Hexagonal Network Research Articles

Gas adsorption analysis for quantifying the edge sites of graphite

The edge plane exposed on the surface of carbon materials is the active site that determines their properties. When graphite is used as the negative electrode in lithium-ion batteries, the edge plane acts as an access point for lithium insertion/desorption. However, because of the low specific surface area and amorphous carbon coating of graphite particles, accurately estimating the number of edge planes is challenging. Therefore, we propose a technique for determining graphite edge planes based on the stepwise adsorption of Kr onto the hexagonal carbon network surface. Graphite particles with highly modified surface structures were prepared by controlling the particle size, heat treatment temperature, and amorphous carbon coating. Electrochemical evaluation revealed significant differences in charge-transfer resistance, an indicator of edge planes. The edge plane determination results obtained using conventional methods such as X-ray diffractometry and Raman spectroscopy did not correlate well with charge-transfer resistance. Meanwhile, Kr adsorption measurements revealed that the stepwise adsorption behavior, because of the interaction of Kr with the energetically homogenous surface, varied significantly depending on the surface properties of graphite particles. The number of edge planes estimated by gas adsorption strongly correlated with charge-transfer resistance. Consequently, we determined that the graphite edge plane tied to the electrochemical index can be derived using gas adsorption analysis. This edge plane determination technique would be applicable not only to graphite but also to highly crystalline carbon materials with an exposed hexagonal carbon network surface.

MEG AND PET IMAGES-BASED BRAIN TUMOR DETECTION USING KAPUR’S OTSU SEGMENTATION AND SOOTY OPTIMIZED MOBILENET CLASSIFICATION

Deep learning techniques have revolutionized medical image analysis recently, particularly in brain tumor (BT) detection. A comprehensive overview of the advancements and challenges associated with employing deep learning methodologies for the accurate and timely detection of BT. This work proposes a novel brain hybrid hexagonal mobile network (BH2Mnet) to identify benign and malignant tumors using MEG and PET images. An adaptive bilateral filter (ABF) is used as a de-noising for input images to eliminate noise artifacts. Eliminating the skull and outer cortical regions, a process known as "skull stripping" is utilized to enhance the number of training images. The de-noised images are segmented to detect the BT using Kapur's Otsu threshold (KOT) algorithm. Based on these segmented tumors, hexagonal feature sets with and without segmentation masks are produced using hybrid hexagonal features (HHF). Finally, the Sooty optimization-based MobileNet classifier is employed to classify the BT into benign, malignant cases. It was determined that the proposed BH2Mnet approach was 99.21 % accurate in classifying data. According to the proposed BH2Mnet NS-CNN, the total accuracy is enhanced by 1.67 %, 2.69 %, and 4.11 % compared to hybrid DAE, BFC, Deep CNN, and Neutrosophy.

Role of the structural order of the hydration layer in regulating the heterogeneous ice nucleation efficiency

Understanding the complex microscopic mechanisms of heterogeneous ice nucleation is crucial across diverse fields from cloud science to microbiology. In this work, we examined the ability of solid surfaces to promote ice nucleation as a function of the structural order of interfacial water, including the first and second hydration layers. Comprehensive all-atom molecular dynamics simulations using the TIP4P/ice water model were conducted on a water film atop a modeled surface inspired by the (0001) surface of AgI crystal, with varying surface charges. These simulations revealed non-monotonic nucleation rates. The first hydration layer formed a hexagonal hydrogen-bond network resembling ice structures, exhibiting low mobility essential for inducing ice nucleation. Notably, the second hydration layer, acting as a key-point bridge, displayed varying degrees of orientational preference facilitated by inter-layer hydrogen bonds. The calculation of fluctuation parameters indicated that the greater structural order of the second layer significantly enhances the surface’s ice-forming capabilities. Unlike previous studies that focused primarily on the role of the first layer of interfacial water, our findings demonstrate that the second layer provides a more accurate indicator of ice nucleation capabilities.

Single-metal-adatom catalysts for the synthesis of 2D carbon nitride metal-coordinated networks

Metal-coordinated networks have been found to be excellent catalyst for environmental purposes, such as green hydrogen generation or photo-degradation of pollutants. Recently, its traditional three-dimensional structure has been extended to two dimensions. However, the synthesis and stability of these networks in their 2D form remains a challenge. We have designed, characterized and synthesized, using a bottom-up approach, a 2D metal-coordinated network combining melamine molecules and thermally generated native copper adatoms on a Cu(110) substrate at 600 K. As a result, we have obtained a 2D hexagonal carbon nitride Cu-coordinated network. We demonstrate that the underlying mechanism of its formation involves partial dehydrogenation and subsequent metalation of amino groups. We prove the crucial role of copper adatoms in the formation, serving as heterogeneous metal-site catalysts, as well as in the further stabilization of the network. The obtained metal-coordinated network is indeed a single atom catalyst with high potential in technological applications.

