electron microscopy (TEM), and X-ray diffraction. Changes in specular reflectance were measured using ultraviolet–visible and near-infrared spectroscopy. The low roughness values obtained from the AFM images resulted in high film reflectivity, even for thicker films. TEM and AFM results indicate monomodal, randomly oriented grain growth without a distinct columnar or spherical morphology. Using TEM cross-sectional images and the dependence of the grain size on the film thickness, we propose a grain growth mechanism based on the diffusion mobility of aluminum atoms through grain boundaries.

Exploring the Dependency of Order Size in Integrated Inventory Model Under Partial Trade Credit and All Unit Discounts with Capacity Constraints

Exploring the Dependency of Order Size in Integrated Inventory Model Under Partial Trade Credit and All Unit Discounts with Capacity Constraints

An electrochemiluminescence sensor for ultrasensitive determination of tyrosine based on ceria nanomaterial as a novel luminophor

BackgroudRecently, optical nanomaterials have attracted much attention in the field of electrochemiluminescence (ECL). Nanostructured ceria possessed unique optical properties, and it's always used for constructing ECL sensor as catalyst for improving sensing performance, while the ECL property of ceria is rarely studied. In fact, it could be the potential candidate for applying in ECL sensors based on size and shape dependency optical property caused by the quantum scale effects. Therefore, new simple and efficient ceria nanomaterial used as luminophor for constructing the ECL sensor have aroused more research interest and motivation. (91 words). ResultsIn the work, three kinds of nanostructured ceria, ceria nano-cube (CeO2-NC), ceria nano-rods (CeO2-NR) and ceria nano-particle (CeO2-NP), have been prepared by hydrothermal method, and CeO2-NC with the less oxygen vacancy has the highest ECL signal. Moreover, how the shape affects the ECL property was investigated in detail, especially the oxygen vacancy on the surface of the ceria. The less of oxygen vacancy content of CeO2 nanomaterials is more favorable the ECL reaction. Furthermore, a novel ECL sensor was constructed based on reduced graphene oxide (rGO), Au nano-particle (AuNPs) and CeO2-NC for Tyrosine (Tyr) determination owing to the electron transform between the luminous of ceria and Tyr resulting in the cathodic ECL intensity quenched correspondingly, and it has possessed excellent sensing performance with a linear range of 0.005–20 nmol/L and the limit of detection (LOD) value of 1.7 fmol/L (141 words) Significance and noveltyThe proposed method demonstrated excellent selectivity and ultra-sensitivity toward Tyr, which had been used for the determination of Tyr in human serum successfully, possessing outstanding analytical performance. Therefore, nanostructured ceria is a new category of efficient and promising luminophore, which would open new avenues for the potential application in the field of ECL sensing for clinical diagnosis. (57 words).

Thermal conductivity of WC: Microstructural design driven by first-principles simulations

The relationships between the microstructure and the thermal conductivity of binderless WC have been quantified, considering crystal orientation, isotopic abundance, porosity, and grain size. A significantly higher conductivity is predicted in the out-of-plane (c-axis) direction vs. the in-plane (a-axis) direction, using first principles simulations. Isotopic enrichment of the tungsten sublattice is predicted to increase conductivity, e.g., by a factor of 4–5 in the absence of boundary scattering. The results suggest that for an isotopically pure single crystal a thermal conductivity exceeding 1000 W m−1 K−1 may be achievable normal to the basal plane. The conductivity of samples with various porosities could be well fit by a minimum surface area (exponential) model, with a porosity exponent of b = 4.4. Experiment and simulation show a strong grain size dependence to conductivity below 1 µm, with a saturation beyond ∼10 µm. The experimental plateau values for κ were ∼45 % lower than those of the simulations due to deviations from perfect stoichiometry. We also find a higher scattering coefficient in the experiments, likely due to effects of grain size distribution and elongation. Our study clarifies the physical origin of disagreeing literature reports as being predominantly due to grain boundary scattering and enables microstructural design for thermally demanding environments.

