Microstructural Patterns Research Articles

Numerical Simulation for the Hard‐Tooth Surface Heat Treatment Process of 20CrMnTi Steel Spiral Bevel Gear Based on Multifield Coupling Model

To obtain ideal fatigue resistance, low‐carbon steel spiral bevel gears for axles generally undergo continuous carburizing‐quenching‐tempering heat treatment (hereinafter referred to as hard‐tooth surface heat treatment). Herein, on the basis of multifield coupling effects, a multifield coupling model of hard‐tooth surface heat treatment is established. The model considers the latent heat generated via phase transformation and the influence of surface carbon concentration on the temperature at which martensitic transformation commences (Ms). A numerical simulation and experimental verification are conducted on the hard‐tooth surface heat treatment process for the 20CrMnTi steel spiral bevel gear. Results show that the maximum relative errors in carbon concentration, hardness, retained austenite content, and residual stress between the predicted and measured values are 4.8, 4.3, 4.6, and 7.6%, respectively. In addition, the article investigates the microstructure and stress evolution patterns of the spiral bevel gear during quenching. The results reveal that Ms decreases with increasing carbon concentration on the gear surface, resulting in the martensite transformation on the surface lagging significantly behind that at the core. The proposed model provides a reference for developing a formulating strategy for a realistic hard‐tooth surface heat treatment process of spiral bevel gear.

Digitally Programmable Microphase Separation in Polymer Network Generates Microstructure Pattern.

Polymers with microstructure patterns are crucial to many applications, such as separation, optics, electronics, metamaterials, etc. However, introducing microstructure patterns with diverse morphologies and feature sizes ranging from nanometers to micrometers into large-area polymers remains a significant challenge. Here, we design a material system that enables digital programming microphase separation in a polymer network to generate microstructure patterns. The polymer network is engineered to allow digital programming of local modulus, which arrests the length scale of microphase separation to generate various microstructures. These local modulus-regulated microstructures exhibit either bicontinuous or sea-island morphology and have various feature sizes ranging from ∼100 nm to several micrometers. Using household devices of an ink printer and an ultraviolet light lamp, the microstructure patterns can be programmed with fine resolutions (∼100 μm) over large areas (≫100 mm). The locally varied microstructures have different capabilities to scatter light and result in a visible pattern. We further demonstrate this design with a soft anticounterfeiting device. This approach of digital programming microphase separation in polymer networks is applicable to various polymers and provides a platform for designing many other functional devices.

Multivariate patterns linking brain microstructure to temperament and behavior in adolescent eating disorders.

Eating disorders (EDs) are multifaceted psychiatric disorders characterized by varying behaviors, traits, and cognitive profiles thought to drive symptom heterogeneity and severity. Non-invasive neuroimaging methods have been critical to elucidate the neurobiological circuitry involved in ED-related behaviors, but often focused on a limited set of regions of interest and/or symptoms. The current study harnesses multivariate methods to map microstructural and morphometric patterns across the entire brain to multiple domains of behavior and symptomatology in patients. Diffusion-weighted images, modeled with restriction spectrum imaging, were analyzed for 91 adolescent patients with an ED and 48 healthy controls. Partial least squares analysis was applied to map 38 behavioral measures (encompassing cognition, temperament, and ED symptoms) to restricted diffusion in white matter tracts and subcortical structures across 65 regions of interest. The first significant latent variable explained 46.9% of the covariance between microstructure and behavior. This latent variable retained a significant brain-behavior correlation in held-out data, where an 'undercontrolled' behavioral profile (e.g., higher emotional dysregulation, novelty seeking; lower effortful control and interoceptive awareness) was linked to increased restricted diffusion across white matter tracts, particularly those joining frontal, limbic, and thalamic regions. Individually-derived brain and behavior scores for this latent variable were higher in patients with binge-purge symptoms, compared to those with only restrictive eating symptoms. Findings demonstrate the value of applying multivariate modeling to the array of brain-behavior relationships inherent to the clinical presentation of EDs, and their relevance for providing a neurobiologically-informed model for future clinical subtyping and prediction efforts.