Pegylated surfactants based on fatty acids: 12-hydroxystearic acid versus stearic acid

We describe the aqueous behavior of short Polyethylene glycol (PEG) chains of Mw 4 kDa that are either mono-functionalized or di-functionalized by 12-hydroxy stearic acid (HSA), and stearic acid (SA), respectively. The end capping of the chains by the fatty acids is achieved by Steglich esterification, after a step of protection of the 12-OH functional group in the case of HSA. Small Angle Neutron Scattering (SANS) shows that mono-functionalized chains with both SA or HSA sticky ends self-assemble in star micelles in aqueous solution, and interact through repulsive steric interactions. The di-functionalized telechelic chains self-assemble in flower micelles that interact through interactions that are attractive on average due to the formation of bridges by chains that share their both ends in two different micelles. Solutions of telechelic chains undergo a phase separation between a dilute solution of micelles and a dense hexagonal crystalline network of flower micelles above a given polymer concentration threshold. This threshold is lower for SA-PEG-SA than for HSA-PEG-HSA. We postulate that this difference of behavior arises from the formation of hydrogen bonds between the OH groups at the C12 of the alkyl chain in case of HSA that increase the stability of the hydrophobic core of the micelles.

Nonlinear wave propagation in homogenized strain gradient 1D and 2D lattice materials: Applications to hexagonal and triangular networks

AbstractThis work aims to analyze the propagation of fully nonlinear waves, encompassing shear, extension, and bending deformation modes, within homogenized periodic nonlinear hexagonal and triangular networks, successively considering 1D and 2D situations. The wave analysis is conducted from the expression of the effective strain energy density of periodic hexagonal and triangular lattices in the nonlinear regime by a continualization of the discrete lattice equations, considering all forms of energy. We incorporate strain gradient effects into the continuous model to account for the wave‐dispersive nature. The resulting second‐gradient nonlinear continuum exhibits subsonic and supersonic propagation modes. We first examine in a 1D situation the dynamical response of the hexagonal and triangular lattices, considering varying levels of nonlinearity quantified by a single scalar valued parameter. We further evaluate the impact of a fully nonlinear analysis compared to an analysis solely based on the shear energy, regarding both supersonic and subsonic modes. The nonlinear wave propagation analysis is then extended to a 2D situation for the same two lattices. It is shown that the longitudinal mode exhibits a higher frequency at a low degree of nonlinearity; however, as the degree of nonlinearity increases, the shear mode surpasses the longitudinal mode in terms of frequency. As the wavenumber increases, the nonlinearity has a lesser impact on the frequency behavior, and the phase velocity is more influenced by other factors, such as the second gradient contributions of the effective constitutive law. Such a behavior indicates a transition from a highly nonlinear behavior at lower wave numbers to a more linear behavior at higher wave numbers.

Facile fabrication of recyclable robust noncovalent porous crystals from low-symmetry helicene derivative

Porous frameworks constructed via noncovalent interactions show wide potential in molecular separation and gas adsorption. However, it remains a major challenge to prepare these materials from low-symmetry molecular building blocks. Herein, we report a facile strategy to fabricate noncovalent porous crystals through modular self-assembly of a low-symmetry helicene racemate. The P and M enantiomers in the racemate first stack into right- and left-handed triangular prisms, respectively, and subsequently the two types of prisms alternatively stack together into a hexagonal network with one-dimensional channels with a diameter of 14.5 Å. Remarkably, the framework reveals high stability upon heating to 275 °C, majorly due to the abundant π-interactions between the complementarily engaged helicene building blocks. Such porous framework can be readily prepared by fast rotary evaporation, and is easy to recycle and repeatedly reform. The refined porous structure and enriched π-conjugation also favor the selective adsorption of a series of small molecules.

Comparing Adsorption of an Electron-Rich Triphenylene Derivative: Metallic vs Graphitic Surfaces.

