Random Structure Research Articles

Various Grids in Moiré Measurements

The moiré effect is typically observed in regular periodic structures and sometimes in random (aperiodic) structures. However, currently, only regular graphical objects are used in measurements. We propose using graphical objects that are not regular but not entirely random and that resemble rows, such as grids of dotted lines or matrixes of dots. The moiré effect in such objects may become similar to the moiré effect in regular graphical objects if a relatively simple modification of the image processing algorithm is applied. We demonstrated that the results of measurements with five different graphical objects arranged in rows (including text) are similar. Using such objects can be helpful for practical moiré measurements.

Research on 3D humanoid robot pose estimation based on HRNet-Epipolar and CRF robot model by multiple view

Purpose This paper aims to present an unmarked method including entire two-dimensional (2D) and three-dimensional (3D) methods to recover absolute 3D humanoid robot poses from multiview images. Design/methodology/approach The method consists of two separate steps: estimating the 2D poses in multiview images and recovering the 3D poses from the multiview 2D heatmaps. The 2D one is conducted by High-Resolution Net with Epipolar (HRNet-Epipolar), and the Conditional Random Fields Humanoid Robot Pictorial Structure Model (CRF Robot Model) is proposed to recover 3D poses. Findings The performance of the algorithm is validated by experiments developed on data sets captured by four RGB cameras in Qualisys system. It illustrates that the algorithm has higher Mean Per Joint Position Error than Direct Linear Transformation and Recursive Pictorial Structure Model algorithms when estimating 14 joints of the humanoid robot. Originality/value A new unmarked method is proposed for 3D humanoid robot pose estimation. Experimental results show enhanced absolute accuracy, which holds important theoretical significance and application value for humanoid robot pose estimation and motion performance testing.

Enhancing Uniformity, Read Voltage Margin, and Retention in Three-Dimensional and Self-Rectifying Vertical Pt/Ta2O5/Al2O3/TiN Memristors.

This study introduces a Ta2O5-based self-rectifying memristor (SRM) with an Al2O3 interfacial layer adopted to improve switching uniformity, read voltage margin, and long-term retention. The Pt/Ta2O5/Al2O3/TiN (PTAT) device exhibits a 105 rectification ratio, 104 on/off ratio, 2 × 106 endurance, and retention of 104 s at 150 °C. A 3-layer 4 × 4 vertical resistive random access memory structure exhibits uniform switching parameters. The coefficient of variation (CV) for device-to-device measurements is 0.23 for the low resistance state (LRS) and 0.22 for the high resistance state (HRS), while for cycle-to-cycle measurements, the CV is 0.38 for the LRS and 0.11 for the HRS. Finally, the present study demonstrates the superior performance of the PTAT devices in the context of hardware-aware training for a fully connected neural network implementation. These advancements position the PTAT device as a promising candidate for high-density three-dimensional storage class memory and low-power neural networks, offering the consistent performance and reliability necessary for future high-density storage applications.

Enzymatic production and physicochemical and functional properties of sorghum protein isolates.

Grain sorghum has emerged as a promising source for producing alternative proteins, yet current extraction methods lack efficiency. In this study, a novel enzymatic approach using α-amylase and cellulase on sorghum materials was developed to address this challenge. Comparisons were made among the proteins isolated from dry-milled sorghum flours, wet-milled sorghum gluten meals, and sorghum dried distiller's grains (DDG). Remarkably, proteins obtained from sorghum gluten meals demonstrated the highest protein purity (83-85 %) and recovery rate (92-93 %), followed by those from sorghum flour (purity 75-76 %) and DDG (purity 45-50 %). Physicochemical properties and functionalities of the isolated sorghum proteins were analyzed and compared with common commercial plant proteins (e.g., soy protein isolate, pea protein isolate, and wheat gluten). Sorghum proteins exhibited higher levels of crude fat content, α-helix, and random coil structures, along with higher surface hydrophobicity and oil holding capacity (OHC) compared to the commercial plant protein isolates. Notably, proteins extracted from sorghum flours displayed slightly higher α-helix and random coil structures, total sulfhydryl content, water holding capacity (WHC), OHC, and protein digestibility compared to proteins isolated from sorghum gluten meals. Overall, this study demonstrates that enzymatic processing is feasible in producing sorghum proteins and provides insights into their basic properties and functionalities.