Automated de novo design of architectured materials: Leveraging eXplainable Artificial Intelligence (XAI) for inspiration from stochastic microstructure outliers

Engineered architectured Materials, such as metamaterials with periodic patterns, achieve superior properties compared with their stochastic counterparts, such as the random microstructures found in natural materials. The primary research question focuses on the feasibility of learning advantageous microstructural features from stochastic microstructure samples to facilitate the generative design of periodic microstructures, resulting in unprecedented properties. Instead of relying on brainstorming-based, ad hoc design inspiration approaches, we propose an eXplainable Artificial Intelligence (XAI)-based framework to automatically learn critical features from the exceptional outliers (with respect to properties) in stochastic microstructure samples, enabling the generation of novel periodic microstructure patterns with superior properties. This framework is demonstrated on three benchmark cases: designing 2D cellular metamaterials to maximize stiffness in all directions, to maximize the Poisson’s ratio in all directions, and to minimize the thermal expansion ratio. The effectiveness of the design framework is validated by comparing its novel microstructure designs with known stochastic and periodic microstructure designs in terms of the properties of interest.

Microstructural asymmetry in the human cortex

The human cerebral cortex shows hemispheric asymmetry, yet the microstructural basis of this asymmetry remains incompletely understood. Here, we probe layer-specific microstructural asymmetry using one post-mortem male brain. Overall, anterior and posterior regions show leftward and rightward asymmetry respectively, but this pattern varies across cortical layers. A similar anterior-posterior pattern is observed using in vivo Human Connectome Project (N = 1101) T1w/T2w microstructural data, with average cortical asymmetry showing the strongest similarity with post-mortem-based asymmetry of layer III. Moreover, microstructural asymmetry is found to be heritable, varies as a function of age and sex, and corresponds to intrinsic functional asymmetry. We also observe a differential association of language and markers of mental health with microstructural asymmetry patterns at the individual level, illustrating a functional divergence between inferior-superior and anterior-posterior microstructural axes, possibly anchored in development. Last, we could show concordant evidence with alternative in vivo microstructural measures: magnetization transfer (N = 286) and quantitative T1 (N = 50). Together, our study highlights microstructural asymmetry in the human cortex and its functional and behavioral relevance.

Enhancing CMP Performance of Micro-Structured Pad Patterns: CFD Simulations and Experimental Evaluations

Enhancing CMP Performance of Micro-Structured Pad Patterns: CFD Simulations and Experimental Evaluations

Prediction of microstructural evolution of multicomponent polymers by Physics-Informed neural networks

As emerging concepts, leveraging physical information with machine learning to construct hybrid models enables a scientific data-driven paradigm for the investigation of complex kinetic issues in the field of polymer science. Herein, the model of physics-informed neural networks (PINNs), integrating advantages of neural networks with physics-based knowledge, is extended to predict the spatiotemporal patterns of phase-separated microstructures of multicomponent polymers. It is demonstrated that the PINN-based data-driven model can achieve the forward, backward and bidirectional predictions of spatiotemporally phase-separated patterns of homopolymer blends. All predicted patterns reveal a high accuracy and robustness of PINN-based data-driven model by leveraging a small amount of training data. Particularly, the PINN-based method can be harnessed to infer the latent physical law about the growth kinetics of phase-separated microstructures. In addition, PINN-based data-driven model can also be generalized to forecast the spatiotemporal patterns of microphase-separated nanostructures of block copolymers and infer their growth kinetics. Our study opens the possibility of learning non-equilibrium phenomena of complex polymer systems from only a few snapshots of microstructural evolution.