Size and shape dependence of hydrogen-induced phase transformation and sorption hysteresis in palladium nanoparticles

Abstract Phase transitions of metals in hydrogen environments are critically important for applications in energy storage, catalysis, and sensing. Nanostructured metallic particles can lead to faster charging and discharging kinetics, increased lifespan, and enhanced catalytic activities. However, establishing a direct causal link between nanoparticle structure and function remains challenging. In this work, we establish a computational framework to explore the atomic configuration of a metal-hydrogen (M-H) system when in equilibrium with a H environment. This approach combines Diffusive Molecular Dynamics with an iteration strategy, aiming to minimize the system's free energy and ensure uniform chemical potential across the system that matches that of the H environment. Applying this framework, we investigate H chemical potential-composition isotherms during the hydrogenation and dehydrogenation of palladium nanoparticles, ranging in size from $3.9$ nm to $15.6$ nm and featuring various shapes including cube, rhombic dodecahedron, octahedron, and sphere. Our findings reveal an abrupt phase transformation in all examined particles during both H loading and unloading processes, accompanied by a distinct hysteresis gap between absorption and desorption chemical potentials. Notably, as particle size increases, absorption chemical potential rises while desorption chemical potential declines, consequently widening the hysteresis gap across all shapes. Regarding shape effects, we observe that, at a given size, cubic particles exhibit the lowest absorption chemical potentials during H loading, whereas octahedral particles demonstrate the highest. Moreover, octahedral particles also exhibit the highest desorption chemical potentials during H unloading. These size and shape effects are elucidated by statistics of atomic volumetric strains resulting from specific facet orientations and inhomogeneous H distributions. Prior to phase transformation in absorption, a H-rich surface shell induces lattice expansion in the H-poor core, while before phase transformation in desorption, surface stress promotes lattice compression in the H-rich core. The magnitude of the volumetric strains correlates well with the size and shape dependence, underlining their pivotal role in the observed phenomena.

Equation of State for Nanopores and Shale: Pore Size–Dependent Acentric Factor

Nanopores pose a challenge to phase-behavior modeling when using the equation of state (EOS), and common methods do not capture their vapor pressure or become difficult to implement because they require additional tuning parameters. This study focuses on improving the vapor-pressure prediction of EOS in nanopores by proposing a pore size–dependent acentric factor (ACF). It determines the ACF from experimental data and implements it in EOS along with critical pressure and temperature. The proposed approach is then applied to the vapor-pressure measurements of nitrogen, argon, oxygen, methane, and ethane in pores ranging from 3.5 nm to 8.1 nm. The results show that the ACF in nanopores increases as the pore size decreases, and the degree of size dependency varies across different pure components. The results also demonstrate that the proposed approach enables EOS predictions to match the measurements with good accuracy. This study quantifies the effects of pore size on the ACF for the first time and presents simple correlations for estimating the ACF when the pore radius is smaller than or equal to 10 nm. The proposed approach simplifies the application of EOS in nanopores and unconventional hydrocarbon reservoirs.

Effect of grain size on tensile deformation behavior of nano-polycrystalline Al and Al–Mg alloys with grain boundary segregation of Mg

Mg is easily segregated to the grain boundary of the Al–Mg alloy, which affects the mechanical properties of the alloy. In order to reveal the role of Mg element at grain boundaries in Al–Mg alloys, molecular dynamics simulation was used to study the tensile deformation behavior of nano-polycrystalline Al and Al–Mg alloys with different grain sizes. The results show that the elastic modulus and tensile strength of Al and Al–Mg alloys have a clear grain size dependence. The critical grain size at which the elastic modulus decreases as the grain size decreases is independent of Mg. As the Mg content increases to 3 at. %, the critical grain size for the transition from the Hall-Petch relationship to the inverse Hall-Petch relationship increases. The appropriate content of Mg segregation at the grain boundary can increase the elastic modulus, strength and plasticity of the alloy, and inhibit the grain boundary cracking. This result provides important theoretical support for the composition design and microstructure regulation of high-performance Al–Mg alloys.

Long‐run Effects of Austerity: An Analysis of Size Dependence and Persistence in Fiscal Multipliers

Long‐run Effects of Austerity: An Analysis of Size Dependence and Persistence in Fiscal Multipliers

Effect of grain size on mechanical properties and aging of yttria-stabilized tetragonal zirconia polycrystal fabricated by stereolithography-based additive manufacturing

The objective of this investigation was to comprehensively assess the impact of grain size on the mechanical properties and low-temperature degradation (LTD) of yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP) fabricated by stereolithography-based additive manufacturing at the submicron scale. Four 3Y-TZP ceramics with high relative density (>98%), ranging in grain size from 0.2 μm to 1 μm, were successfully prepared and validated for studying mechanical properties (including Vickers hardness, fracture toughness, and flexural strength) as well as LTD progression. This study elucidates the mechanical behavior of zirconia ceramics at the submicron scale, focusing on fracture micromechanisms and the grain size dependence of transformation toughening. Additionally, it examines the influence of grain size on the hydrothermal aging behavior of zirconia ceramics at the submicron scale using Raman spectroscopy.