Data-driven prediction of higher-order structure in carbon nanotube films for high thermoelectric power factor

We optimized the higher-order structures and semiconducting purity of single-walled carbon nanotubes (SWCNTs) to enhance the thermoelectric power factor PF by combining the thermoelectric random stick network (TE-RSN) method and a genetic algorithm. The PF of the optimized films was increased approximately fivefold for initial random structures. In addition, while the random structures showed the maximum PF when the ratio of semiconducting to metallic SWCNTs R s exceeded 0.98, the optimized structures converged to an R s of approximately 0.9. The optimized structures exhibited an increased local density and the peak of alignment angle distribution, leading to an increase in both the electrical conductivity and the Seebeck coefficient. We interpreted the increase in the Seebeck coefficient using a serial model. The results indicated that the reduction in the number of contacts within the paths and the subsequent increase in temperature difference on semiconducting SWCNTs led to the increase in the Seebeck coefficient.

Small sample adjustment for inference without assuming orthogonality in a mixed model for repeated measures analysis

ABSTRACT The mixed model for repeated measures (MMRM) analysis is sometimes used as a primary statistical analysis for a longitudinal randomized clinical trial. When the MMRM analysis is implemented in ordinary statistical software, the standard error of the treatment effect is estimated by assuming orthogonality between the fixed effects and covariance parameters, based on the characteristics of the normal distribution. However, orthogonality does not hold unless the normality assumption of the error distribution holds, and/or the missing data are derived from the missing completely at random structure. Therefore, assuming orthogonality in the MMRM analysis is not preferable. However, without the assumption of orthogonality, the small-sample bias in the standard error of the treatment effect is significant. Nonetheless, there is no method to improve small-sample performance. Furthermore, there is no software that can easily implement inferences on treatment effects without assuming orthogonality. Hence, we propose two small-sample adjustment methods inflating standard errors that are reasonable in ideal situations and achieve empirical conservatism even in general situations. We also provide an R package to implement these inference processes. The simulation results show that one of the proposed small-sample adjustment methods performs particularly well in terms of underestimation bias of standard errors; consequently, the proposed method is recommended. When using the MMRM analysis, our proposed method is recommended if the sample size is not large and between-group heteroscedasticity is expected.

High speed impact induced dehydrogenation of titanium hydride and formation of cellular structure via cold spray

In this study, it is revealed for the first time that ultra-high-speed impact can trigger in-situ dehydrogenation at the impact interface of titanium hydride (TiH). This phenomenon leads to a phase transformation from brittle TiH to ductile Ti, causing a shift in the ductile-to-brittle transition from the impact interface to the particle interior. Inspired by this unique behavior, and considering the mechanical interactions between particles during the spray process, TiH powders were used as feedstock to successfully produce a large-scale random cellular structure through cold spray. A systematic investigation of the deposition process revealed that unbroken TiH particles interact with dehydrogenated ones, resulting in only the ductile portion of the TiH particle being deposited, while the brittle interior is spalled off, consequently forming the “walls” of the cellular structures. This work highlights the potential of TiH powders to advance cold spray technology, particularly in the creation of complex cellular structures.

