Microstructural Design Research Articles

Significance of microstructural defect-tolerant in the battle for survival: Mantis shrimp VS. Nacre

Mantis shrimps use their robust claws to repeatedly strike and break the shells of bivalves during predation without sustaining damage themselves. It appears to be a confrontation between the bouligand microstructure and the brick-and-mortar microstructure of the nacre layer. In the daily struggle for survival, defects are inevitably introduced. To elucidate the mechanical mechanisms exhibited by the two microstructures in the struggle for survival, thus a bold conjecture was proposed: the bouligand structure exhibits less sensitivity to random defects compared to the brick-and-mortar structure, enabling mantis shrimps to survive in the battle for existence. To verify this hypothesis, numerical models of bouligand and brick-and-mortar microstructures were established considering interfacial random defects. The results indicated that for various defect volume fraction, the bouligand structure demonstrates superior mechanical performance compared to the brick-and-mortar structure. In terms of peak load and damage dissipation energy, the bouligand structure exhibits higher tolerance to interfacial random defects than the brick-and-mortar structure, delaying the occurrence of damage in the Bouligand structure while prematurely inducing damage in the brick-and-mortar structure. This study not only reveals the mechanical mechanisms behind the advantages of biological microstructures in the struggle for survival but also provides technical references for future biomimetic microstructure designs.

Molecular Dynamics Study on the Mechanical Behaviors of Nanotwinned Titanium

Titanium and titanium alloys have been widely applied in the manufacture of aircraft engines and aircraft skins, the mechanical properties of which have a crucial influence on the safety and lifespan of aircrafts. Based on nanotwinned titanium models with different twin boundary spacings, the impacts of different loadings and twin boundary spacings on the plastic deformation of titanium were studied in this paper. It was found that due to the different contained twin boundaries, the different types of nanotwinned titanium possessed different dislocation nucleation abilities on the twin boundaries, different types of dislocation–twin interactions occurred, and significant differences were observed in the mechanical properties and plastic deformation mechanisms. For the {101-2} twin, basal plane dislocations were likely to nucleate on the twin boundary. The plastic deformation mechanism of the material under tensile loading was dominated by partial dislocation slip on the basal plane and face-centered cubic phase transitions, and the yield strength of the titanium increased with decreasing twin boundary spacing. However, under compression loading, the plastic deformation mechanism of the material was dominated by a combination of partial dislocation slip on the basal plane and twin boundary migration. For the {101-1} twin under tensile loading, the plastic deformation mechanism of the material was dominated by partial dislocation slip on the basal plane and crack nucleation and propagation, while under compression loading, the plastic deformation mechanism of the material was dominated by partial dislocation slip on the basal plane and twin boundary migration. For the {1124} twin, the interaction of its twin boundary and dislocation could produce secondary twins. Under tensile loading, the plastic deformation mechanism of the material was dominated by dislocation–twin and twin–twin interactions, while under compression loading, the plastic deformation mechanism of the material was dominated by partial dislocation slip on the basal plane, and the product of the dislocation–twin interactions was basal dislocation. All these results are of guiding value for the optimal design of microstructures in titanium, which should be helpful for achieving strong and tough metallic materials for aircraft manufacturing.

Unveiling the quantitative relationship between microstructural features and quasi-static tensile properties in dual-phase titanium alloys based on data-driven neural networks

The quasi-static mechanical properties of α+β dual-phase titanium alloys are susceptible to their microstructural features, presenting a complex, high-dimensional nonlinear relationship, which hinders the rapid development of high-performance materials. In this work, 4065 micro-representative models were virtually constructed with varying volume fractions of α and β phases and characteristic dimensions via high-throughput finite element simulation, incorporating a cohesive zone model to simulate the interfaces between the two phases. Especially, the established representative models were experimentally verified by two groups of real material microstructures, and the results showed that the relative errors were not more than 9.5 % in microstructural characteristics and quasi-static mechanical properties. Afterward, a neural network model was developed to correlate the quasi-static tensile properties with the microstructural features of the dual-phase TC6 titanium alloys, achieving an 88.2 % accuracy in predicting overall mechanical performance. Utilizing the Shaply Additive Explanation method, it was found that the primary α phase's volume fraction and the secondary α phase's width were the most significant microstructural features affecting quasi-static strength. Specifically, the volume fraction of the primary α phase and the width of the secondary α phase negatively affected strength, while the width of the secondary α phase positively influenced plasticity. Notably, the primary α phase's volume fraction had a quadratic curve pattern of influence on plasticity. The intrinsic mechanisms behind these laws were further revealed based on local stress-strain responses and crack propagation analysis. Ultimately, the optimal microstructural features with strength-plasticity balance were identified through the lower threshold method: a secondary α phase width of about 1 μm and a primary α phase volume fraction ranging from 0.1 to 0.2, effectively facilitating microstructure design.

