Optimal Microstructure Research Articles

A Sustainable Microstructure Modification‐Based Design of Al‐Si Alloys for Energy Efficient Electric Power Transmission and Distribution

Power transmission and distribution systems need to be more efficient and sustainable to meet the growing electricity demand. The high conductivity of aluminum alloys is advantageous for power transmission. The present work demonstrates how the size, shape, and distribution of phases influence the electrical and thermal conductivity of a hypoeutectic Al‐Si alloy power connector. The addition of Al‐10 wt% Sr to Al‐10.5 wt% Si reduces the size of eutectic Si from 15 ± 8 μm to 0.75 ± 0.2 μm and β‐(Al‐Fe‐Si) phases from 52.85 ± 7 μm to 35.79 ± 3 μm, while slightly increasing the secondary dendrite arm spacing from 40.5 ± 3 μm to 55.2 ± 5 μm. These modifications increase the thermal conductivity from 111 to 127 W mK−1, which enhances the current density of the power connector assembly from 1.7 × 107 to 2.1 × 107 A m−2, improving its ampacity. Additionally, the Sr‐modified alloy exhibits superior corrosion resistance, with the corrosion rate decreases from 0.0416 to 0.012 mm year−1. These results are supported by finite element simulations and experimental validation, which show that microstructure optimization enhances electrical and thermal conductivity while reducing energy losses. This approach lowers the electricity demand, decreases greenhouse gas emissions, and minimizes the environmental impact of frequent replacements.

Design, development and performance of a Fe-Mn-Si-Cu alloy for bioabsorbable medical implants.

Bioabsorbable metallic alloys constitute a very challenging and innovative field, mainly aimed to develop the next generation of temporary medical implants. Degradation data, biological in vitro and in vivo tests are of major importance in particular for complex alloys, in which the individual element additions could enhance material performance and add functionalities. In this study, a novel Fe-Mn-Si-Cu alloy was carefully designed for vascular and blood-contact applications, and its microstructure, mechanical behavior, degradation behavior and biological performances were investigated accordingly. In previous studies, Mn and Si were found to be suitable elements to effectively enhance mechanical properties and accelerate corrosion rate in simulated body fluid. Cu was added for further grain refinement by the formation of small Cu-rich particles, potentially impacting mechanical properties and degradation behavior. In addition, the feasibility of inducing antibacterial effects in a Fe-Mn-Si-Cu alloy with low Cu content was investigated. The alloy was prepared firstly on a small scale by vacuum arc remelting, then on a larger scale by vacuum induction melting and converted into sheets by conventional thermomechanical processing techniques. Heat treatments were explored to find optimal microstructure conditions. The results confirm promising mechanical, degradation and biological performance in testing the material in in vitro conditions, showing that the degradation products are neither systematically cytotoxic nor have any hemotoxic effects. On the other hand, the expected antibacterial effects could not be confirmed.

Microstructure Optimization of Nickel–Nitrogen‐Doped Porous Nanofibers for Enhanced Electrochemical CO2 Reduction

AbstractThe utilization of renewable energy for electrocatalytic CO2 reduction (CO2RR) represents a significant advancement in green carbon conversion technologies. Single atom catalysts (SACs) featuring a transition metal‐nitride‐carbon (M‐Nx‐C) architecture exhibit catalytic activity for the reduction of CO2 to CO. However, the impact of the morphology of carbon supports, particularly their pore structure, on the electrocatalytic performance of CO2RR warrants further investigation. In this study, we fabricated a series of Ni‐based SACs supported by porous carbon nanofibers through electrospinning and sacrificial template method. We examined variations in microstructure of these porous carbon nanofiber carriers at different pyrolysis temperatures and elucidated their effects on CO2RR catalytic performance. The catalyst obtained at 1000 °C demonstrated efficient electrocatalysis for converting CO2 to CO due to its large specific surface area, abundant hierarchical pore structure, and high content of Ni‐Nx species resulting from both the sacrificial template method and high‐temperature pyrolysis. A Faradaic efficiency exceeding 90% was sustained across potentials ranging from −0.7 V to −1.3 V (versus RHE), with a peak efficiency reaching 96.1% at −1.0 V (versus RHE). Kinetic analysis indicated that this sample exhibited the highest reaction kinetics alongside minimal charge transfer resistance.

Machine Learning-Assisted Microstructural Quantification of Multiphase Cathode Composites in All-Solid-State Batteries: Correlation with Battery Performance.

