Hexagonal Pattern Research Articles

The Impact of Marangoni and Buoyancy Convections on Flow and Segregation Patterns during the Solidification of Fe-0.82wt%C Steel.

Due to the high computational costs of the Eulerian multiphase model, which solves the conservation equations for each considered phase, a two-phase mixture model is proposed to reduce these costs in the current study. Only one single equation for each the momentum and enthalpy equations has to be solved for the mixture phase. The Navier-Stokes and energy equations were solved using the 3D finite volume method. The model was used to simulate the liquid-solid phase transformation of a Fe-0.82wt%C steel alloy under the effect of both thermocapillary and buoyancy convections. The alloy was cooled in a rectangular ingot (100 × 100 × 10 mm3) from the bottom cold surface to the top hot free surface by applying a heat transfer coefficient of h = 600 W/m2/K, which allows for heat exchange with the outer medium. The purpose of this work is to study the effect of the surface tension on the flow and segregation patterns. The results before solidification show that Marangoni flow was formed at the free surface of the molten alloy, extending into the liquid depth and creating polygonized hexagonal patterns. The size and the number of these hexagons were found to be dependent on the Marangoni number, where the number of convective cells increases with the increase in the Marangoni number. During solidification, the solid front grew in a concave morphology, as the centers of the cells were hotter; a macro-segregation pattern with hexagonal cells was formed, which was analogous to the hexagonal flow cells generated by the Marangoni effect. After full solidification, the segregation was found to be in perfect hexagonal shapes with a strong compositional variation at the free surface. This study illuminates the crucial role of surface-tension-driven Marangoni flow in producing hexagonal patterns before and during the solidification process and provides valuable insights into the complex interplay between the Marangoni flow, buoyancy convection, and solidification phenomena.

How to regulate pattern formations for malware propagation in cyber-physical systems.

Malware propagation can be fatal to cyber-physical systems. How to detect and prevent the spatiotemporal evolution of malware is the major challenge we are facing now. This paper is concerned with the control of Turing patterns arising in a malware propagation model depicted by partial differential equations for the first time. From the control theoretic perspective, the goal is not only to predict the formation and evolution of patterns but also to design the spatiotemporal state feedback scheme to modulate the switch of patterns between different modes. The Turing instability conditions are obtained for the controlled malware propagation model with cross-diffusion. Then, the multi-scale analysis is carried out to explore the amplitude equations near the threshold of Turing bifurcation. The selection and stability of pattern formations are determined based on the established amplitude equations. It is proved that the reaction-diffusion propagation model has three types of patterns: hexagonal pattern, striped pattern, and mixed pattern, and selecting the appropriate control parameters can make the pattern transform among the three patterns. The results of the analysis are numerically verified and provide valuable insights into dynamics and control of patterns embedded in reaction-diffusion systems.

Optimization of 3D printer settings for recycled PET filament using analysis of variance (ANOVA)

Fused Deposition Modeling (FDM) 3D printing creates components by layering extruded material. Printer parameters such as layer height and infill density can greatly impact the mechanical properties and quality of the printed parts. One critical factor to be considered in analysis is the anisotropy nature of printed components, considering all cross-sectional area (CSA) profiles for less than 100% infill density. This paper investigates the effect of the anisotropy nature of 3D printed CSA has on stress calculations and hence mechanical properties of the specimen through Design of Experiment (DOE). Analysis of variance (ANOVA) is utilised to evaluate the results. Printed specimens were tensile tested as per ASTM D638-14. Raw data was analysed using various CSA profiles, taking changes in infill density and layer height into account. Fixed parameter such as shell count, top and bottom layers, nozzle diameter, Hexagonal pattern were defined. Specimens Ultimate Tensile Strength (UTS) values increased on average by 30% using average profile CSA data compared to using external specimen dimensions. Further analysis assessing printer parameters affect on recycled Polyethylene Terephthalate (rPET) specimen's Young's Modulus (YM) and UTS was studied. One significant finding from this study suggests that the thickness of each layer has the most significant impact on the material properties of 3D printed rPET, as observed through the analysis of tensile test data obtained from 3D printed samples. A 3D printed rPET specimen with 30% infill density and 0.25 mm layer height has a higher YM (1175 MPa) and UTS (39 MPa) compared to a specimen with 75% infill density and 0.1 mm layer height (1159 MPa, 31 MPa). However careful interpretation of the results is required because for the same 30% infill parameter at 0.2 mm layer height the YM (936 MPa) and UTM (28 MPa) are significantly lower than at 0.25 mm layer height. If a higher value of YM and UTS is required an infill setting of 50% and layer height of 0.25 mm gave the highest values, YM (1330 MPa) and UTS (43 MPa).

