3D Polyhedra Research Articles

Sulfur and nitrogen co-doped Ni/Co carbide 3D polyhedron nanoparticles with hollow core for hybrid supercapacitors

The methodologies for the synthesis of core-shell multilayered morphologies are being intensely explored. Following such scenarios, we report the fabrication of sulfur (S) and nitrogen (N) co-doped nickel/cobalt carbide (S,N@Ni/Co–C) hollow (carbon matrix) polyhedral nanoparticles (PNPs) by facile solvothermal and sulfurization process. The main objective of this research is to study the anomaly behind the structural deformation of the PNPs during the annealing and to propose a relevant method to preserve them by enhancing their abilities. Additionally, the electrochemical properties of the S, N@Ni/Co–C/nickel foam (NF) electrode are optimized and examined, exhibiting a high areal capacity of 563.3 μAh cm−2 and a notable cycling retention of 96 % at 7 mA cm−2 for 5000 cycles in a three-electrode system. Furthermore, the optimized electrode is employed as a positive electrode along with an activated carbon-coated NF as a negative electrode to fabricate a hybrid supercapacitor device which delivers a maximum energy density of 118.9 μAh cm−2 and a maximum power density of 7000 μA cm−2. Finally, it is used as a power source to drive a few real-time electronic devices, especially safety E-bands.

A macro BDM H-div mixed finite element on polygonal and polyhedral meshes

A BDM type of H(div) mixed finite element is constructed on polygonal and polyhedral meshes. The flux space is the H(div) subspace of the n-product ΠiPk(Ti)d space such that the divergence is a one-piece Pk−1 polynomial on the big polygon or polyhedron T. Here we assume the 2D polygon can be subdivided into triangles by connecting only one vertex with some vertices of the polygon. For the 3D polyhedron we assume it can be subdivided into tetrahedra, with no added vertex on subdividing its face-polygons, and with either no internal edge or one internal edge. Such mixed finite elements can be more economic on quadrilateral and hexahedral meshes, compared with the standard BDM mixed element on triangular and tetrahedral meshes. Numerical tests and comparisons with the triangular and tetrahedral BDM finite elements are provided.

Component modulation and integrated multidimensional heterostructures of bimetallic MOFs derived 0D Co3ZnC/Co encapsulated in 2D CNTs-grafted 3D N-doped porous carbon polyhedron for high-efficient microwave absorption

Component modulation and multidimensional structural design are effective strategies to regulate the electromagnetic parameters and impedance matching, resulting in high-efficient microwave absorption. Herein, multidimensional integrated Co3ZnC/Co@C heterostructures compounding of 0D Co and Co3ZnC NCs, 1D CNTs and 3D porous carbon polyhedrons were fabricated by pyrolysis of bimetallic MOFs. Co and Co3ZnC NCs are uniformly encapsulated in CNTs-grafted porous carbon polyhedrons, forming 0D-1D-3D integrated heterostructures. The Co3ZnC/Co@C composites show component-modulated electromagnetic parameters and microwave absorption properties, which can be simply regulated by adjusting the ratio of Co/Zn in the MOFs precursor. With a filling ratio of 30 wt%, the optimal Co3ZnC/Co@C heterostructures show a minimum reflection loss (RL) value of −66.78 dB at 7.43 GHz with a thickness of 4.5 mm, located at the C band. The maximum effective absorption bandwidth (RL≤−10 dB) is up to 4.8 GHz (12.9–17.7 GHz) at only 2.0 mm. The high-efficient microwave absorption performance is attributed to that the multidimensional integrated heterostructures can sufficiently maximize the synergistic effects of each component. The uniformly distributed 0D Co and Co3ZnC NCs can promote magnetic loss and interfacial polarization. 1D CNTs are beneficial to enhance the conductive loss. 3D porous carbon polyhedrons grafted with CNTs are favored to promote the scattering of microwaves and impedance matching. These findings suggest a new insight to achieve high-performance microwave absorption by modulating the component and integrating multidimensional structures.