Polyvinyl alcohol and alginate bio-composite film containing titanium dioxide nanotubes for skin injury repair

This study explores the potential of polyvinyl alcohol (PVA) and alginate (SA) blend polymer films with embedded titanium dioxide nanotubes (TiO2NT) for wound healing applications. The nanocomposite film (PVA+SA@TiO2NT) was fabricated via a simple solvent casting process. The synergistic interaction between PVA and alginate significantly enhanced the film's stability in aqueous environments without compromising its weight. After 24 hours of immersion, the film exhibited a substantial swelling capacity (836±6%) and good WVTR ((282±4%). Scanning electron microscopy (SEM) revealed the formation of a smooth and random pore structure within the film. Fourier-transform infrared spectroscopy (FTIR) confirmed the successful formation of hydrogen bonds between PVA and alginate, along with the presence of Ti-O bonds, indicating successful incorporation of TiO2NT into the PVA+SA matrix. X-ray diffraction (XRD) analysis further corroborated the presence of TiO2NT. In vitro biocompatibility studies demonstrated the non-cytotoxic nature of the PVA+SA@TiO2NT bio-composite film. Additionally, in vitro wound healing studies suggest its potential as a promising biomaterial for wound dressing applications. These findings warrant further investigation to elucidate the complete mechanisms of action and optimize the nanocomposite's properties for clinical translation.

Liquid and gas permeabilities of nanostructured layers: Three-dimensional lattice Boltzmann simulation

Liquid water and gas permeabilities in nanostructured catalyst layers (CLs) (pore size ∼10–150 nm) and microporous layers (MPLs) (pore size ∼50 nm-5 μm) are crucial to reduce the mass transport loss in proton exchange membrane fuel cells (PEMFCs). Experimental measurement of their permeabilities poses great challenges due to their brittle and thin characteristics. Presently, considerable discrepancy exists in the reported permeability values for CLs and MPLs in the literature with variation spanning several orders of magnitude. This study digitally reconstructed various nanostructures of similar pore size as CLs and MPLs to calculate their permeabilities using the Lattice Boltzmann Method (LBM) based on no-slip (e.g. for liquid water flow in MPL and CL's secondary pores) or slip condition (e.g. for gas flow in MPL). Analysis was performed to evaluate the range of pore size in nanostructures for the two boundary conditions. A comprehensive investigation was conducted under various parameters such as the Reynolds number (Re), sphere diameter, porosity, and pore structure. The results revealed that permeability exhibits an increasing trend with the diameter and porosity. The predicted permeability of randomly arranged spheres agrees well with established correlations. The random sphere structure demonstrates higher permeability than their body-centered cubic (BCC) and face-centered cubic (FCC) counterparts. Under slip boundary condition, the permeability was enhanced, compared to the no-slip condition. This study's novelty lies in using distinct boundary conditions to assess the permeabilities of liquid and air, based on flow pattern analysis in the CL and MPL pore structures. A new empirical correlation describing the influence of the Knudsen number (Kn) on the slip permeability was developed, exhibiting consistency with simulation across the entire porosity spectrum.

The combination of random and controllable--- design strategy and mechanical properties of directional random porous structures inspired by Wolff's law

The combination of random and controllable--- design strategy and mechanical properties of directional random porous structures inspired by Wolff's law

Research on the random generation model of 2D irregular aggregates in concrete based on fast grid region division method and its ground penetrating radar characteristics

Concrete can be regarded as a composite material with aggregates embedded in hardened slurries. The size, shape and distribution of aggregates directly affect multiple properties of concrete, including mechanical properties, ultrasonic field characteristics of concrete and ground penetrating radar (GPR) wave field characteristics. Therefore, conducting in-depth research on the random generation model of two-dimensional irregular aggregates is particularly important. This article introduces a fast grid region division method (FGRDM), which is an efficient reconstruction algorithm designed for two-dimensional concrete aggregate models. The algorithm takes into consideration the random micro-aggregate structure of concrete. A two-dimensional random distribution model of irregular aggregates in concrete was successfully established by generating concrete models with different particle size distributions and aggregate contents. Furthermore, the finite difference time domain method was used to analyze the GPR wave field of the random model. The significant influence of aggregate shape and distribution on the GPR wave field was discussed. Compared with existing two-dimensional irregular aggregate random generation models, the FGRDM proposed in this paper avoids computational redundancy and generates irregular aggregates at an increasingly fast speed. In the analysis of GPR data, electromagnetic waves are greatly affected by the shape and distribution of aggregates, highlighting the critical role of two-dimensional random distribution models in GPR data analysis. The paper uses FGRDM to generate random irregular aggregates to simulate the distribution of aggregates in actual concrete. Different diameter glass fiber reinforced polymer (GFRP) bars are inserted into the actual concrete and the numerical model to investigate the effect of aggregate size on the recognition of different diameter GFRP bars. The simulation results are generally consistent with the experimental results.