Impact of grain size on the performance of WSe2 FETs revealed by first-principles calculations

We theoretically investigate the grain size dependence of the mobility of WSe2 FETs, and the experimental results which have been recently reported. A larger grain size (LG) WSe2 has been modeled by a single monolayer WSe2 of infinite length. We model a smaller grain size (SG) WSe2 as a partial monolayer of WSe2 with a zigzag edge WSe2 nanoribbon. Our results show that the step edges of the partial monolayer WSe2 function as electron traps. Moreover, the effective mass of SG WSe2 appears to be much larger than that of LG WSe2 because of hybridization with gap states originating from step edges at the conduction band minimum. These results coincide with recent experiments that show that the on-currents of the SG WSe2 are much lower than those of the LG WSe2. Hence, our calculated results indicate that LG fabrication is essential for advanced large-scale integration (LSI) using WSe2 FETs.

Exceptional strength-ductility synergy in the novel metastable FeCoCrNiVSi high-entropy alloys via tuning the grain size dependency of the transformation-induced plasticity effect

In-depth knowledge of the coupling between grain refinement and the transformation-induced plasticity (TRIP) effect in metastable alloys is a viable approach for the improvement of strength-ductility synergy, which needs systematic research with consideration of commercial austenitic stainless steels and novel high-entropy alloys (HEAs). Accordingly, in the present work, two Si-containing metastable HEAs in the Fe47Co30Cr10Ni5V8-xSix system (x = 3 and 6 at.%) were designed, and the TRIP-assisted AISI 304L stainless steel was also considered for comparison. The alloys were processed by cold rolling and annealing to obtain different grain sizes. Reducing the stacking fault energy (SFE) through adjusting chemical composition contributes to minimizing the detrimental effect of grain refinement on the ductility of TRIP alloys, while extremely low SFE must be avoided owing to the fast kinetics of deformation-induced martensitic phase transformation, which leads to the deterioration of ductility. In contrast to AISI 304L stainless steel, a strong TRIP effect was maintained upon grain refinement in the Fe47Co30Cr10Ni5V2Si6 HEA due to the remaining apparent SFE in the appropriate TRIP range. The tuned kinetics of martensitic transformation was found to be responsible for the exceptional ductility (∼65%) of Fe47Co30Cr10Ni5V2Si6 HEA at an ultrahigh tensile strength of 1250 MPa. Therefore, considering the identical trend of SFE with grain size, an appropriate initial SFE value is important for tuning the grain size dependency of the TRIP effect. Moreover, the ultrahigh strength was attributed to the high volume fraction of α΄-martensite as well as the high strength of the martensite phase due to the high Si content. Accordingly, for achieving strong-yet-ductile HEAs, a high Si content is recommended to benefit from solid solution strengthening in the martensite phase, a specially-designed chemical composition is needed for attaining a high volume fraction of α΄-martensite, and SFE should be in a desirable range to tune the kinetics of martensitic phase transformation.

Grain size dependent deformation microstructure evolution and work-hardening in CoCrNi medium entropy alloy

This study clarified the grain size dependence of the deformation microstructure evolution and work-hardening behavior in CoCrNi medium entropy alloy. We fabricated fully recrystallized specimens with coarse-grained (CG) and ultrafine-grained (UFG) specimens by severe plastic deformation and subsequent annealing processes. Tensile deformation was applied to the specimens at room temperature. The UFG specimen exhibited both high strength and high ductility compared to conventional UFG metals due to the high work-hardening ability. In the CG specimen, three distinct types of deformation microstructures consisting of dislocations and deformation twins developed depending on grain orientations, similar to the single-crystalline specimens. In the UFG specimen, widely extended stacking faults and randomly-tangled dislocations were found to coexist in most grains. Deformation twins were found to nucleate without evidence of dislocation reactions regardless of grain orientations, implying abnormal nucleation mechanisms of deformation twins in the UFG specimen. Dislocation densities quantified by in-situ synchrotron XRD measurements during tensile deformation were higher in the UFG specimen than those in the CG specimen and conventional UFG metals. Our analysis showed that the work-hardening behavior of the specimens was primarily controlled by increases in dislocation density as well as the introduction of planar defects during deformation. Through comparisons with the CG specimen and conventional UFG metals, we concluded that the excellent work-hardening ability of the UFG specimen was mainly due to the evolution of unique deformation microstructures and rapid increase in dislocation density, which could be due to inhibited dynamic recovery in the MEA.