Effect of ultrasound power on moisture status change of apple by contact ultrasound reinforced far-infrared radiation drying

To explore the effect of ultrasound power on internal water change of apple dried by contact ultrasound enhanced far-infrared radiation drying (CUFRD), the drying characteristics, microstructure, moisture migration, and molecular vibration patterns of apple slices subjected to this process at different ultrasound powers were investigated using low-field nuclear magnetic resonance (LF-NMR), Near-infrared (NIR) and two-dimensional(2D) correlation analysis. With the increase of contact ultrasound (CU) power, the drying times of apple were shortened by 8.69% to 17.39%, respectively. Scanning electron microscopy (SEM) observation indicated that higher CU power resulted in an increase in the number of microporous channels and pore diameter within apple’s internal tissue. The findings of LF-NMR clarified that free water content kept decreasing, while the content of semi-bound water initially increased and then reduced. Magnetic resonance imaging (MRI) images illustrated that higher CU power corresponded to a faster decrease in the redness value of the H+ density map of apple during drying. 2D correlation analysis revealed that the changes in the O-H bonds of apple were prioritized over the C-H bonds during drying process. NIR spectroscopy and LF-NMR heterogeneous correlation spectrograms demonstrated that at wavelengths of 950, 1450, and 1680 nm, the order of changes in water-related functional groups was quadruple-frequency O-H > combination of the first overtone of O-H stretching and OH-bending band > double-frequency C-H. Moreover, with increasing CU power, the vibration of hydrogen-containing functional groups intensified, leading to increased water activity. Thus, CU application could significantly enhance the CUFRD process of apple slices.

Concept of a Cyber–Physical System for Control of a Self-Cleaning Aquaponic Unit

The article aims to present a cyber–physical system (CPS) to support the cultivation of aquaculture in a closed aquaponic system using the deep-water culture (DWC) method. The CPS uses precision sensors as TriOxmatic 700 IQ (for dissolved oxygen and water temperature), AmmoLyt Plus 700 IQ (for ammonium), NiCaVis 701 IQ NI (for nitrites and nitrates), SensoLyt® 700 IQ (for pH), and SL-M5 (for water level). It is built with a Raspberry Pi 4, 8 GB as a server, OpenHAB 3.0 software, and other specialized software for measuring water parameters. Some of the parameters are maintained completely autonomously, while others are indirectly controlled. Basic knowledge of hydroponics and aquaculture is required to set up the system, but day-to-day maintenance can be carried out by employees who receive instructions from the CPS. A method for the physical modification of the fish tank surface by using laser processing is proposed. This results in a change in surface topography (creating diverse microstructure patterns) and its roughness, which is of crucial importance for the bacterial adhesion mechanism.

Sex-Specific Association Patterns of Bone Microstructure and Lower Leg Arterial Calcification

In conversations about bone loss and the importance of calcium homeostasis, patients frequently inquire about the association with arterial calcifications. Although a relationship between bone loss and the occurrence of vascular calcifications is suspected, it is not yet fully investigated and understood. This study aims to analyze associations between bone mineralization, structure, and vascular calcification at the lower leg in patients with low bone mineral density in HR-pQCT. We retrospectively analyzed 774 high-resolution quantitative computed tomography (HR-pQCT) scans of the distal tibia for the presence of vascular calcifications. After sex-specific propensity score matching for age and BMI to account for confounders, 132 patients remained for quantification of bone microstructure, bone density, lower leg arterial calcification (LLAC), and laboratory parameters of bone turnover. The interactions between bone parameters and vascular calcification were quantified by regression analyses. The calcium metabolism was not different between individuals with and without LLAC, nor oral calcium supplementation. Female patients with LLAC had a higher cortical perimeter (p = 0.016) compared to female patients without LLAC, whereas male patients with LLAC had lower cortical pore diameter than male patients without LLAC (p = 0.027). The appearance of LLAC was sex specifically associated with bone parameters. In female patients, only plaque density was associated with HR-pQCT bone parameters and age, whereas in male patients, plaque volume was associated with HR-pQCT parameters of the distal tibia. Female patients exhibit an increasing plaque density depended on age and trabecular thinning. Decreasing cortical pore diameter and trabecular number along with increasing bone mineralization are linked to increasing plaque volume in male patients.