Microstructure optimization and high-performance material development are crucial for improving the electrochemical performance of all-solid-state batteries (ASSBs). Researchers frequently record numerous micro-scale or nano-scale electron micrographs for unbiased post-mortem analysis, performance evaluation, and improvement of ASSBs. However, these micrographs are often underutilized and typically analyzed qualitatively without ensuring an accurate representation of the experimental objectives. This study explores machine learning (ML)-based quantitative analysis techniques using electron microscopy images, combined with a stereology-driven linear-intercept concept method and semantic segmentation, to extract quantitative microstructural parameters for optimizing ASSB performance. The applicability of ML-assisted image analytics is demonstrated by employing composite cathodes in ASSBs to achieve unbiased automation and deep semantic segmentation during microstructural characterization. Furthermore, the ramifications of this ML-assisted method are discussed, along with its advantages and disadvantages in battery research.

2D mechanical metamaterials synthesized by topology optimization in the different symmetry classes

Abstract The aim of this paper is to recourse to topology optimization method to synthesize mechanical matematerials, based on the topologial derivative. Material symmetries play a major role in the very definition and expression of the homogenized properties; the search of optimal microstructures is done in given symmetry classes characterized by invariants of the homogenized moduli. We synthesize thanks to this methodology periodic microstructures prone to auxetic and anti-auxetic behaviors, or with a very large or small bulk to shear modulus ratio.

Review of the Microstructural Impact on Creep Mechanisms and Performance for Laser Powder Bed Fusion Inconel 718.

Inconel 718 (IN718) is a polycrystalline nickel-based superalloy and one of the most widely used materials in the aerospace industry owing to its excellent mechanical performances at high temperatures, including creep resistance. Interest in additively manufactured components in aerospace is greatly increasing due to their ability to reduce material consumption, to manufacture complex parts, and to produce out-of-equilibrium microstructures, which can be beneficial for mechanical behavior. IN718's properties are, however, very sensitive to microstructural features, which strongly depend on the manufacturing process and subsequent heat treatments. Additive manufacturing and, more specifically, Laser Powder Bed Fusion (LPBF) induces very high thermal gradients and anisotropic features due to its inherently directional nature, which largely defines the microstructure of the alloy. Hence, defining appropriate manufacturing parameters and heat treatments is critical to obtain appropriate mechanical behavior. This review aims to present the main microstructural features of IN718 produced by LPBF, the creep mechanisms taking place, the optimal microstructure for creep strength, and the most efficient heat treatments to yield such an optimized microstructure.

Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.

Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation functionality. Here, we present an artificial intelligence inverse design paradigm for creating deployable implants as planar and tubular thermal mechanical metamaterials (thermo-metamaterials). These thermo-metamaterial implants exhibit tunable mechanical properties and volume change in response to temperature changes, enabling minimally invasive and personalized surgery. We begin by generating a large database of corrugated thermo-metamaterials with various cell structures and bending stiffnesses. An artificial intelligence inverse design model is subsequently developed by integrating an evolutionary algorithm with a neural network. This model allows for the automatic determination of the optimal microstructure for thermo-metamaterials with desired performance,i.e., target bending stiffness. We validate this approach by designing patient-specific spinal fusion implants and tracheal stents. The results demonstrate that the deployable thermo-metamaterial implants can achieve over a 200% increase in volume or cross-sectional area in their fully deployed states. Finally, we propose a broader vision for a clinically informed artificial intelligence design process that prioritizes biocompatibility, feasibility, and precision simultaneously for the development of high-performing and clinically viable implants. The feasibility of this proposed vision is demonstrated using a fuzzy analytic hierarchy process to customize thermo-metamaterial implants based on clinically relevant factors.

Optimization of microstructure to improve Si3N4 ceramics with thermal conductivity and mechanical properties: effect of Si and α-Si3N4 powder composition

The heat dissipation capacity and mechanical reliability of silicon nitride (Si3N4) ceramic substrates determine the service life of power devices. In this work, a two-step sintering method was designed to produce Si3N4 ceramics with excellent performance using Si and α-Si3N4 powders with different ratios as raw materials. The nitridation mechanism and the microstructural evolution mechanism were clarified. The in-situ-generated β-Si3N4 seeds regulated the microstructure of the post-sintered Si3N4 ceramics. The introduction of Si powder reduced the content of oxygen impurities and regulated the microstructure of Si3N4 ceramics, thereby improving thermal conductivity while maintaining excellent mechanical properties. When the mass ratio of Si powder nitridation to α-Si3N4 was 0.75, its thermal conductivity was 120W·m-1·K-1, fracture toughness was 11.92±0.36MPa·m1/2, and bending strength was 712±20.6MPa. This study provides a strategy to reduce the introduction of oxygen impurities while optimizing the microstructure to prepare Si3N4 ceramics with excellent performance.