Co4N embedded nitrogen doped carbon with 2D/3D hybrid structure as sulfur host for room-temperature sodium-sulfur batteries

Room temperature sodium-sulfur (RT Na-S) batteries demonstrate a high theoretical energy density, but their practical application is limited by the sodium polysulfides (NaPSs) shuttling and slow redox kinetics. Herein, we report the design of the dimensional hybrid structure of 2D ZIF-67 nanosheets and 3D ZIF-67 polyhedron on the surface of carbon fiber by a pseudomorphic replication approach. After pyrolysis in ammonia, a hybrid structure composed of 2D N-doped carbon nanosheets and 3D N-doped carbon nano-polyhedrons embedded with Co4N nanoparticles (denoted as 2D/3D Co4N-NC@CC) is designed as a sulfur host for RT Na-S battery. The complex structure of 2D/3D composite guarantees abundant adsorption and catalytic sites, accelerating electrons/mass transport abilities compared with single 2D or 3D structure, in which Co4N can effectively catalyze the conversion of NaPSs and inhibit “shuttling effect”. Consequently, the RT Na-S cell with 2D/3D Co4N-NC@CC cathode exhibits extra-high discharge capacity of 466 mAh g−1 at 3.0 C and an outstanding long-term cycling stability (592 mAh g−1 at 1.0 C after 1000 cycles). The hybrid 2D/3D Co4N-NC@CC with excellent electrochemical performance represents a potential candidate for developing advanced RT Na-S batteries and other energy storage systems.

Algorithmic Design of 3D Wireframe RNA Polyhedra.

We address the problem of de novo design and synthesis of nucleic acid nanostructures, a challenge that has been considered in the area of DNA nanotechnology since the 1980s and more recently in the area of RNA nanotechnology. Toward this goal, we introduce a general algorithmic design process and software pipeline for rendering 3D wireframe polyhedral nanostructures in single-stranded RNA. To initiate the pipeline, the user creates a model of the desired polyhedron using standard 3D graphic design software. As its output, the pipeline produces an RNA nucleotide sequence whose corresponding RNA primary structure can be transcribed from a DNA template and folded in the laboratory. As case examples, we design and characterize experimentally three 3D RNA nanostructures: a tetrahedron, a triangular bipyramid, and a triangular prism. The design software is openly available and also provides an export of the targeted 3D structure into the oxDNA molecular dynamics simulator for easy simulation and visualization.

Magnetic Anomalies Caused by 3D Polyhedral Structures With Arbitrary Polynomial Magnetization

AbstractMagnetization is a natural property of magnetic materials which is widely used to analyze paramagnetic data, locate unexploded ordnance, explore mineral deposits and gas resources, and image anomalous magnetic structures in the Earth's crust. An essential and challenging task is to compute accurate magnetic anomalies caused by realistic magnetic 3D structures. In this study, for the first time, we derive the analytical expressions of magnetic potential, magnetic field and magnetic gradient tensor for magnetic materials with 3D polyhedral shapes and magnetization vectors that may vary in the space following polynomial trends. The order of polynomials can vary from one to high positive integers in both horizontal and vertical directions. Synthetic and realistic deposit models are used to validate our analytical solutions. We release the open‐source code in C++.

Mn-Based Hierarchical Polyhedral 2D/3D Nanostructures MnX2 (X = S, Se, Te) Derived from Mn-Based Metal–Organic Frameworks as High-Performance Electrocatalysts for the Oxygen Evolution Reaction

Three-dimensional (3D) nanomaterials are being explored extensively to serve as efficient electrocatalyts, which can be designed through the modification of electronic states of active sites in energy conversion applications. In this work, for the first time, a series of hierarchical polyhedral 3D nanostructures of Fe-doped manganese-based chalcogenides MnX2 (X = S, Se, Te) incorporating amorphous carbon (C) is synthesized using an Mn-based metal–organic framework as the precursor via a two-step hydrothermal route. The MnX2/C hierarchical polyhedral nanostructures (HPNs) (X = S, Se, Te) display remarkable results such as lower overpotentials of 305, 276, and 246 mV at a current density of 10 mA cm–2 and small Tafel slopes of 85, 90, and 48 mV dec–1, respectively. Moreover, iron-doped MnX2 (Fe–MnX2/C-HPNs, X = S, Se, Te) display improved electrocatalytic activity, achieving lower overpotentials of 280, 246, and 210 mV at a current density of 10 mA cm–2 and smaller Tafel slopes of 85, 65, and 48 mV dec–1, respectively. The enhanced efficiency of two-dimensional (2D)/3D hierarchical polyhedral nanostructures (Fe–MnX2/C-HPNs, X = S, Se, Te) is due to the larger specific surface area, easy charge transport, and integrated amorphous carbon. Hence, the construction of exceptionally efficient and low-cost electrocatalysts could be facilitated by this MOF-template approach for multilayer nanostructured materials for future applications.