Crucial to the performance of devices based on organic molecules is an understanding of how the substrate-molecule interface influences both structural and electronic properties of the molecular layers. Within this context we studied the self-assembly of an alkoxy-triphenylene derived electron donor (HAT) in the monolayer regime on graphene/Ni(111). The molecules assembled into a close-packed hexagonal network commensurate with the graphene layer. Despite the commensurate structure, the HAT molecules only had a weak, physisorptive interaction with the substrate as pointed out by the photoelectron spectroscopy data. We discuss these findings in view of our recent reports for HAT adsorbed on Ag(111) and graphene/Ir(111). For all three substrates HAT adopts a similar close-packed hexagonal structure commensurate with the substrate while being physisorbed. The ionization potential is equal for all three substrates, supporting weak molecule-substrate interactions. These findings are remarkable, as commensurate overlayers usually only form at strongly interacting interfaces. We discuss potential reasons for this particular behavior of HAT which clearly sets itself apart from most studied molecule-substrate systems. In particular, these are the relatively weak but flexible intermolecular interactions, the molecular symmetry matching that of the substrate, and the comparatively weak but directional molecule-substrate interactions.

High-cycle and low-cycle fatigue characteristics of multilayered dissimilar titanium alloys

Multilayered structures of dissimilar titanium alloys can achieve excellent fracture ductility and strength, while their fatigue characteristics especially dislocation networks and twin formation are rarely reported. Heterogeneous microstructures are observed in the multilayered TC4/TB8 alloys, including fine acicular α grains, continuous α layer at prior β grain boundaries (αGB) and β matrix on the TB8 layer, together with equiaxed α grains on the TC4 layer. High-cycle fatigue (HCF) and low-cycle fatigue (LCF) tests show that the initial fatigue damage appears at the αGB/β matrix interfaces on the TB8 layer instead of the boned TC4/TB8 interfaces. Since the stress concentration induced by dislocation pile-up is prone to micro-void formation and crack propagation at the αGB/β interfaces. For LCF, the αGB/β interfaces can not only act as impenetrable barriers and sources of lattice dislocations, but also allow the dislocations cross boundaries during cyclic tension and compression because of the high boundary energy. The formation characteristic of deformation twins that is beneficial for the plastic deformation of α grains in TC4 layer during cyclic strain is investigated. Furthermore, the hexagonal dislocation networks are also found within the equiaxed α grains of TC4 layer after LCF, and the role between interface barrier and slip direction in the formation mechanism is analyzed.

Defined benefit pension plan inhibit the emergence of cooperation in the public goods games

As a social welfare, pension insurance has provided a great assistance to retiree in maintaining their livelihoods. In order to reward the contributions made by cooperators, an additional pension income is provided to them. In this paper, we study a public goods game based on the pension system on population structure, in which only cooperators can purchase pension insurance and receive pension benefits upon meeting specified conditions. In the simulation, we demonstrate the evolution of cooperation frequency over time and investigate the influence of insurance premium, pension baseline, the number of defected neighbors of cooperators, and the enhancement factor on the cooperation frequency. Additionally, we examine the impact of the pension system on cooperative behavior in triangular and hexagonal networks. Our results suggest that in the public goods game on networked structure, the pension system not only fails to promote cooperation but actually inhibits it, even when cooperators do not have to pay any costs and can receive pensions when conditions are met.

Ionic Liquid Crystals Based on Loop-Shaped Copper(I) Complexes.

This paper describes the synthesis and characterization of liquid crystals based on loop-shaped cationic copper(I) complexes of a multidentate ligand. Their synthesis involves the one-pot reaction of an alkyloxy-decorated pyridine-aldehyde unit with a diamine (2,2'-(ethylenedioxy)bis(ethylamine)) spacer to form in situ a pyridine-imine quadridentate-N4-donor ligand, L, which is able to chelate a copper(I) center associated with various noncoordinating anions. All of these compounds were characterized by NMR, IR, and electronic absorption spectroscopy, and more particularly by X-ray diffraction and mass spectroscopy, enabling unambiguous assignment of the [ML]+ mononuclear nature of the cationic components. The presence of six flexible alkyloxy chains at each end of the ligand associated with the rigidity of the core complex causes induction of a liquid crystal state with a columnar self-organized architecture, where the columns are packed in a hexagonal two-dimensional network.

Topological Invariants of Hexagonal Cage Network by Using Algebraic Polynomials

In this article, we go beyond earlier limits in the analysis by using algebraic polynomials to compute the topological indices for hexagonal cage networks. We investigate hexagonal cage networks of different orders and copies by introducing M-Polynomials and Forgotten polynomials, and we derive novel closed formulae and conclusions for a broad range of topological indices. We also create an efficient technique to compute , a pivotal polynomial, as part of our work. In addition to computing, we apply algebraic polynomials to the analysis of these indices, providing more insights into their structural significance in hexagonal cage networks. This work illuminates the algebraic underpinnings of these intricate networks and broadens the scope of topological index computation, with implications for a variety of scientific domains. These polynomials allow us to calculate several features of the network, such as the first and second Zagreb, modified Zagreb, General Randić, inverse General Randić, harmonic, symmetric division, inverse sum, and so on. There are now new closed formulae and outcomes available. Additionally, we offer a technique for calculating the polynomial . We also use algebraic polynomials to analyses all of the aforementioned indices.