Macrofaunal Biodiversity and Patch Mosaics on the Deep Gulf of Mexico Seafloor

ABSTRACTThe deep‐sea benthos often exhibit exceptional biodiversity. The patch‐mosaic hypothesis proposes that this deep‐sea diversity arises from varied microhabitats with prolonged temporal persistence filtering for distinctive communities thereby increasing beta‐diversity. This study investigated environmental, community, and macrofaunal species turnover at four deep‐sea sites (~2000 m) in the northern Gulf of Mexico. Using precise small‐scale sampling with a ROV, we analyzed patterns across spatial scales from centimeters to approximately 400 km among 67 sediment cores. We examined the relationships between sedimentary carbon, sediment grain size, and macrofaunal alpha‐ and beta‐diversity. Subsequently, we explored the role of these environmental properties and their spatial arrangement in shaping communities and species distributions. We observed a consistent trend where the overall abundance and diversity of a community increased with higher carbon but decreased with increasing grain size. Substantial faunal turnover was observed among cores, even at centimeter scales, with the contribution of centimeter‐scale spatial distance rivaling that of 100‐km scales in faunal dissimilarity. Similar to alpha‐diversity, beta‐diversity exhibited strong correlations with sediment carbon and grain size. The observed random spatial structure in grain size and carbon appear to translate into randomness in both community and species distribution. These findings align with the patch‐mosaic model, underscoring the complexity of deep‐sea ecosystems. These findings suggest an intricate relationship between sedimentary attributes, faunal composition, and spatial arrangement in the deep‐sea benthos, shedding light on the mechanisms driving biodiversity in seemingly homogeneous environments.

Random Raman Lasing in Diode-Pumped Multi-Mode Graded-Index Fiber with Femtosecond Laser-Inscribed Random Refractive Index Structures of Various Shapes

Diode-pumped multi-mode graded-index (GRIN) fiber Raman lasers provide prominent brightness enhancement both in linear and half-open cavities with random distributed feedback via natural Rayleigh backscattering. Femtosecond laser-inscribed random refractive index structures allow for the sufficient reduction in the Raman threshold by means of Rayleigh backscattering signal enhancement by +50 + 66 dB relative to the intrinsic fiber level. At the same time, they offer an opportunity to generate Stokes beams with a shape close to fundamental transverse mode (LP01), as well as to select higher-order modes such as LP11 with a near-1D longitudinal random structure shifted off the fiber axis. Further development of the inscription technology includes the fabrication of 3D ring-shaped random structures using a spatial light modulator (SLM) in a 100/140 μm GRIN multi-mode fiber. This allows for the generation of a multi-mode diode-pumped GRIN fiber random Raman laser at 976 nm with a ring-shaped output beam at a relatively low pumping threshold (~160 W), demonstrated for the first time to our knowledge.