Targeted Synthesis of Anti‐Hydrolysis 2D‐ZIF Laminates with Super‐Hydrophobic Transport Channels via In Situ Phase Transition Strategy

AbstractThe design flexibility in the crystalline structure and surface wettability make the zeolitic imidazolate frameworks (ZIFs) an excellent platform for task‐specific applications. However, the key challenge lies in the precise modulation of transport channels, which still suffers from slow diffusion kinetics in nanopores and the loss of hydrophobicity during long‐term operation. Here, a facile structural directing method to render conventional 3D polyhedrons to well‐controlled ZIF nanoplates, and further to super‐hydrophobic laminated material by an in situ phase transition strategy is reported. As exemplified in water transport devices, the integrated ZIFs laminate shows an exceptional anti‐hydrolysis property and super‐hydrophobic transport channels, which warrant remarkable structural stability at fully wet conditions for a time period of at least 3 months, even under acidic conditions and boiling water for 24 h. The simple transformation strategy paves the way for fabrication and regulation of coordinated structures where hydrophobic transport channels are required, and opens a new opportunity for the smart design of advanced structures for water treatment under harsh environments.

High performance humidity sensor based on 3D mesoporous Co3O4 hollow polyhedron for multifunctional applications

In this work, the three-dimensional (3D) hollow mesoporous Co3O4 was successfully prepared by calcining the Co-based zeolitic imidazolate framework-67 (ZIF-67). As-obtained Co3O4 inherited the rhombohedral framework structure of ZIF-67 and possessed mesoporous and hollow structure. Further, the humidity sensor based on Co3O4 was fabricated, and its humidity sensing properties were investigated at room temperature (25 °C). The results indicated that the Co3O4 humidity sensor exhibited high humidity sensing performance with a wide linear detection range (10%−95% relative humidity (RH)), small humidity hysteresis (2.6% RH), and fast response/recovery times (1.0/13.5 s). In particular, the Co3O4 humidity sensor was of high detection resolution (1% RH). The excellent performance was attributed to the strong hydrophilicity and the unique 3D porous structure of Co3O4. In addition, the potential applications of the fabricated Co3O4 humidity sensor in skin humidity, simulated diaper, human breathing, and non-contact switch were demonstrated. This work provides a promising humidity sensing material for fabricating high-performance humidity sensors.

DEM models using direct and indirect shape descriptions for Toyoura sand along monotonous loading paths

Two different DEM models are proposed for quantitatively simulating Toyoura sand macroscopic response along various monotonous loading paths and for a wide range of initial densities. The first model adopts spherical particles and compensates for the irregular shapes of Toyoura sand grains by adding an additional rolling resistance stiffness to the classical linear contact model. The second model follows a different strategy whereby rolling stiffness is abandoned in favor of more complex shapes in the form of a few different 3D polyhedrons defined from a 2D micrograph of Toyoura particles. After a preliminary analysis of the number of particles for optimal REV simulations, the two different modeling approaches are calibrated using triaxial compression in so-called drained conditions, adopting a common contact friction angle for the two models. Similar predictive abilities are then obtained along so-called undrained (constant volume) triaxial compression and extension paths. Although it leads to 9-times longer simulations, the polyhedral approach is easier to calibrate regarding the contact parameters. It also enables a more precise description of the microstructure in terms of particle shapes and initial fabric anisotropy, whose crucial role is evidenced in a parametric analysis.