Mechanical Characteristics of Bivalve (Mollusc) Shells from the East Coast of India: Implications and Their Significance on the Survival Strategy

Due to natural selection, an increase in biotic and abiotic factors develops an adaptive response in bivalves (molluscs) for survival. Morphological variation in a bivalve is strongly correlated with the changes in the structural and compositional properties of a shell. Therefore, the mechanical characteristics of a shell reflect its morpho-functional adaptation against predation and ecological stresses. An initial investigation into the primary mechanical attributes of predominant bivalve shells from the east coast of India, Tegillarca granosa, Meretrix meretrix, Sunetta meroe, Mactra turgida and Donax scortum, has been documented in this study. The quantitative assessment of the centreline thickness, Vickers hardness and density variation of the shells were measured and correlated along with the preliminary investigation of the microstructural patterns. The results from our study are in agreement with the most vulnerable region of a shell, located just below the umbonal zone, which has been verified through predatory boreholes in other studies. Our data shows a high correlation between shell hardness and density, which could also be the potential properties to consider in detail for future studies, apart from the shell thickness, which could provide a broader perspective on the stability of bivalve shells. Different microstructural patterns observed in the species could be phylogenetically driven based on their life modes.

Design of bimetallic interpenetrating biomimetic structures and additive-casting synergetic manufacturing

Inspired by biological materials like shell nacre, biphase interpenetrating materials with alternating soft and hard phases significantly enhance mechanical properties. However, their application in metallic materials is still unexplored. This study investigates the microstructure and fracture patterns of steel/aluminum interpenetrating composites with a Diamond TPMS structure, fabricated via vacuum infiltration casting. We found that steel and aluminum form a biomimetic "brick-and-mortar" structure under the Diamond framework, significantly enhancing the composites' ductility and strength. The interfacial bonding layer, composed of Fe2Al5, Al8Fe2Si, and Al4.5FeSi, shows a hardness far exceeding the adjacent base materials. This hardness increases unevenly with distance from the interface. Tensile tests reveal that structurally periodic interpenetrating materials outperform both trapezoidal interpenetrating and planar materials. Upon fracturing, cracks initially form at the interfacial bonding layer and gradually spread into the interpenetrating region. Subsequently, under tensile and shear stress from mechanical interlocking, brittle fractures develop between aluminum components. The crack then extends into the steel framework, causing ductile fractures and complete failure of the composite.

Yttrium cuprates modification in linear generator application for power generation

Abstract Yttrium barium copper oxide (YBCO) is used for special applications in linear generators because of its excitation loss, lower weight, and higher efficiency. These qualities enable the compound to operate better than the conventional copper wire coil in the stator unit of the linear generator. However, the continuous use of YBCO in linear generators has a fundamental challenge that affects industrial production and material stability after prolonged use. This paper seeks to sustain the adoption of YBCO by improving its quality for linear generator applications. The yttrium cuprates modification (YBYbCO) was synthesized using the solid-state reaction technique by doping YBCO with ytterbium. The crystalline structure, microstructural pattern, and stability of the new sample were adequately measured and found to be structurally stable to ensure durability. It was reported that applying YBYbCO in the linear generator would lead to a 200% increase in energy generation. The higher number of particles and lower individual particulate resistance enable it to withstand chemical pressure, thereby prolonging the lifespan of the linear generator.

Elimination of the Solid Graininess Issue with Different Micro-Pattern Structures at Flexo Printing

Flexo printing is a relief printing system, and ink transfers on the solid areas are not transferring well during the printing. That is why graininess is increasing and pinholes are occurring on the solid areas. This is a well-known issue in the flexo printing system. Micro-patterns usually eliminate these pinholes. Using correct micro-patterns allows homogeneous ink laydown and increases solid ink density. Micro-pattern holes behave like gravure cylinders on plate surfaces, and this makes for better ink transfer to the substrate. In this study, a more successful micro-pattern structure than the ones currently used was found by examining the solid ink density (SID) values and ink laydown obtained from the structure by producing eight different micro-pattern structures of 1000 LPI and 1500 LPI (line per inch) pattern screen frequencies with the same polymer structure and type. Densitometric values of solid prints made with the developed micro-patterns were measured. By eliminating the pinholes formed in solid prints and at the screen dot shapes, the ink is distributed more homogeneously without graininess. It has been determined that this results in a more stable measurement of ink density and eliminates the measurement of excess ink and low density.