Design and Control of Polymeric Network Architectures Based on Network Dimension Theory

AbstractA new design policy to synthesize nanogel molecules having desired dimensions under unperturbed state is proposed. Miniemulsion copolymerization of vinyl and divinyl monomers, both conventional free‐radical polymerization and ideal living polymerization, is used to illustrate the method. For the network formation dynamics, the newly proposed model that takes into account the size and structure dependence of cross‐linking/cyclization reactions is employed. The master curve relationship that indicates the maximum average dimensions for randomly cross‐linked networks is used as a guideline and the network dimension is controlled by the magnitude of network maturity index NMI, which is the average number of cycle rank per primary chain. By appropriately sizing the NMI, it is possible to synthesize network polymers with dimensions equal to or greater than the maximum dimensions achievable with a homogeneous, randomly cross‐linked network polymer of the same cycle rank and molecular weight. The current strategy of designing and controlling 3D size is applicable regardless of the reaction mechanism of network formation and will also be applied to the synthesis of macro‐gels.

Determination of the particle size distribution of cube-shaped colloidal perovskite quantum dots from photoluminescence spectra: A combined theoretical-experimental approach.

A theoretical-experimental approach is proposed to convert the photoluminescence spectra of colloidal perovskite quantum dot ensembles into accurate estimates for their intrinsic particle size distribution functions. Two main problems were addressed and properly correlated: the size dependence of the first excitonic transition in a single cube-shaped quantum dot and the inhomogeneous broadening of the fluorescence line shape due to the size nonuniformity of the chemically prepared quantum dot suspension in addition to the single-dot homogeneous broadening. By applying the reported methodology to CsPbBr3 quantum dot samples belonging to the strong and intermediate confinement regimes, the calculated size distributions exhibited close agreement with those obtained from transmission electron microscopy, with precise estimates for the average particle size and standard deviation. Specifically for strongly confined ultrasmall CsPbBr3 quantum dots, the presented spectroscopic model for size distribution computation is based on a new analytical expression for the size-dependent bandgap, which was developed within the framework of the finite-depth square-well effective mass approximation accounting for band nonparabolicity effects. Such a quantum mechanical approach correctly predicts the expected transition to the intermediate confinement regime in sufficiently large quantum dots, which are traditionally described by the well-known bandgap equation in the infinite potential barrier limit with a spatially correlated electron-hole wavefunction and nonparabolic carrier effective masses. The proposed calculation scheme originates from general theoretical considerations so that it can be readily adapted to semiconductor quantum dots of many other systems, from all inorganic metal halides to hybrid perovskite materials, regardless of the adopted chemical synthesis route.

An Increase in The Cross-Section of Two-Photon Absorption of Styrene Dye in Supramolecular Complexes with Cucurbituriles

Two-photon absorption cross sections of aqueous solutions of the styryl dye trans-4-[4-(dimethylamino)styryl]-1-methylpyridinium iodide (DASPI) and its inclusion complexes with cucurbit[n]urils (CB[n] n = 6–8) were measured using fluorescence spectroscopy. A nonmonotonic dependence of the cross-section size on the excitation wavelength and on the cavitand cavity size was found. Compared with a free dye, a sevenfold increase in the two-photon absorption cross section was observed in DASPI inclusion complexes with CB[8] at an excitation wavelength of 980 nm.

Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization.

Precise size and shape control in nanocrystal synthesis is essential for utilizing nanocrystals in various industrial applications, such as catalysis, sensing, and energy conversion. However, traditional ensemble measurements often overlook the subtle size and shape distributions of individual nanocrystals, hindering the establishment of robust structure-property relationships. In this study, we uncover intricate shape evolutions and growth mechanisms in Co3O4 nanocrystal synthesis at a subnanometer scale, enabled by deep-learning-assisted statistical characterization. By first controlling synthetic parameters such as cobalt precursor concentration and water amount then using high resolution electron microscopy imaging to identify the geometric features of individual nanocrystals, this study provides insights into the interplay between synthesis conditions and the size-dependent shape evolution in colloidal nanocrystals. Utilizing population-wide imaging data encompassing over 441,067 nanocrystals, we analyze their characteristics and elucidate previously unobserved size-resolved shape evolution. This high-throughput statistical analysis is essential for representing the entire population accurately and enables the study of the size dependency of growth regimes in shaping nanocrystals. Our findings provide experimental quantification of the growth regime transition based on the size of the crystals, specifically (i) for faceting and (ii) from thermodynamic to kinetic, as evidenced by transitions from convex to concave polyhedral crystals. Additionally, we introduce the concept of an "onset radius," which describes the critical size thresholds at which these transitions occur. This discovery has implications beyond achieving nanocrystals with desired morphology; it enables finely tuned correlation between geometry and material properties, advancing the field of colloidal nanocrystal synthesis and its applications.