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.

Turing patterns in a predator–prey model with double Allee effect

In this paper, a predator–prey model with double Allee effect and self-diffusion terms is considered. The stability of the coexisting equilibrium is studied by analyzing the eigenvalue spectrum, and the spatial Turing patterns are investigated by using the method of multiple scale analysis. The amplitude equation is obtained, which shows that the system supports patterns like spots, stripes, hexagonal patterns and mixed-mode patterns. The influence of double Allee effect in system is discussed by the comparison of bifurcation diagrams. Finally, the numerical simulations have verified the correctness of above theoretical analysis and tell how the double Allee effect plays an important role in biological universe.

Insights for improving the electromagnetic properties of conductive nanocomposites manufactured with carbon nanotubes

Additive manufacturing (AM) technologies offer many advantages that are attractive for electromagnetic compatibility (EMC) in industrial environments, and possibilities include customizable sizes and new complex internal shapes (infill) for parts. The polymeric nanocomposites with carbon-based nanomaterials, such as multi-walled carbon nanotubes (MWCNT), are of great interest and can be used for the development of functional electromagnetic components using the material extrusion (MEX) technique,. However, the literature lacks a deeper understanding of the relationship between the MEX process, the slicing parameters, the structure generated, and the electromagnetic behavior of the nanocomposite-based parts. This work studied the influence of building direction, various infill patterns, and orientations of acrylonitrile-butadiene-styrene copolymer (ABS)/MWCNT nanocomposite with 3 wt% of MWCNT on the manufacture of samples by additive manufacturing, with the evaluation of the electromagnetic interference shielding effectiveness (EMI SE) and reflection loss (RL) performances of the prepared materials. The correlation between geometric parameters and the EM response was explored and corroborated with computational simulations. The results pointed out that parts using the building direction (ZX and XY) may achieve similar shielding results depending mainly on the infill orientation. When the deposited filament (or the entire layer) is aligned with the electric field, the EM shielding behavior is maximized. In contrast, when the deposited filaments are orthogonal to the electric field, the behavior is impaired. The computational simulation of the rheological flow of the nanocomposite and the EM behavior corroborated these findings, and the MEX sample matched the attenuation of the injection molded sample behavior for a greater thickness (16 dB at 9 mm). Additionally, the RL behavior of the parts with different infill patterns and thicknesses was studied. These results indicated that the MEX process might be a promising way to promote the reflection loss (RL) behavior of conductive materials that, in bulk, would not promote such a good response. The best RL performance found was − 18 dB and 1.4 GHz bandwidth for the 50 wt% hexagonal infill pattern with an extra layer in the middle of the body sample.

Epitaxial Growth of 2D Binary Phosphides.

Combinations of phosphorus with main group III, IV, and V elements are theoretically predicted to generate 2D binary phosphides with extraordinary properties and promising applications. However, experimental synthesis is significantly lacking. Here, a general approach for preparing 2D binary phosphides is reported using single crystalline surfaces containing the constituent element of target 2D materials as the substrate. To validate this, SnP3 and BiP, representing typical 2D binary phosphides, are successfully synthesized on Cu2Sn and bismuthene, respectively. Scanning tunneling microscopy imaging reveals a hexagonal pattern of SnP3 on Cu2Sn, while α-BiP can be epitaxially grown on the α-bismuthene domain on Cu2Sb. First-principles calculations reveal that the formation of SnP3 on Cu2Sn is associated with strong interface bonding and significant charge transfer, while α-BiP interacts weakly with α-bismuthene so that its semiconducting property is preserved. The study demonstrates an attractive avenue for the atomic-scale growth of binary 2D materials via substrate phase engineering.