Exposure to multiple ambient air pollutants changes white matter microstructure during early adolescence with sex-specific differences

BackgroundAir pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex.MethodsWe investigate sex-stratified effects of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at ages 9–10 years on longitudinal patterns of white matter microstructure over a 2-year period. Diffusion-weighted imaging was collected on 3T MRI scanners for 8182 participants (1–2 scans per subject; 45% with two scans) from the Adolescent Brain Cognitive Development (ABCD) Study®. Restriction spectrum imaging was performed to quantify intracellular isotropic (RNI) and directional (RND) diffusion. Ensemble-based air pollution concentrations were assigned to each child’s primary residential address. Multi-pollutant, sex-stratified linear mixed-effect models assessed associations between pollutants and RNI/RND with age over time, adjusting for sociodemographic factors.ResultsHere we show higher PM2.5 exposure is associated with higher RND at age 9 in both sexes, with no significant effects of PM2.5 on RNI/RND change over time. Higher NO2 exposure is associated with higher RNI at age 9 in both sexes, as well as attenuating RNI over time in females. Higher O3 exposure is associated with differences in RND and RNI at age 9, as well as changes in RND and RNI over time in both sexes.ConclusionsCriteria air pollutants influence patterns of white matter maturation between 9–13 years old, with some sex-specific differences in the magnitude and anatomical locations of affected tracts. This occurs at concentrations that are below current U.S. standards, suggesting exposure to low-level pollution during adolescence may have long-term consequences.

Unraveling the orientation-dependent mechanics of dental enamel in the red-necked wallaby

Dental enamels of different species exhibit a wide variety of microstructural patterns that are attractive to mimic in bioinspired composites to simultaneously achieve high stiffness and superior toughness. Non-human enamel types, however, have not yet received the deserved attention and their mechanical behaviour is largely unknown. Using nanoindentation tests and finite element modelling, we investigate the mechanical behaviour of Macropus rufogriseus enamel, revealing a dominating influence of the microstructure on the effective mechanical behaviour and allowing insight into structural dependencies. We find a shallow gradient in stiffness and low degree of anisotropy over the enamel thickness that is attributed to the orientation and size of microstructural features. Most notably, M. rufogriseus’s modified radial enamel has a far simpler structural pattern than other species’, but achieves great property amplification. It is therefore a very promising template for biomimetic design. Statement of significanceThe diversity of dental enamel structures in different species is well documented, but the mechanical behaviour of non-human enamel types is largely unknown. In this work, we investigate the microstructure and structure-dependent mechanical properties of marsupial enamel by nanoindentation and finite element simulations. Combining these methods gives valuable insights into the performance of modified radial enamel structures. Their stiffness and toughness stems from a unique structural design that is far less complex than well-studied human enamel types, which makes it a uniquely suitable template for biomimetic design.

Exploring large language models for microstructure evolution in materials

There is a significant potential for coding skills to transition fully to natural language in the future. In this context, large language models (LLMs) have shown impressive natural language processing abilities to generate sophisticated computer code for research tasks in various domains. We report the first study on the applicability of LLMs to perform computer experiments on microstructure pattern formation in model materials. In particular, we exploit LLM’s ability to generate code for solving various types of phase-field-based partial differential equations (PDEs) that integrate additional physics to model material microstructures. The results indicate that LLMs have a remarkable capacity to generate multi-physics code and can effectively deal with materials microstructure problems up to a certain complexity. However, for complex multi-physics coupled PDEs for which a detailed understanding of the problem is required, LLMs fail to perform the task efficiently, since much more detailed instructions with many iterations of the same query are required to generate the desired output. Nonetheless, at their current stage of development and potential future advancements, LLMs offer a promising outlook for accelerating materials education and research by supporting beginners and experts in their physics-based methodology. We hope this paper will spur further interest to leverage LLMs as a supporting tool in the integrated computational materials engineering (ICME) approach to materials modeling and design.