Minimizing Redundancy and Data Requirements of Machine Learning Potential: A Case Study in Interface Combustion.

The machine learning potential has emerged as a promising approach for addressing the accuracy-versus-efficiency dilemma in molecular modeling. Efficiently exploring chemical spaces with high accuracy presents a significant challenge, particularly for the interface reaction system. This study introduces a workflow aimed at achieving this goal by incorporating the classical SOAP descriptor and practical PCA strategy to minimize redundancy and data requirements, while successfully capturing the features of complex potential energy surfaces. Specifically, the study focuses on interface combustion behaviors within promising alloy-based solid propellants. A neural network potential model tailored for modeling AlLi-AP interface reactions under varying conditions is constructed, showcasing excellent predictive capabilities in energy prediction, force estimation, and bond energies. A series of large-scale MD simulations reveal that Li doping significantly influences the initial combustion stage, enhancing reactivity and reducing thermal conductivity. Mass transfer analysis also highlights the considerably higher diffusion coefficient of Li compared to Al, with the former being three times greater. Consequently, the overall combustion process is accelerated by approximately 10%. These breakthroughs pave the way for virtual screening and the rational design of advanced propellant formulations and microstructures incorporating alloy-formula propellants.

Multifunctional heterostructured composite foam with 3D hierarchical network for efficient electromagnetic interference shielding

The development of multifunctional electromagnetic interference (EMI) shielding materials represents an important research direction. However, the challenge remains to develop multifunctional and high-performance electromagnetic waves (EMW) shielding materials through the effective integration of multiple functions into the materials through appropriate multicomponent strategies and ingenious microstructural design. In this study, magnetic Fe3O4 nanoparticles with polypyrrole (PPy) encapsulation were successfully assembled on melamine foam (MF) with a hierarchical structure combined with a highly conductive silver layer by in situ polymerization and cyclic immersion processes to achieve absorption-dominated electromagnetic shielding and multifunctionality. The composite benefits from good impedance matching, dielectric/magnetic losses, interfacial/dipole polarization, and internal multiple reflections and scattering due to the three-dimensional conductive network. Moreover, the high concentration of modified Fe3O4@PPy particles assembled on the MF skeleton ensures that the multifunctional heterostructured composite foams remain stable and superhydrophobic even when the surface is repeatedly abraded. At the same time, MHCF exhibits excellent thermal insulation and infrared stealth properties. This work offers new insights into the design and development of lightweight and multifunctional high-performance EMW shielding materials, while simultaneously opening up new prospects for their practical applications.

Deformation Mechanisms Dominated by Decomposition of an Interfacial Misfit Dislocation Network in Ni/Ni3Al Multilayer Structures.

Ni/Ni3Al heterogeneous multilayer structures are widely used in aerospace manufacturing because of their unique coherent interfaces and excellent mechanical properties. Revealing the deformation mechanisms of interfacial structures is of great significance for microstructural design and their engineering applications. Thus, this work aims to establish the connection between the evolution of an interfacial misfit dislocation (IMD) network and tensile deformation mechanisms of Ni/Ni3Al multilayer structures. It is shown that the decomposition of IMD networks dominates the deformation of Ni/Ni3Al multilayer structures, which exhibits distinct effects on crystallographic orientation and layer thickness. Specifically, the Ni/Ni3Al (100) multilayer structure achieves its maximum yield strength of 5.28 GPa at the layer thickness of 3.19 nm. As a comparison, the (110) case has a maximum yield strength of 4.35 GPa as the layer thickness is 3.01 nm. However, the yield strength of the (111) one seems irrelevant to layer thickness, which fluctuates between 10.89 and 11.81 GPa. These findings can provide new insights into a deep understanding of the evolution and deformation of the IMD network of Ni/Ni3Al multilayer structures.

Bioinspired microstructure design simultaneously enhances strain-rate stiffening and toughening of composites

Keratinous biological materials, such as baleen, pangolin scales, and human hair, have similar constituent materials. However, their strain-rate dependent mechanical properties vary due to differences in their microstructures. Inspired by the microstructures observed in baleen, here we present novel microstructural designs of three types of lamellar-tubular fibers, namely the lamellar-tubular fiber (LTF), mineralized lamellar-tubular fiber (MLTF) and hollow mineralized-lamellar-tubular fiber (HMLTF). We systematically investigated their strain-rate dependent mechanical behaviors with comparison to the conventional cylinder-fiber (CF) reinforced composites. Through the finite element analysis (FEA), we found that the baleen-inspired composites have superior strain-rate stiffening and toughening effects than the conventional fiber reinforced composite. Rate-dependent constitutive models decoupling elastic and inelastic regimes were constructed for these bioinspired composites. Based on the FEA results, three constitutive parameters were obtained to quantitatively characterize the rate-dependent mechanical behaviors of these composites, especially the microstructure-induced difference. Furthermore, our study found that the baleen-inspired tubular microstructure improves stiffness and strain-rate stiffening through raising the stress levels of all phases and improves toughness and strain-rate toughening through enlarging the deformation in the inelastic region. This novel bioinspired design is hopeful to pave ways for the development of advanced composites with simultaneously enhanced strain-rate stiffening and toughening.