Full field-of-view hexagonal lattice structured illumination microscopy based on the phase shift of electro-optic modulators.

High throughput has become an important research direction in the field of super-resolution (SR) microscopy, especially in improving the capability of dynamic observations. In this study, we present a hexagonal lattice structured illumination microscopy (hexSIM) system characterized by a large field of view (FOV), rapid imaging speed, and high power efficiency. Our approach employs spatial light interference to generate a two-dimensional hexagonal SIM pattern, and utilizes electro-optical modulators for high-speed phase shifting. This design enables the achievement of a 210-µm diameter SIM illumination FOV when using a 100×/1.49 objective lens, capturing 2048 × 2048 pixel images at an impressive 98 frames per second (fps) single frame rate. Notably, this method attains a near 100% full field-of-view and power efficiency, with the speed limited only by the camera's capabilities. Our hexSIM demonstrates a substantial 1.73-fold improvement in spatial resolution and necessitates only seven phase-shift images, thus enhancing the imaging speed compared to conventional 2D-SIM.

Tailoring Resin–Metal Adhesion by Femtosecond Laser Surface Texturing

Epoxy resin wettability and adhesion on metal surfaces are of interest to composite manufacturing processes in two aspects: while higher adhesion is desired for composite to metal part bonding, lower adhesion is expected for metal tools used in the composite fabrication process. Among several surface modification techniques to achieve such increased/decreased adhesion strengths, femtosecond laser micromachining is a sustainable and scalable technique. Therefore, this study aims to explore epoxy resin adhesion behavior against femtosecond laser micromachined aluminum surfaces as a function of different microscale topographies. The texture types include microscale hexagonal and cylindrical hole patterns with different solid/air surface fractions and comparatively smaller‐scale laser‐induced periodic surface structures. Based on polished metal contact angle results, desired texture geometries are selected in a range to theoretically favor or inhibit resin penetration into microcavities. Theoretical predictions are derived from the capillary effect and Gibb's energy difference. The adhesion strength of resin to metal is examined by tensile tests. All the laser‐textured surfaces show considerably increased adhesion strengths compared to polished surfaces. Scanning electron microscopy and laser profilometry analysis on failed surfaces confirm resin penetration into all textures. Nevertheless, hexagonal holes, which exhibit the highest microcavity volume, show potential for air trapping.

PH-induced morphological transition of aggregates formed by miktoarm star polymers in dilute solution: a mesoscopic simulation study.

The self-assembly of miktoarm star polymers μ-A i (B(D)) j C k in a neutral solution and the pH-responsive behaviors of vesicles and spherical micelles in an acidic solution have been investigated by DPD simulation. The results show that the self-assembled morphologies can be regulated by the lengths of pH-responsive arm B and hydrophilic arm C, leading to the formation of vesicles, discoidal micelles, and spherical micelles in a neutral solution. The dynamic evolution pathways of vesicles and spherical micelles are categorized into three stages: nucleation, coalescence, and growth. Subsequently, the pH-responsive behaviors of vesicles and spherical micelles have been explored by tuning the protonation degree of pH-responsive arm B. The vesicles evolves from nanodisks to nanosheets, then to nanoribbons, as the protonation degree increases, corresponding to a decrease in pH value, while the spherical micelles undergoes a transition into worm-like micelles, nanosheets, and nanoribbons. Notably, the electrostatic interaction leads the counterions to form a regular hexagonal pattern in nanosheets, while an alternative distribution of charged beads has been observed in nanoribbons. Furthermore, the role of the electrostatic interaction in the morphological transition has been elucidated through the analysis of the distribution of positive and negative charges, as well as the electrostatic potential for associates.

A superamphiphobic surface with ordered hexagonal microstructures inspired by springtails

Inspired by springtails, we prepared an ordered hexagonal microscale and nanoparticle composite superamphiphobic surface, which can repel liquids with different surface tensions.