Development of the distinct lattice spring model with polyhedral particles

Distinct Lattice Spring Model (DLSM) is a microscopic model to overcome the mismatch problem of degrees of freedom when coupling between discrete element method (DEM) and finite element method (FEM). In the original DLSM, the lattice model is composed of a number of same spherical particles, which has the problem of inaccurate geometric description. A polyhedral 3D DLSM was developed to overcome some limitations of the original DLSM. A new pre- and post-processing method is introduced to extend the ability of DLSM on precise geometry description. Following this, a pre-processing method is proposed to generate the lattice model from a 3D Finite Element (FE) Mesh or a 3D Numerical Manifold Method (NMM) Mesh. It is required that the generated mesh can present the precise 3D geometry and consider the spatial morphology of joint surfaces. The 3D FE mesh is generated by using the general mesh software. The FE mesh is generated according to the free surfaces and the joint surfaces defined in the model. To get the 3D NMM mesh, a 3D surface mesh Boolean algorithm is developed. The surface mesh Boolean algorithm is used for solving the Boolean operations between mathematic covers and physical covers in NMM. By using the algorithm, the 3D closed geometry cut by 3D surface and the union of multiple 3D surfaces can be solved. The 3D NMM mesh is ultimately generated through the Boolean intersection of mathematical covers and physical covers, the physical covers include the free surfaces and joint faces. The polyhedral particles generated by the FE mesh or NMM mesh have different shapes and sizes, the springs between polyhedral particles will also have different lengths. The effectiveness, necessity, and correctness of these enrichments are demonstrated from a number of specially designed numerical examples.

Self-supporting structure design with feature-driven optimization approach for additive manufacturing

In this work, a topology optimization approach is developed for additive manufacturing (AM) of 2D and 3D self-supporting structures. Three important issues, i.e., overhang angle control, avoidance of the so-called V-shaped areas and minimum length scale control are addressed. 2D solid polygon and 3D polyhedron features are introduced as basic design primitives that are capable of translations, deformations and intersections to drive topological changes of the structure. The overhang angle control is realized in a straightforward way only by imposing upper bounds to related design variables without introducing any nonlinear constraint. The V-shaped area is avoided by simply limiting the positions of solid features. Minimum length scale control is controlled by a robust formulation. Numerical examples in 2D and 3D demonstrate the effectiveness of the proposed approach for various build directions, critical overhang angles and minimum length scales considered in AM.

Shared memory parallelization for high-fidelity large-scale 3D polyhedral particle simulations

Particle shape plays a vital role in granular material behavior, but simulations with realistic particle shapes are uncommon due to significant computational demands of complex particle geometry representation. In this work, BLOKS3D, a polyhedral Discrete Element Method (DEM) and impulse-based DEM (iDEM) codes are parallelized to enable large-scale simulations with realistic particle shapes on readily accessible multi-core machines. Data structures used in the original codes were redesigned and optimized, leading to 15% improved performance of the original serial codes. New parallel algorithms were developed resulting in 28 times performance improvement on a 48-core (quad-CPU) shared memory system over single core serial algorithm. The parallelized 3D polyhedral DEM and iDEM were applied to series of column collapse simulations. The codes successfully reproduced the runout distance in granular column collapse experiments. The particle force data from both parallelized DEM and iDEM matched data from the serial algorithm. The new parallel implementation of iDEM was then demonstrated with unprecedented 52 million 3D polyhedral particles simulations. This work will benefit future granular material studies with the newly introduced capacity to run large-scale simulations with realistic particle shapes on shared memory hardware platforms readily accessible to many engineers and researchers.

PolyFrame, Efficient Computation for 3D Graphic Statics

In this paper, we introduce a structural form finding plugin called PolyFrame for the Rhinoceros software. This plugin is developed based on the methods of 3D Graphic Statics and Polyhedral Reciprocal Diagrams. The computational framework of this plugin uses new robust and efficient algorithms for the creation and modification of complex funicular, compression-only structural forms and is freely available for students, designers, researchers, and practitioners in the fields of architecture, structural engineering, mechanical engineering, and material science. The geometry-based structural design methods are one of the most intuitive yet powerful structural design methods that have recently been extended to 3D based on the Principles of the Equilibrium of Polyhedral Frames. Still, the increased geometrical complexities of the polyhedral diagrams hinder more in-depth practical applications and the research in this field. The framework proposed in this paper can manage, in near real-time, the creation and transformation of reciprocal polyhedral diagrams with a large number of elements as form and force diagrams for structural design purposes. The paper also introduces a hybrid object-oriented data structure that extends and generalizes the previously proposed approaches and thus allows the users to incorporate a variety of different geometric constraints, including edge lengths and the location of the supports from the initial stages of design. Additionally, a new parallel manipulation algorithm is introduced that is capable of transforming polyhedral diagrams while preserving the edge directions and face normal. As a result, a designer can effectively manipulate both structural form and its force distribution without breaking their reciprocity.