Optimization of microstructure for HRE-free Nd-Fe-B magnets with improved properties

Optimization of microstructure for HRE-free Nd-Fe-B magnets with improved properties

Advanced phenomenological models guided heat treating processes for LPBF Ti-6Al-4V alloy

Ti-6Al-4V (Ti64) alloy produced by laser powder bed fusion (LPBF) technique consists of an α′-martensite phase, which is usually brittle. Hence, heat treatments are required to promote the α՛→α+β and/or α→β transformations for microstructural optimization to achieve balances between strength and ductility. To guide the selection of heat treatment parameters for the design of LPBF Ti64 microstructures exhibiting optimized strength and ductility, this work explores the suitability of a Johnson-Mehl-Avrami-Kolmogorov (JMAK) and Lifshitz-Slyozov-Wagner (LSW) models. The work showed that the JMAK model can effectively model the heat treatment processes to predict volume fraction of constituent phases in LPBF Ti64. The transformation kinetics was predicted by an extended non-isothermal JMAK model based on differential scanning calorimetry (DSC) experimental data recorded during continuous heating. Moreover, hardness, as a mechanical property index, was measured for a set of specimens. The hardness initially decreased, then remained constant, and finally slightly increased with the increase in β phase fraction and underlying evolution of microstructure. When the β phase fraction was small < 3%, hardness decreased with the continuous coarsening of α lath during heat treatment process. The measured hardness and α lath width for the specimens followed the Hall-Petch relationship. Moreover, the α lath width and heat treatment time at a given temperature were found to undergo the LSW model. Hardness became independent on the β phase fraction of 3-8%, owing to the competition between α lath coarsening and solution strengthening. The hardness slightly increased when the β phase fraction was greater than 8%, because solid solution strengthening of the α phase played a dominant role over the coarsening of α lath width. The experimentally verified JMAK and LSW models are therefore discussed as effective tools to guide the selection of heat treatment parameters for designing the microstructure and hardness/strength of LPBF Ti64 alloy.

Investigation of Mo microalloying-induced intragranular ferrite and grain refinement

In this work, the Mo microalloying-induced intragranular ferrite and grain refinement are studied through macroscopic experimental research and microstructural simulation. The microstructure and precipitates in high-strength low-alloy steel (DH36 steel) were characterised by an optical microscope and transmission electron microscope to investigate the effect of Mo on fine crystal strengthening and intragranular ferrite induction. It is demonstrated through first-principle calculations that the surface energy of the MoC(100) plane is the lowest and the structural stability is the best, and molecular dynamic simulations confirmed that the phenomena observed in TEM experiments: the α-Fe (100) surface is the optimal orientation surface of the MoC(100) surface. The solidification structure of DH36 steel during the continuous casting process was simulated based on the cellular automaton-finite element (CAFE) model. Based on these observations, solidification structure simulations confirmed the phenomena observed in metallographic experiments. Meanwhile, it is proposed that the grain refinement and microstructure optimisation effect can be controlled by Mo microalloy content, so as to provide important theoretical data for practical shipbuilding steel DH36 production and improvement of the continuous casting quality.

Fast-Charging Solid-State Li Batteries: Materials, Strategies, and Prospects.

The ability to rapidly charge batteries is crucial for widespread electrification across a number of key sectors, including transportation, grid storage, and portable electronics. Nevertheless, conventional Li-ion batteries with organic liquid electrolytes face significant technical challenges in achieving rapid charging rates without sacrificing electrochemical efficiency and safety. Solid-state batteries (SSBs) offer intrinsic stability and safety over their liquid counterparts, which can potentially bring exciting opportunities for fast charging applications. Yet realizing fast-charging SSBs remains challenging due to several fundamental obstacles, including slow Li+ transport within solid electrolytes, sluggish kinetics with the electrodes, poor electrode/electrolyte interfacial contact, as well as the growth of Li dendrites. This article examines fast-charging SSB challenges through a comprehensive review of materials and strategies for solid electrolytes (ceramics, polymers, and composites), electrodes, and their composites. In particular, methods to enhance ion transport through crystal structure engineering, compositional control, and microstructure optimization are analyzed. The review also addresses interface/interphase chemistry and Li+ transport mechanisms, providing insights to guide material design and interface optimization for next-generation fast-charging SSBs.