Investigation of Geometric and Hardness Parameters of Tank Track Grooves Equipped on Photovoltaic Cleaning Robot

The utilization of photovoltaic (PV) cleaning robots has proven to be an effective method for maintaining the conversion efficiency of utility-scale PV power plants by mitigating the impact of dust accumulation. However, ensuring the safe operation of these robots, resembling tanks in appearance, particularly in wet working conditions, relies heavily on their adherence to PV panels. This study focuses on assessing the slip resistance of candidate materials coated on endless polyurethane timing belts, which are equipped on PV cleaning robots to enable the efficient cleaning of uneven and misaligned PV arrays. A novel apparatus is proposed to evaluate the coefficient of static friction (COSF) of slip specimens, considering factors such as outsole patterns, area density, and shore hardness. The results highlight the significant influence of shore hardness and area density on the slip resistance of the specimens. Based on the findings, it is recommended to design track grooves with hexagon or zigzag patterns and maintain a low area density (e.g., 0.44 g·mm−2) to ensure the safe operation of PV cleaning robots, irrespective of the working conditions they encounter. By addressing the slip resistance challenge, this research contributes to the overall efficiency and reliability of PV cleaning robots, enhancing their performance in maintaining clean and optimal PV panel surfaces.

Oxidation-driven 2D LIPSS on amorphous Si films atop metal layers: The interplay of near-field and far-field effects

We investigate the formation of Laser-Induced Periodic Surface Structures (LIPSS) on amorphous Si films coated on Al using circularly polarized femtosecond lasers. By controlling laser fluence, we induce oxidation-based surface patterns, with their regularity governed by the interplay between near-field and far-field contributions. Achieving the right balance between these effects results in a consistent hexagonal pattern. Varying the underlying metal type further revealed its impact on pattern quality: strong far-field contributions led to irregular patterns, while dominant near-field effects resulted in extensive oxidation. Our study reveals the critical balance between near-field and far-field effects in optimizing 2D LIPSS patterns, emphasizing the role of the underlying metal.

Алгоритм лечения далеко зашедшей пролиферативной диабетической ретинопатии

Purpose. To develop an algorithm for the treatment of patients with advanced proliferative diabetic retinopathy with the determination of the stages of laser and surgical methods and evaluate its effectiveness. Material and methods. The study group included 38 patients (38 eyes) with type 1 diabetes mellitus (21 patients) and type 2 diabetes mellitus (17 patients, 16 of them with the insulin-requiring form of the disease). Patients age ranged from 24 to 75 years (41±8.6 years) old. All patients underwent staged treatment. Primary subtotal three-port 27 G vitrectomy was performed. Transpupillary patterned panretinal laser coagulation was performed at 1,5–2 months after the first stage of treatment. Panretinal laser coagulation was performed with a hexagonal matrix pattern with a laser spot diameter of 300 µm, exposure time of 30 ms on an Integre Pro Scan laser device (Ellex, Australia) with a wavelength of 561 nm using a panfundus lens. In cases of gas-air tamponade, panretinal laser coagulation was performed according to the same parameters in two sessions with an interval of 1–2 months between them, the average number of coagulates per session was 1053±107 applications. As the third stage of treatment, 1,5–2 months after panretinal laser coagulation, those patients whose vitreal cavity was tamponed with silicone oil underwent vitrectomy with the removal of silicone oil and it's replacement with a balanced solution. Results. The total number of treatment steps in the observation group (n=34) ranged from 1 to 5 and averaged 3±0.97. The time from primary vitrectomy followed by patterned panretinal laser coagulation to silicone oil removal was at average 3.7±0.48 months. Performing primary subtotal vitrectomy as the first stage of combined treatment made it possible achieve retinal attachment and its visualization throughout, to perform surgical intervention without massive endolaser coagulation, which reduced the duration of surgery and accelerated postoperative rehabilitation. The subsequent transpupillary panretinal laser coagulation of the retina in the pattern mode provided a dosed precision effect on the retina and made it possible perform the laser stage of treatment in one session. Conclusion. A step-by-step algorithm, including primary subtotal vitrectomy followed by simultaneous transpupillary pattern laser coagulation of the retina, is effective and safe in the treatment of proliferative diabetic retinopathy complicated by hemophthalmos. Key words: proliferative diabetic retinopathy, treatment algorithm, surgical treatment, laser treatment, vitrectomy, pattern laser coagulation

Anti-Adhesive Surfaces Inspired by Bee Mandible Surfaces.