Lemon juice-assisted synthesis of LaMnO3 perovskite nanoparticles for electrochemical detection of dopamine

Dopamine (DA) is a significant neurotransmitter in the central nervous system that controls many physiological functions. The abnormal or imbalance of DA levels in the human body remarkably affects the physiological functions. Therefore, to detect and monitor DA levels in the human body is necessary to control the body functions. In this context, we have prepared well-defined three-dimensional (3D) polyhedron structured lanthanum manganite nanoparticles (LaMnO3 NPs) by using conventional (Cp) and lemon-juice (Lj) assisted routes and utilized as an electrocatalyst for the sensitive and selective electrochemical detection of DA. The crystalline phase and structure of as-prepared LaMnO3 NPs are confirmed by XRD, XPS and TEM analyses. The Lj-LaMnO3 NPs modified glassy carbon electrode (GCE) shows enhanced electrocatalytic activity towards DA oxidation with lower potential compared to the Cp-LaMnO3 NPs and bare GC electrodes. Moreover, Lj-LaMnO3 NPs/GCE exhibited a wide detection window (1–600 µM), lower detection limit (32 nM), good selectivity and stability. Besides, the modified electrodes are successfully used in the real samples analysis such as urine and saliva samples and the obtained recovery values are good and satisfactory. Hence, the Lj-LaMnO3 NPs/GCE can be used to determine the DA level and offers a best matrix for pharmaceutical applications.

DEM modelling of 3D polyhedra with applications to gabion rockfall barriers

Rock particle shape plays a crucial role in shear resistance and energy consumption during transient loads. The dynamics of such granular materials are complex and cannot be properly described using closed-form solutions when the problem involves more than a few particles. Thus, for the sake of computational efficiency, it is common practice to implement simplified numerical models that involve a limited number of particle interactions. In this study, a novel approach is used to capture realistic particle shapes while maintaining a relatively high simulation efficiency. The geometry of the particles is determined by a Delaunay triangulation which operates on a set of vertices and returns the corresponding network of facets and grid connections. Inertial and material properties are assigned to the rock prototype which are representative of realistic gravel particles. The algorithm is validated by performing a series of numerical simulations for various particle configurations, demonstrating that mass and momentum are conserved. A potential application of this work is related to rockfall barriers and their response to rigid boulder impacts. This innovative model, based on the discrete element method, is shown to be capable of simulating rock particles with realistic shapes and complex physical interactions.

Meta-DNA structures.

DNA origami has emerged as a highly programmable method to construct customized objects and functional devices in the 10-100 nm scale. Scaling up the size of the DNA origami would enable many potential applications, which include metamaterial construction and surface-based biophysical assays. Here we demonstrate that a six-helix bundle DNA origami nanostructure in the submicrometre scale (meta-DNA) could be used as a magnified analogue of single-stranded DNA, and that two meta-DNAs that contain complementary 'meta-base pairs' can form double helices with programmed handedness and helical pitches. By mimicking the molecular behaviours of DNA strands and their assembly strategies, we used meta-DNA building blocks to form diverse and complex structures on the micrometre scale. Using meta-DNA building blocks, we constructed a series of DNA architectures on a submicrometre-to-micrometre scale, which include meta-multi-arm junctions, three-dimensional (3D) polyhedrons, and various 2D/3D lattices. We also demonstrated a hierarchical strand-displacement reaction on meta-DNA to transfer the dynamic features of DNA into the meta-DNA. This meta-DNA self-assembly concept may transform the microscopic world of structural DNA nanotechnology.