Fast simulation of the influence of a refractive free-form microstructure on a wave field based on scalar diffraction theory

We present a novel fast simulation approach to simulate the influence of refractive freeform microstructures on a wave field. The FRISP (Finite Refractive Index Selective Propagation) method combines the Rayleigh-Sommerfeld diffraction integral with a thin element approximation and provides a comprehensive framework for understanding the optical properties of these microstructures. The main advantage of this method is its reduced complexity, which leads to a remarkable reduction in computation time by more than two orders of magnitude compared to finite-difference time-domain (FDTD) methods. This efficiency facilitates the iterative optimization of refractive microstructures and thus represents a practical tool to improve this type of microstructures. The verification of the FRISP method is realized by comparing the focal position and spot size of refractive microstructures. For this purpose, we compare FDTD, Mie theory and experimental data on microspheres with the predictions of FRISP. This comparison demonstrates the robustness and reliability of the approach, emphasizes its validity and demonstrates it as a valuable tool for the design and analysis of microstructures.

Engineering the Microstructure and Spatial Bioactivity of MAP Scaffolds Instructs Vasculogenesis In Vitro and Modifies Vessel Formation In Vivo

AbstractIn tissues where the vasculature is either lacking or abnormal, biomaterials can be designed to promote vessel formation and enhance tissue repair. In this work, the microstructure and bioactivity of microporous annealed particle (MAP) scaffolds are independently tuned to guide cell growth in 3D and promote de novo assembly of endothelial progenitor‐like cells into vessels. Both in silico characterization and in vitro experimentation are implemented to elucidate an optimal scaffold formulation for vasculogenesis. It is determined that MAP scaffolds with pore volumes on the same order of magnitude as cells facilitate cell growth and vacuole formation. Spatial control over cell spreading is achieved by incorporating adhesive microgels in well‐mixed, heterogeneous MAP scaffolds. While it is demonstrated that integrin engagement is the primary driver of network formation in these materials, introducing adhesive microgels loaded with heparin nanoparticles leads to the formation of vascular tubes after 3 days in culture. It is then shown in vivo that this unique scaffold formulation enhances vessel maturation in a wound‐healing model and instructs differential vascular development in the tumor microenvironment. Taken together, this work determines the optimal microstructure and ligand presentation within MAP scaffolds that leads to vascular constructs in vitro and facilitates vessel formation in vivo.

Microstructure Optimization of Thermoelectric τ1-Al2Fe3Si3 via Graded Temperature Heat Treatments.

To investigate the relationship between microstructure, chemical composition, and thermoelectric properties, we have applied graded temperature heat treatments to recently developed τ1-Al2Fe3Si3-based thermoelectric (FAST) materials formed by a peritectic reaction. We investigated microstructures, chemical compositions, and Seebeck coefficients as continuous functions of heat treatment temperature. The τ1 phase can become p- and n-type semiconductors without doping by changing the Al/Si ratio. The Seebeck coefficient was maximized, exceeding |S| > 140 μVK-1 for both p- and n-type materials, by heat treatment at 1173 K for 24 h through microstructural optimization. These results show that combining the graded temperature heat treatments and spatial mapping measurements of thermoelectric properties gives effective routes to determine the suitable heat treatment temperature for materials with multiphase microstructure.

Optimization of Process Parameters and Microstructure of CoCrFeNiTiAl High-Performance High-Entropy Alloy Coating

CoCrFeNiTiAl high-entropy alloy coatings have been prepared by laser cladding technology based on response surface methodology (RSM). The results show that the effects of laser power, cladding speed, and pulse width on the dilution rate and microhardness of the high-entropy alloy coatings are investigated. Among the single-factor results, the laser power has the most significant effect on the properties of high-entropy alloy coatings, followed by the cladding speed, while the pulse width has no significant effect. In the interaction term analysis, the interaction term of laser power and pulse width has a remarkable effect on both output responses, whereas the interaction term of pulse width and cladding speed only has a considerable effect on microhardness, while the interaction term of laser power and cladding speed has an insignificant effect on both output responses. The optimum parameters for the preparation of high-performance high-entropy alloy coatings are found at laser power P = 676.73 W, cladding speed V = 5 mm/s, and pulse width P0 = 9 ms. The microstructures of the high-entropy alloy coating prepared with optimal process parameters have been characterized, which show that the metallurgical bonding between the cladding layer and the substrate is strong and without obvious defects such as porosity and cracks.