Structure prediction of stable sodium germanides at 0 and 10 GPa

In this paper we used random structure searching (AIRSS) to carry out a systematic search for crystalline Na-Ge materials at both 0 and 10 GPa. The high-throughput structural relaxations were accelerated using a machine-learned interatomic potential (MLIP) fit to density-functional theory (DFT) reference data, allowing ∼1.5 million structures to be relaxed. At ambient conditions we predict three new Zintl phases, Na3Ge2,Na2Ge, and Na9Ge4, to be stable and a number of Ge-rich layered structures to lie in close proximity to the convex hull. The known NaδGe34 clathrate and Na4Ge13 host-guest structures are found to be relatively stabilized at higher temperature by vibrational contributions to the free energy. Overall, the low-energy phases exhibit exceptional structural diversity, with the expected mixture of covalent and ionic bonding confirmed using the electron-localization function (ELF). The local Ge structural motifs present at each composition were determined using smooth overlap of atomic positions (SOAP) descriptors and the Ge-K edge was simulated for representatives of each motif, providing a direct link to experimental x-ray absorption spectroscopy (XAS). Two Ge-rich phases are predicted to be stable at 10 GPa; NaGe3 and NaGe2 have simple kagome and simple hexagonal Ge lattices respectively with Na contained in the pores. NaGe3 is isostructural with the MgB3 and MgSi3 family of kagome superconductors and remains dynamically stable at 0 GPa. Removing the Na from NaGe2 results in the hexagonal lonsdalite Ge allotrope, which has a direct band gap. Published by the American Physical Society 2024

Random structures and automorphisms with a single orbit

AbstractWe investigate the class of m-hypergraphs whose substructures with l elements have more than sm-element subsets that do not form a hyperedge. The class will have the free amalgamation property if s is small, but it does not if s is large. We find the boundary of s. Suppose the class has the free amalgamation property. In the case $$m \ge 3$$ m ≥ 3 , we demonstrate that the random structure for the class has continuum-many automorphisms with a single orbit. The situation differs from the case of Henson graphs. In the case of generic hypergraphs constructed by Hrushovski’s method using a predimension function, we also demonstrate that they have no automorphisms with a single orbit.

Laser Control of Specular and Diffuse Reflectance of Thin Aluminum Film-Isolator-Metal Structures for Anti-Counterfeiting and Plasmonic Color Applications

Plasmonic structural color originates from the scattering and absorption of visible light by metallic nanostructures. Stacks consisting of thin, disordered semicontinuous metal films are attractive plasmonic color media, as they can be mass-produced using industry-proven physical vapor deposition techniques. These films are comprised of random nano-island structures of various sizes and shapes resonating at different wavelengths. When irradiated with short-pulse lasers, the nanostructures are locally restructured, and their optical response is altered in a spectrally selective manner. Therefore, various colors are obtained. We demonstrate the generation of structural plasmonic colors through femtosecond laser modification of a thin aluminum film–isolator–metal mirror (TAFIM) structure. Laser-induced structuring of TAFIM’s top aluminum film significantly alters the sample’s specular and diffuse reflectance depending on the fluence value and the number of times a region is scanned. A “negative image” effect is possible, where a dark field observation mode image is a negative of a bright field mode image. This effect is visible using an optical microscope, the naked eye, and a digital camera. The use of self-passivating aluminum results in a long-lasting, non-fading coloration effect. The reported technique could be used in anti-counterfeiting and security applications, as well as in plasmonic color printing and macroscopic and microscopic marking for personalized fine arts and aesthetic products such as jewelry.

Mechanochemical Synthesis, Characterization and Reactivity of a Room Temperature Stable Calcium Electride.

A new calcium-based Room temperature Stable Electride (RoSE), K[{Ca[N(Mes)(SiMe3)]3(e-)}2K3] (2), is successfully synthesized from the reaction of a calcium tris-amide, [Ca{N(Mes)(SiMe3)}3K] (1) (Mes = 2,4,6-trimethylphenyl), with potassium under mechanochemical treatment. The dimeric structure of K[{Ca[N(Mes)(SiMe3)]3(e-)}2K3] is calculated using ab initio random structure searching (AIRSS) methods. This shows the existence of highly localized anionic electrons (e-) and suggests poor electrical conductance, as confirmed via electroconductivity measurements. The two anionic electrons in 2 are strongly antiferromagnetically coupled, thus in agreement with the largely diamagnetic response from magnetometry. Reaction of 2 with pyridine affords 4,4'-bipyridine, while reaction with benzene gives C-H activation and formation of a calcium hydride complex, [K(η6-C6H6)4][{Ca[N(Mes)(SiMe3)](H)}2K3] (3). Computational DFT analysis reveals the crucial role played by the ligand framework in the stabilization of this new Ca-hydride complex.