Algorithm for generation of 3D polyhedrons for simulation of rock particles by DEM and its application to tunneling in boulder-soil matrix

The shape of rock particle can profoundly affect its mechanical behaviors due to the interlocking force associated with morphological features. In this study, a hybrid extension method encompassing both convexity control and overlap detection was developed to generate three-dimensional (3D) polyhedrons for simulating irregularly shaped rock particles by discrete-element-method (DEM). Based on a random initial tetrahedron, a polyhedron can be extended from a simple shape to a complex one by adding new tetrahedrons. To control polyhedron convexity, a two-step method derived from the definition of convexity was proposed in this study. Moreover, the enhanced Gilbert–Johnson–Keerthi (GJK) algorithm was applied for overlap detection during the extension process of polyhedron generation. With the proposed hybrid extension method (HEM), a numerical model for simulation of tunnelling in boulder-soil matrix was built in the commercial DEM software; then, extensive parametric studies were performed to explore the influence of several factors (boulder size, orientation, position, and morphology) on tunnelling. The simulation results demonstrate the efficiency and reliability of the proposed algorithm and revealed the ground movement patterns in case an undetected large boulder was accidently encountered by tunnelling at shallow depth.

Cut-enhanced PolyCube-maps for feature-aware all-hex meshing

Volumetric PolyCube-Map-based methods offer automatic ways to construct all-hexahedral meshes for closed 3D polyhedral domains, but their meshing quality is limited by the lack of interior singularities and feature alignment. In the presented work, we propose cut-enhanced PolyCube-Maps , to introduce essential interior singularities and preserve most input features. Our main idea is simple and intuitive: by inserting proper parameterization seams into the initial PolyCube-Map via novel PolyCube cutting operations, the mapping distortion can be reduced significantly. The cut-enhanced PolyCube-Map computation includes feature-aware PolyCube-Map construction and cut-enhanced PolyCube deformation. The former aims to preserve input feature edges during the initial PolyCube-Map construction. The latter introduces seams into the volumetric PolyCube shape by cutting it through selective PolyCube edges and deforms the modified PolyCube under the seamless constraints to compute a low-distortion PolyCube-Map. The hexahedral mesh induced by the final PolyCube-Map can be further enhanced by our mesh improvement algorithm. We validate the efficacy of our method on a collection of more than one hundred CAD models and demonstrate its advantages over other automatic all-hex meshing methods and padding strategies. The limitations of cut-enhanced PolyCube-Maps are also discussed thoroughly.

Precursor- and Time-Dependent Morphological Evolution of ZnO Nanostructures for Comparative Photocatalytic Activity and Adsorption Dynamics with Methylene Blue Dye.

Diverse ZnO nanostructures were successfully fabricated at 700 °C by direct annealing of 1D Zn(II) coordination polymer precursors, namely, [Zn2(bpma)2(adc)2]n, [Zn2(bpea)2(adc)2]n, and {[Zn2(bpta)2(adc)2]·2H2O}n. The effect of sacrificial ligands present in the precursors as well as a variation in the retention time (6–24 h) during their synthesis resulted in 0D nanospheres, 1D microrods, and 3D polyhedra (with a diamond-like structure) of ZnO. The as-synthesized ZnO nanostructures were characterized by field-emission scanning electron microscopy, transmission electron microscopy, X-ray diffractometry, diffuse reflectance spectroscopy, and Raman spectroscopy. The hexagonal crystal structure was confirmed for all the ZnO samples. A lattice spacing of 0.22 nm has been observed for nanospheres, whereas a lattice spacing of 0.26 nm has been observed for the polyhedra. Their Raman spectra confirm the wurtzite phase of ZnO. UV–vis spectra of ZnO nanostructures exhibit broad peaks in the range of 350–370 nm, and the band gap energies are found to be in the range of 3.02–3.20 eV. Based on the photoluminescence spectra photocatalytic activities of the as-synthesized ZnO nanostructures calcined for 12 h were tested with methylene blue (MB) as a contaminant in an aqueous solution. These results demonstrate that the photocatalytic efficiency of polyhedra is higher than those of nanospheres and microrods. The adsorption kinetics of MB dye by these nanostructures were studied by three different kinetic models—Elovich’s, intraparticle, and pseudo-second-order. The maximum rate of adsorption was observed with the intraparticle diffusion model.