Elliptic RevanIndexand its Exponential of Certain Networks

The reverse elliptic Somborindex is a recently introduced topological index. In this paper, we put forward theelliptic Revanindex and its corresponding exponential of a graph and compute exact formulas for some families of networkssuch as silicate networks, rhombus silicate networks, oxide networks, rhombus oxide networks, hexagonal networks and honeycomb networks. Also we establish some properties of elliptic Revan index

Detection of Brain Tumour Via Reversing Hexagonal Feature Pattern for Classifying Double-Modal Brain Images

The diagnosis of brain tumours (BT) is time-consuming and heavily dependent on the radiologists' abilities. Multiple algorithms have been developed for detecting and classifying BT that are both accurate and fast. Recent years have seen an increase in the popularity of deep learning, especially when it comes to developing automated systems that can diagnose and segment BT more accurately and with less time. In this paper, a novel Brain Hexagonal Pattern Network (BHPN) has been proposed to classify the MEG and PET images into normal, benign and malignant tumours. For pre-processing, a bilateral filter is employed to remove noise artifacts from the collected MEG and PET images. To remove the outer cortical and skull region, skull stripping is used, to be implemented to raise the volume of the training datasets. The pre-processed images are segmented using the Otsu threshold algorithm to segment the BT. These segmented tumours are taken as input to the Reversing Hexagonal algorithm to generate the hexagonal feature sets with and without a segmentation mask. In order to categorize tumours into normal, benign and malignant cases, a Spiking Dilated Convolutional Neural Network (SDCNN) classifier system is implemented. The classification accuracy of the Proposed BHPN approach is 99.54%. The Proposed BHPN approach improves the overall accuracy by 1.49%, 2.52%, and 3.93% better than hybrid deep autoencoder (DAE) and Bayesian Fuzzy Clustering (BFC), Deep CNN, and Neutrosophy and Convolutional Neural Network (NS-CNN) respectively.

Investigation of magnetic hysteresis in biased Ta/Pt/Co/FeMn/Ta antidots: Influence of structural dimensions

There exists a controversy in the literature concerning the values of coercive and bias fields in antidots magnetic structures formed by a hexagonal network of nanoholes. The coercive fields (HC) and the exchange bias fields (∣HEXC∣) for antidots (deposited on ultrathin anodic aluminum oxide, namely, AAO) are either increased or diminished by comparison with the same magnetic nanostructures grown on continuous substrates (namely, CML). We propose to elucidate these debates by showing the importance of the easy axis of the magnetization, the direction of the applied magnetic field, the thicknesses of the layers, and the 3D-topology of nanoholes, as well as the magnetic and thermal history of the magnetic measurements. Here, biased Ta(5 nm)/Pt(5 nm)/Co(0.6 nm)/Fe50Mn50(X)/Ta(5 nm) antidots are investigated by extraordinary Hall effect measurements at 5 K, where X varies in the (0–5.5) nm range. The substrate consists in a hexagonal array of holes, described by the pair of (p,d) values, respectively, the period as the distance from center to center of two consecutive holes and the hole diameter. The dimensions of antidots are (p≈100 and d≈40 nm) for X=(2–5.5) nm, (p≈150 and d≈60 nm) for X=3.5 nm, and (p≈100 and d≈60 nm) for X=0. A continuous stack using Si/SiO2(100 nm) is used for comparison. HC and ∣HEXC∣ gradually increase when X is enhanced for both substrates, with nevertheless a weak decrease at high X for the continuous system. Perpendicular magnetic anisotropy is only observed for both unbiased samples, the X=2 nm continuous sample, and both X=5 nm samples that have undergone field cooling treatment from 500 to 5 K under −2 T. Usually, HC(AAO)>HC(CML), ∣HEXC(AAO)∣>∣HEXC(CML)∣, and ∣HA(AAO)∣<∣HA(CML)∣ (HA designating the anisotropy field). However, for certain conditions, as, for instance, for FC-procedures starting from high temperatures and/or strong magnetic field, other situations might be observed. A discussion pertaining to the amplitudes of HC, ∣HEXC∣ and the anisotropy field (∣HA∣) of continuous and discontinuous samples is given for our experimental results as well as for published data in the literature, in the light of structural characteristics (wedge-to-wedge distance, porosity, or coverage ratio). Such biased perpendicular antidots might be particularly used in specific nanomaterials devoted to spintronics.