Materials design using genetic algorithms informed by convolutional neural networks: Application to carbon nanotube bundles

Carbon nanotube (CNT) composites are promising but complex material systems whose mechanical response is influenced by many features, including CNT bundle microstructures. It is intractable to design CNT bundle microstructures using experiments and/or simulations alone. Thus, we implement a machine learning-based tool comprising a genetic algorithm (GA) (which aids in selecting features for bundle microstructures) and a convolutional neural network (CNN) (which rapidly predicts mechanical performance of bundle microstructures). Training data for the CNN are obtained from micromechanical finite element simulations. CNN predictions achieve R2>0.96 for elastic and shear moduli and R2>0.83 for Poisson’s ratios. Microstructures identified by the CNN-informed GA outperform between 79% and 100% of solutions found using a brute-force search and are found in less than 5% of the time, providing an efficient tool for informed materials design of CNT bundle microstructures.

(Invited) Wearable Pocket-Sized Fully Non-Contact Cardiorespiratory Sensor

Cardiovascular and respiratory diseases have emerged as the leading cause of global mortality over the past decade, encompassing conditions such as atrial fibrillation and chronic obstructive pulmonary disease. Consequently, continuous monitoring plays a crucial role in managing these conditions, as it enables early detection, improves patient survival rates, and alleviates the burden on emergency medical resources. Our research group has developed a wearable pocket-sized fully non-contact cardiorespiratory sensor that utilizes electromagnetic induction technology to measure dynamic changes in electrical conductivity resulting from cardiac contractions and pulmonary volume variations. This enables the continuous acquisition of eddy current damping response signals to achieve cardiorespiratory monitoring. In comparison to commercially available ECGs, PPG smartwatches, and respiratory sensors, our proposed pocket-sized sensor offers three major advantages: exceptional concealment, convenience, and comfort for health monitoring due to its pocket-sized and micro-structured design; simultaneous acquisition of two-dimensional cardiac and respiratory signals, facilitating comprehensive cardiorespiratory health monitoring; and the ability to adjust sensing depth through frequency modulation of the electromagnetic field, thus eliminating variations in physiological structures among subjects and achieving optimized sensing and personalized medical benefits.

Unravelling Effects of Microstructural Electrode Architecture on Cell Performance and Aging - a Combined Experimental and Simulation-Based Study on Commercial 21700 Lithium-Ion High-Energy Cells

In order to balance energy and power density of Li-ion batteries – and to ensure a long battery life – it is crucial to understand in detail how the composition and the microstructural design of the electrodes affects their capacity and kinetics.In our study we compare different commercial 21700 high-energy cells with very similar capacities (5 Ah) and energy densities (264 Wh/kg, 735 Wh/l) according to the supplier’s data sheets. However, in electrochemical tests, these cells showed significant differences with respect to rate capability and cyclic ageing. Detailed microstructural, chemical as well as electrochemical tests utilizing rebuilt half cells and symmetrical cells were done to identify microstructure-property relationships and the most critical microstructural parameters. In doing so, our study contributes to derive guidelines for optimized microstructural electrode design that combines energy with power and a long battery life.For material and microstructural analyses of fresh and aged cells, we used complementary methods such as optical and scanning electron microscopy, µCT- and FIB/SEM tomography, EDS and XRD to characterize the architecture of the electrodes at different length scales. We combined these results with results from detailed electrochemical studies such as OCV and half-cell tests with rebuilt cells as well as electrochemical impedance spectroscopy. Moreover, the 3D data from FIB/SEM tomography has been used as the input for microstructure-resolved simulations in the framework BEST, which allows for further investigation of the electrode microstructure and its effect on the electrochemical behaviour. In doing so, we gained a comprehensive dataset that allowed us to understand the different electrochemical behaviour of the different cells in the pristine state as well as their different behaviour during cyclic ageing.Some of the main findings are: (i) Different suppliers realize the same nominal capacity and energy densities of their cells by different electrode loadings; we observed differences of about 25 %; (ii) All suppliers strive to highly densify both, cathode and anode. Typical densities are 3.4 – 3.6 g/cm³ for the cathode and 1.5 – 1.6 g/cm³ for the anode. (iii) All investigated cells contain Si-rich phases within the anode, however, the chemical composition and the morphology is quite different and affects the electrochemical behaviour; (iv) We found significant differences in the binder-additive content; microstructure-resolved simulations indicate that this critically affects the electronic conductivity of the electrodes and thus, their electrochemical behaviour; (iv) The rate capability of the cells is significantly affected by the areal capacity of the electrodes (and presumably, their electronic conductivity); (vi) This in turn affects the cyclic aging behaviour of the cells. The investigated cells exhibit significant differences under various cycling protocols; we varied upper and lower cut-off voltage as well as the C-rate to investigate how microstructural features affect aging under different conditions.Within the talk, we will provide detailed insights into the results briefly outlined above and try to put the individual pieces of the puzzle together into an overall picture to elucidate how different microstructural features in combination determine the performance and cycling stability of the cells. Figure 1