Size-dependency and lattice-discreetness effect on fracture toughness in 2D crystals under antiplanar loading

AbstractFracture toughness is the material property characterizing resistance to failure. Predicting its value from the solid structure at the atomistic scale remains elusive, even in the simplest situations of brittle fracture. We report here numerical simulations of crack propagation in two-dimensional fuse networks of different periodic geometries, which are electrical analogs of bidimensional brittle crystals under antiplanar loading. Fracture energy is determined from Griffith’s analysis of energy balance during crack propagation, and fracture toughness is determined from fits of the displacement fields with Williams’ asymptotic solutions. Significant size dependencies are evidenced in small lattices, with fracture energy and fracture toughness both converging algebraically with system size toward well-defined material-constant values in the limit of infinite system size. The convergence speed depends on the loading conditions and is faster when the symmetry of the considered lattice increases. The material constants at infinity obey Irwin’s relation and properly define the material resistance to failure. Their values are approached up to $$\sim 15\%$$ ∼ 15 % using the recent analytical method proposed in Nguyen and Bonamy (Phys Rev Lett 123:205503, 2019). Nevertheless, the deviation remains finite and does not vanish when the system size goes to infinity. We finally show that this deviation is a consequence of the lattice discreetness and decreases when the super-singular terms of Williams’ solutions (absent in a continuum medium but present here due to lattice discreetness) are taken into account.

Edge-state-mediated RKKY coupling in graphene nanoflakes

We investigate the long-range behavior and size dependence of the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction in hexagonal and triangular graphene nanoflakes with zigzag and armchair edges. We employ the tight-binding model with exact diagonalization to calculate the RKKY interaction as a function of the distance between magnetic impurities, nanoflake size, and edge geometry. Our findings demonstrate a strong dependency of the RKKY interaction on edge geometry and flake size, with notable changes in the RKKY interaction strength. We further analyze the influence of structural defects on the interaction strength of exchange interactions.

Understanding the mechanisms of change in social norms around tobacco use: A systematic review and meta-analysis of interventions.

Tobacco use spreads through social networks influencing social norms around tobacco use. However, the social norms scholarship is extremely diverse and occasionally conflicting, complicating efforts to understand how best to leverage social norms to reduce tobacco use. This study systematically reviewed and meta-analyzed this vast terrain by focusing on social norms measurement and mechanism, and intervention effectiveness and modality aimed at changing social norms around tobacco use and actual tobacco use. We searched Scopus, PubMed, PsycInfo, Clinicaltrials.gov, ProQuest Dissertations, the Cochrane Trial Registry, as well as the websites of the Society for Research on Nicotine and Tobacco, the Open Science Framework, medrXiv and the Truth Initiative for experimental and quasi-experimental evaluation studies of interventions designed to shift tobacco use. We included studies written in English from inception to 30 May 2024. We only included studies which noted social norms or social influence as part of the intervention design or set of measured variables. We excluded studies with only one time point, without an intervention being evaluatedand those not published in English. Study screening followed the PRISMA 2020 guidelines, and was conducted by at least two independent reviewers who resolved discrepancies through discussion and consensus. All included studies were analyzed in a narrative synthesis, and those providing sufficient statistics for tobacco and social norms outcomes were included in meta-analyses, which were performed separately for tobacco outcomes and social norms outcomes. Study outcomes were transformed into a standardized mean difference (Hedges' g) and several meta-regressions were fit to explore sources of heterogeneity using a robust variance estimation specification to handle effect size dependency. A total of 95 studies met inclusion criteria for the narrative synthesis, 200 effect sizes from 86 studies were included in the tobacco outcomes meta-analysis, and 66 effect sizes from 29 studies were included in the social norms outcomes meta-analysis. Nearly 90% of included studies were conducted in high-income settings, with the remainder conducted in middle-income settings. No studies were conducted in Latin America or on the African continent. Social norms change interventions had a statistically significant effect on reducing tobacco use and pro-tobacco social normative perceptions [g = 0.233, 95% confidence interval (CI) = 0.166, 0.301, P < 0.001 and g = 0.292, 95% CI = 0.090, 0.494, P = 0.007, respectively]. Interventions were commonly conducted among schoolchildren in classrooms through multicomponent education sessions, often coupled with regular 'booster' sessions over time. Among adult populations, motivational interviewing and other counselling approaches were used in some cases, and few interventions leveraged digital technologies to change social norms. Social norms change interventions appear to be effective for reducing tobacco use and pro-tobacco social normative perceptions. In particular, leveraging role models appears to be the most effective social norms change mechanisms for tobacco control.