Preparation of fused silica glass micropatterns via gel method using quartz fiber as reinforcer

The preparation of fused silica glass with microstructural patterns has attracted considerable interest, and the process chain of using nano-silica powders mixed with organic polymers to prepare composites for molding, degreasing, and sintering provides a good solution. However, the potential negative effects of organic residues cannot be avoided. In this study, a pattern stencil replication method with silica gel using high-purity quartz fibers as reinforcement is proposed for preparing micropatterned fused silica glass. The microscopic morphology and mechanical properties before and after silica gel drying and the optical properties of fused silica glass obtained by sintering were evaluated via transmission electron microscopy), three-point bending strength test, scanning electron microscopy, X-ray diffraction spectrum analysis, ultraviolet–visible and infrared measurements. The results showed that quartz fiber as a reinforcer could shorten the drying time of the gel and did not degrade the quality of the fused silica glass obtained by sintering. Laser confocal test results showed that microlens arrays were generated by template replication, demonstrating the feasibility of molding fused silica lens arrays with small feature sizes and providing new ideas for the preparation of bulk fused silica glass or micropatterned glass.

Monotonic tensile and cyclic deformation of a Ni-based single crystal superalloy with anisotropic microstructural rafting patterns at high temperature: Experiment and constitutive modelling

Monotonic tensile and cyclic deformation behaviours are investigated under different microstructural rafting states of a SC Ni-based superalloy, with emphasis on the influences of the rafting extent, type and loading orientation. The deformed microstructures and the dislocation configurations are characterized to give a micro-based understanding on the varying of deformation behaviours due to rafting. It is found that the decreases in the initial yield point and cyclic stress amplitude are only related to the rafting extent. Nevertheless, the rafting type (namely, the plate-like and needle-like morphology) has an undeniable contribution to the shape of hysteresis loops, where the plate-like rafting morphology results in more significant Bauschinger effect than needle-like rafting morphology. The variation of monotonic and cyclic deformation induced by rafting shares affinity with the alteration of internal stress and the movement of dislocations. Afterwards, a microstructure-sensitive constitutive model with two-phase flow rules has been developed. The effect of rafting on the monotonic and cyclic stress-strain responses is captured by introduce a series of microscopic mechanisms and a micromechanics-based back stress model that considers the morphology and size of the γ'/γ two-phase structures. The developed model is used to simulate the macroscopic stress-strain responses of the SC Ni-based superalloy under different rafting states. Model predictions are in good agreement with tests, capturing the reduction of cyclic stress amplitudes and the change in hysteresis loops. Finally, the impacts of the two-phase flow rules and the micromechanics-based back stress on the simulation capability have been discussed.

Physicochemical, functional, and nutraceutical properties of Spirulina and Chlorella biomass: A comparative study

This comparative study investigates the physicochemical, functional, and nutraceutical properties of Spirulina (Arthrospira platensis) and Chlorella sp. biomass, two of the most prevalent microalgae species. We assessed their proximate composition, pH, acidity, color, granulometry, microstructure (SEM), functional groups (FTIR), crystallinity (XRD), and thermal stability (GTA). Functional properties were thoroughly examined, including bulk density, water and oil holding capacities, and gelling, foaming, and emulsifying capabilities. Additionally, the study quantified the content of pigments, phenolic compounds, carotenoids, and flavonoids and evaluated antioxidant activity. Our findings indicate that Spirulina biomass exhibits higher protein and ash content, whereas Chlorella biomass surpasses phenolic compounds, carotenoids, and antioxidant activity. Notable differences were observed in their microstructure and thermal degradation patterns. Both biomasses demonstrated considerable potential as functional ingredients, owing to their superior water and oil retention, foaming, emulsifying, and gelling properties. This investigation underscores the distinct physicochemical and nutraceutical profiles of Spirulina and Chlorella biomass, highlighting their significant applicability in the food industry for developing novel value-added food products.