Optimal Motion Planning for Heterogeneous Multi-USV Systems Using Hexagonal Grid-Based Neural Networks and Parallelogram Law Under Ocean Currents

Optimal Motion Planning for Heterogeneous Multi-USV Systems Using Hexagonal Grid-Based Neural Networks and Parallelogram Law Under Ocean Currents

Partition Dimension of Generalized Hexagonal Cellular Networks and Its Application

Partition Dimension of Generalized Hexagonal Cellular Networks and Its Application

Discarding metal incorporation in pyrazole macrocycles and the role of the substrate on single-layer assemblies.

Pyrazole derivatives are key in crystal engineering and liquid crystal fields and thrive in agriculture, pharmaceutical, or biomedicine industries. Such versatility relies in their supramolecular bond adaptability when forming hydrogen bonds or metal-pyrazole complexes. Interestingly, the precise structure of pyrazole-based macrocycles forming widespread porous structures is still unsolved. We bring insight into such fundamental question by studying the self-assembled structures of a bis-pyrazole derivative sublimed in ultra-high-vacuum conditions (without solvents) onto the three (111) noble metal surfaces. By means of high-resolution scanning tunneling microscopy that is validated by gas phase density functional theory calculations, we find a common hexagonal nanoporous network condensed by triple hydrogen bonds at the molecule-metal interface. Such assembly is disrupted and divergent after annealing: (i) on copper, the molecular integrity is compromised leading to structural chaos, (ii) on silver, an incommensurate new oblique structure requiring molecular deprotonation is found and, (iii) on gold, metal-organic complexes are promoted yielding irregular chain structures. Our findings confirm the critical role of these metals on the different pyrazole nanoporous structure formation, discarding their preference for metal incorporation into the connecting nodes whenever there is no solvent involved.

Analyzing the normalized Laplacian spectrum and spanning tree of the cross of the derivative of linear networks

<abstract><p>In this paper, we focus on the strong product of the pentagonal networks. Let $ R_{n} $ be a hexagonal network composed of $ 2n $ pentagons and $ n $ quadrilaterals. Let $ P_{n}^{2} $ denote the graph formed by the strong product of $ R_{n} $ and its copy $ R_{n}^{\prime} $. By utilizing the decomposition theorem of the normalized Laplacian characteristics polynomial, we characterize the explicit formula of the multiplicative degree-Kirchhoff index completely. Moreover, the complexity of $ P_{n}^{2} $ is determined.</p></abstract>

Optimization and Removal of Heavy Metals from Groundwater Using Moringa Extracts and Coconut Shell Carbon Powder


 
 
 
 Abstract: This study focuses on enhancing the efficacy and elimination of heavy metals from groundwater by employing bio-absorbents generated from Moringa extracts and Coconut shell carbon powder. The green synthesis technique was utilized to produce cost-effective absorbents, including powdered Moringa seeds, leaves and carbon from coconut shells. The study examines the effectiveness of synthetic bio-absorbents in removing heavy metals, including Copper (Cu), Cadmium (Cd), Iron (Fe), Lead (Pb), Chromium (Cr), and Zinc (Zn), from groundwater. Identifying functional groups such as Hydroxyl (OH), C-H of alkenes, C=C of alkenes, and C-O from carboxylic acids have been determined to be essential for removing metals in groundwater. The method of FT-IR spectroscopy was used to characterize these functional groups. The examination of the morphology of Moringa seeds indicated the presence of consistent spherical network sheets, but Moringa leaves had a hexagonal network structure like a flower. The coconut shell photos revealed the presence of irregular, small-sized flakes that were clustered together to create a sheet. In light of the escalating deterioration of groundwater quality in Vijayawada as a result of industrial expansion, urban development, and significant infrastructure initiatives, the primary objective of the study was to ascertain the primary contaminants present in the groundwater. Subsequently, adsorption methods utilizing natural bio-absorbents were employed. Water samples were gathered and exposed to bio-absorption utilizing powdered Moringa olifera leaves, powdered Moringa olifera seeds, and powdered carbon derived from coconut shells. The technique of Atomic Absorption Spectroscopy was utilized to examine the decrease in concentrations of heavy metals. The findings demonstrated that the bio-absorption of heavy metals was more prominent in Moringa olifera seed powder than in Moringa olifera leaf powder and coconut shell carbon powder. The highest levels of adsorption for copper, cadmium, and lead were achieved at 98.5%, 99.5% and 99.4%, respectively. This work offers useful insights into the potential of bio-absorbents manufactured using green methods for effectively eliminating heavy metals from groundwater. It addresses the crucial problem of water quality in metropolitan areas.