Propolis, a naturally sticky substance used by bees to secure their hives and protect the colony from pathogens, presents a fascinating challenge. Despite its adhesive nature, honeybees adeptly handle propolis with their mandibles. Previous research has shown a combination of an anti-adhesive fluid layer and scale-like microstructures on the inner surface of bee mandibles. Our aim was to deepen our understanding of how surface energy and microstructure influence the reduction in adhesion for challenging substances like propolis. To achieve this, we devised surfaces inspired by the intricate microstructure of bee mandibles, employing diverse techniques including roughening steel surfaces, creating lacquer structures using Bénard cells, and moulding resin surfaces with hexagonal patterns. These approaches generated patterns that mimicked the bee mandible structure to varying degrees. Subsequently, we assessed the adhesion of propolis on these bioinspired structured substrates. Our findings revealed that on rough steel and resin surfaces structured with hexagonal dimples, propolis adhesion was significantly reduced by over 40% compared to unstructured control surfaces. However, in the case of the lacquer surface patterned with Bénard cells, we did not observe a significant reduction in adhesion.

Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm

To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ∼6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%–2%) is required to dramatically improve the wetting (5–20 times) compared to an unstructured electrode.

The Parasporal Body of Bacillus thuringiensis subsp. israelensis: A Unique Phage Capsid-Associated Prokaryotic Insecticidal Organelle.

The three most important commercial bacterial insecticides are all derived from subspecies of Bacillus thuringiensis (Bt). Specifically, Bt subsp. kurstaki (Btk) and Bt subsp. aizawai (Bta) are used to control larval lepidopteran pests. The third, Bt subsp. israelensis (Bti), is primarily used to control mosquito and blackfly larvae. All three subspecies produce a parasporal body (PB) during sporulation. The PB is composed of insecticidal proteins that damage the midgut epithelium, initiating a complex process that results in the death of the insect. Among these three subspecies of Bt, Bti is unique as it produces the most complex PB consisting of three compartments. Each compartment is bound by a multilaminar fibrous matrix (MFM). Two compartments contain one protein each, Cry11Aa1 and Cyt1Aa1, while the third contains two, Cry4Aa1/Cry4Ba1. Each compartment is packaged independently before coalescing into the mature spherical PB held together by additional layers of the MFM. This distinctive packaging process is unparalleled among known bacterial organelles, although the underlying molecular biology is yet to be determined. Here, we present structural and molecular evidence that the MFM has a hexagonal pattern to which Bti proteins Bt152 and Bt075 bind. Bt152 binds to a defined spot on the MFM during the development of each compartment, yet its function remains unknown. Bt075 appears to be derived from a bacteriophage major capsid protein (MCP), and though its sequence has markedly diverged, it shares striking 3-D structural similarity to the Escherichia coli phage HK97 Head 1 capsid protein. Both proteins are encoded on Bti's pBtoxis plasmid. Additionally, we have also identified a six-amino acid motif that appears to be part of a novel molecular process responsible for targeting the Cry and Cyt proteins to their cytoplasmic compartments. This paper describes several previously unknown features of the Bti organelle, representing a first step to understanding the biology of a unique process of sorting and packaging of proteins into PBs. The insights from this research suggest a potential for future applications in nanotechnology.