A study on the sound scattering characteristics in random structure using Voronoi Tessellation

In room acoustic design, the use of acoustic diffusers is an effective method for achieving a uniform sound field and controlling reverberation. A common approach is to use periodic diffusers that control reflection directions based on the wavelength of sound. In this study, we explore the utilization of random and nonperiodic structures as acoustic diffusers, taking inspiration from the amorphous structures in nature. The irregularities in random structures are expected to enable the broad diffusion of a wide range of frequencies in various directions. We utilized Voronoi tessellation in both two and three dimensions to create 2D Voronoi diffusers with irregular aperture shapes and 3D Voronoi diffusers with irregular aperture shapes and slopes. Then, the acoustic diffusion characteristics of the 2D and 3D Voronoi diffusers were compared with a periodic-type structure through the finite element analysis and experiments. On the basis of these results, the irregularities in the openings and slopes of Voronoi diffusers broaden the scattering frequencies and enhance the scattering coefficients. This suggests that amorphous structures utilizing Voronoi tessellation can be effective as acoustic diffusers.

Response Matching for Generating Materials and Molecules.

Diffusion models have recently emerged as powerful tools for the generation of new molecular and material structures. The key insight is that the noise in these models is related to the response of the atoms to displacement, and the denoising step is thus analogous to the geometry relaxation of atomistic systems starting from a random structure. Building on this, we present a generative method called Response Matching (RM), which leverages the fact that each stable material or molecule exists at the minimum of its potential energy surface. Any perturbation induces a response in energy and stress, driving the structure back to equilibrium. Matching this response is closely related to score matching in diffusion models. Another important aspect of state-of-the-art diffusion models is the incorporation of physical symmetries such as translation, rotation, and periodicity. RM employs a machine learning interatomic potential and random structure search as the denoising model, inherently respecting these symmetries and exploiting the locality of atomic interactions. RM handles both molecules and bulk materials under the same framework. Its efficiency and generalization are demonstrated on three systems: a small organic molecular data set, stable crystals from the Materials Project, and one-shot learning on a single diamond configuration.

Effect of ultrasound combined with highland barley dietary fiber on gel properties of reduced-salt chicken breast myofibrillar protein.

This study aimed to investigate the effect of ultrasound combined with highland barley dietary fiber (HBDF) on the quality of reduced-salt chicken breast myofibrillar protein (MP) gel. The molecular forces maintaining gel structure, the gelling formation process, and gel microstructure of different groups, two control groups (2% sodium chloride [NaCl] group, 1% NaCl group), and four treatment groups (0.3% HBDF+U5, 0.3% HBDF+U10, 0.5% HBDF+U5, and 0.5% HBDF+U10) were examined. Results indicated significant improvements (p<0.05) in gel properties such as water-holding capacity, textural characteristics, and color of the MP gel of the four treatment groups compared to Control 2 (1% NaCl) group. Furthermore, the second structural alterations were characterized by increase β-sheet, β-turn, and random coil structure contents in treatment groups, especially in 0.3% HBDF+U5 and 0.5% HBDF+U5 groups; in addition, the exposure of more hydrophobic groups and the formation of disulfide bonds and hydrogen bonds were promoted in treatment groups, thus enhancing protein aggregation and gel quality. Finally, compared to Control 2 (1% NaCl) group, more compact and uniform gel network structures and pores inside the composite gels were observed in treatment groups. In conclusion, the findings demonstrated that the application of ultrasound in combination with HBDF improved the gelling characteristics of reduced-salt chicken breast MP gel, especially 0.3% HBDF+U5 and 0.5% HBDF+U5 groups.