Optimization of mechanical properties and microstructure of marine soft soil solidified with industrial waste using the D-Optimal method

Optimization of mechanical properties and microstructure of marine soft soil solidified with industrial waste using the D-Optimal method

Grain Boundary Engineering Enhances the Thermoelectric Properties of Y2Te3

AbstractThe performance of thermoelectric materials is typically assessed using the dimensionless figure of merit, zT. Increasing zT is challenging due to the intricate relationships between electrical and thermal transport properties. This study focuses on Y2Te3‐based thermoelectric materials, which are predicted to be promising for high‐temperature applications due to their inherently low lattice thermal conductivity. A series of Y2+xTe3 compositions with excess Y is synthesized to explore the effects on electronic and structural characteristics. Density functional theory calculations suggest that additional Y atoms increase charge carriers, thereby enhancing electrical conductivity and boosting thermoelectric performance. X‐ray diffraction analysis reveals that the presence of excess Y reduces lattice volume and alters bonding structures. Furthermore, the addition of Bi significantly enhances the power factor by promoting the segregation of elemental Bi particles and the formation of Y‐Bi‐rich grain boundaries, which improve weighted mobility. This microstructural optimization leads to a fourfold increase in the Seebeck coefficient, resulting in a peak zT of 1.23 at 973 K and a predicted maximum conversion efficiency of 10.3% under a temperature difference of 673 K. These findings highlight the potential of Y2Te3 for high‐temperature thermoelectric applications and demonstrate the effectiveness of grain boundary engineering in enhancing thermoelectric performance.

An 808 line phasor-based dehomogenisation Matlab code for multi-scale topology optimisation

This work presents an 808-line Matlab educational code for combined multi-scale topology optimisation and phasor-based dehomogenisation titled deHomTop808. The multi-scale formulation utilises homogenisation of optimal microstructures to facilitate efficient coarse-scale optimisation. Dehomogenisation allows for a high-resolution single-scale reconstruction of the optimised multi-scale structure, achieving minor losses in structural performance, at a fraction of the computational cost, compared to its large-scale topology optimisation counterpart. The presented code utilises stiffness optimal Rank-2 microstructures to minimise the compliance of a single-load case problem, subject to a volume fraction constraint. By exploiting the inherent efficiency benefits of the phasor-based dehomogenisation procedure, on-the-fly dehomogenisation to a single-scale structure is obtained. The presented code includes procedures for structural verification of the final dehomogenised structure by comparison to the multi-scale solution. The code is introduced in terms of the underlying theory and its major components, including examples and potential extensions, and can be downloaded from Github.

Advances in Heat Treatment and Microstructural Optimization of Hadfield Steel for Enhanced Wear Resistance

Objective: This study aims to explore the impact of heat treatment processes on carbide formation in Hadfield steel, focusing on optimizing its microstructure and mechanical properties for industrial applications that require high wear resistance. Theoretical Framework: The research is grounded in theories of metallurgical transformation and work hardening, particularly in relation to the metastable austenitic structure of Hadfield steel, which transforms into martensite under impact. This transformation mechanism, alongside alloy composition and heat treatment, shapes the steel’s resistance to wear and mechanical strength. Method: A systematic literature review was conducted, encompassing 11 relevant studies on Hadfield steel from four scientific databases: Taylor &amp; Francis, Springer, Wiley, and ScienceDirect. The selected studies were analyzed using the PRISMA methodology to evaluate the influence of heat treatments—such as austenitization, quenching, and tempering—on carbide formation and microstructure. Results and Discussion: Findings reveal that specific heat treatments significantly enhance Hadfield steel’s wear resistance and strength. The influence of processes like austenitization on carbide dissolution and rapid cooling to avoid carbide precipitation has proven critical for the steel’s toughness. This discussion aligns the observed improvements with theoretical predictions and identifies challenges in carbide control for enhanced performance. Research Implications: The study provides practical insights for industries utilizing Hadfield steel in high-wear environments, such as mining and transportation, and proposes further research into innovative heat treatment strategies. Originality/Value: This study contributes novel perspectives on the optimization of Hadfield steel's heat treatment processes, potentially informing advanced manufacturing techniques to improve the steel’s durability and economic value in key industrial applications.