Numerical simulation of oil shale in-situ exploration productivity comparison between steam injection and electrical heating

Oil shale is an important alternative resource to the conventional oil and gas because of its rich reserves. The in-situ heating exploitation is the most promising method to produce oil from the oil shale, mainly including electrical heating and steam injection heating. However, to the best of our knowledge, a comprehensive comparison between these two kinds of heating methods is still absent, thus the comparison is necessarily conducted to provide suggestions on how to select heating modes for the oil shale in-situ exploitation. On this basis, a systematic comparison is presented between in-situ steam heating and electrical heating, including physical and process parameters, and then sensitivity analysis and optimization on key parameters are carried out. Simulation results show that steam injection heating is superior to electrical heating in output, energy consumption and production cycle. The flow rate and temperature of the injected steam and the specific heat capacity of oil shale are sensitive to productivity. The production will be increased with larger injection flow rate and temperature. The thermal conductivity and porosity are less sensitive to the mining efficiency compared to the injection flow rate and temperature. At the same time, different well pattern structures also have an impact on productivity, and the hexagonal well pattern has better productivity benefits than the triangular and quadrilateral well patterns. In the simulation case of this paper, the most conducive parameters for exploitation were derived as injection flow rate 0.20 kg/s, injection temperature 650 °C, specific heat capacity 1.5 kJ/(kg⋅K), thermal conductivity 0.5 W/(m⋅K), porosity 0.05. These results are expected to provide theoretical suggestions for improving the productivity efficiency of oil shale in-situ exploitation.

Unravelling diverse spatiotemporal orders in chlorine dioxide-iodine-malonic acid reaction-diffusion system through circularly polarized electric field and photo-illumination.

Designing and predicting self-organized pattern formation in out-of-equilibrium chemical and biochemical reactions holds fundamental significance. External perturbations like light and electric fields exert a crucial influence on reaction-diffusion systems involving ionic species. While the separate impacts of light and electric fields have been extensively studied, comprehending their combined effects on spatiotemporal dynamics is paramount for designing versatile spatial orders. Here, we theoretically investigate the spatiotemporal dynamics of chlorine dioxide-iodine-malonic acid reaction-diffusion system under photo-illumination and circularly polarized electric field (CPEF). By applying CPEF at varying intensities and frequencies, we observe the predominant emergence of oscillating hexagonal spot-like patterns from homogeneous stable steady states. Furthermore, our study unveils a spectrum of intriguing spatiotemporal instabilities, encompassing stripe-like patterns, oscillating dumbbell-shaped patterns, spot-like instabilities with square-based symmetry, and irregular chaotic patterns. However, when we introduce periodic photo-illumination to the hexagonal spot-like instabilities induced by CPEF in homogeneous steady states, we observe periodic size fluctuations. Additionally, the stripe-like instabilities undergo alternating transitions between hexagonal spots and stripes. Notably, within the Turing region, the interplay between these two external influences leads to the emergence of distinct superlattice patterns characterized by hexagonal-and square-based symmetry. These patterns include parallel lines of spots, target-like formations, black-eye patterns, and other captivating structures. Remarkably, the simple perturbation of the system through the application of these two external fields offers a versatile tool for generating a wide range of pattern-forming instabilities, thereby opening up exciting possibilities for future experimental validation.

Mechanical Properties and Fracture Resistance of 3D-Printed Polylactic Acid

Abstract 3D printing is a layer-by-layer deposition process, which results in highly anisotropic structures and contains interfaces. Complex shapes manufactured by 3D printing carry defects. Complete elimination of these defects and interfaces is not possible, and these defects degrade the mechanical properties. In the present study, mechanical properties of printed dog bone samples are quantified as a function of building parameters, in particular, filling patterns, raster angle, and orientation of build direction with respect to that of loading, in polylactic acid (PLA). The tensile strength of 3D-printed PLA is the same for hexagonal and linear pattern filling when the build direction is along thickness and width, and failure was initiated at the defects in the structure, while better overall toughness is offered by hexagonal pattern filling. Build direction along specimen gauge length gives very low tensile strength and toughness, and failure happens between the printing layers. To minimize the defects especially near the grip section, cuboid samples were first deposited and micro-machined by laser into dog bone shape to perform tension test. Tensile strength and elastic modulus of micro-machined samples are surprisingly lower, while failure strain is highest among line filling printed samples. Damage resistance was quantified in terms of work of fracture, and hexagonal filling provided better damage resistance than line filling patterns for conditions of 0 deg raster angle with respect to the crack, whereas line filling with 45 deg and 90 deg raster angle tolerated damage better than hexagonal filling.