Design Principles for Architected Battery Electrodes

The properties of rechargeable lithium-ion batteries are determined by the electrochemical and kinetic properties of their constituent materials as well as by their underlying microstructure. The discovery of 2D and 3D mesoscale architectures tailored to diverse applications remain an open challenge and it cannot be approached empirically. In this work, we leverage the design flexibility offered by several additive manufacturing methods (e.g. direct ink write, projection micro-stereolithography, etc.) to engineer the architecture of device electrodes. To explore this vast design space, we employ theoretical analyses and topology optimization techniques to determine printable electrode shapes. Our analyses produce general design guidelines, and three-dimensional CAD representations that optimize the battery architecture over specific performance metrics. In this talk, we show examples of electrode design driven by extreme operating conditions (e.g., low temperature) or by mechanical resilience. We also demonstrate an integrated workflow for model validation and guided experiments. For Li-metal anodes, our objective is to identify regimes of morphologically stable growth--where deleterious effects of dendrite growth might be avoided by microstructural design. For manganese-oxide cathodes, we develop physical models that capturethe pseudocapacitive response of the material and use them in inverse analyses to optimize the cathode architectures.

Guiding the Choice of Carbon Nanotubes Conductive Additives for Silicon Anode Electrode through Microstructure Scale Analysis

Silicon anode electrodes exhibit a large microstructure design space as several carbon additives are considered to improve its conductivity and thus electrochemical performance. Investigating each combination experimentally is time-consuming. In this work, microstructure scale modeling is used to discriminate between different carbon additives to accelerate electrode development [1]. Baseline spherical C45, single wall carbon nano tube (SWCNT, cf. Fig. 1), carbon nano rods (CNR), and mixed SWCNT-CNR are considered and their respective impact on connectivity, effective conductivity, specific surface area, pore size distributions, and effective diffusivity are calculated to provide design recommendations. To do so, microstructures are numerically generated using the NREL open-source Microstructure Analysis Toolbox (MATBOX) available to the battery community* [2].Additionally, the model is used to correlate material utilization and silicon particle size, in agreement with experimental data, to further guide the selection of silicon material.Lastly, the model is used to investigate the porosity specific surface area relationship in the low porosity range, for which the analytical expression 3ε/r (with ε the particle volume fraction and r the particle radius) is no longer valid due to the packing density limit, and revealed a non-monotonic correlation. Such result is very relevant for silicon anode development as one major hindrance to this chemistry is its limited calendar life due to SEI growth, for which the specific surface area is a key parameter. *Nanotube generation new feature will be released after article [1] publication. [1] F. L. E. Usseglio-Viretta, J. H. Kim, J. Preimesberger, N. Neale, P. Weddle, A. Verma, A. M. Colclasure, Guiding the Choice of Carbon Nanotubes Conductive Additives for Silicon Anode Electrode Through Microstructure Scale Analysis, in preparation[2] F. L. E. Usseglio-Viretta, P. Patel, E. Bernhardt, A. Mistry, P. P. Mukherjee, J. Allen, S. J. Cooper, J. Laurencin, K. Smith, MATBOX: An Open-source Microstructure Analysis Toolbox for microstructure generation, segmentation, characterization, visualization, correlation, and meshing, SoftwareX, 17 (2022) 100915. Figure 1

Using Micrometer Scale X-Ray CT and Pore Network Modeling to Assess High-Energy Bi-Layer Li-Ion Battery Cathode Structures

The optimization of cathode pore space is pivotal for enhancing the rate capability of lithium-ion battery electrodes. Previous studies on simulated cathodes have highlighted the importance of achieving an optimal porosity gradient, with a gradual increase from the current collector side to the separator side to accommodate the growing demand for ion transport in that direction [1]–[3]. In this research, we address this requirement by introducing and investigating bi-layer NCM 811 cathodes. These cathodes consist of a slurry-coated dense bottom layer and a spray-coated highly porous top layer with varying relative thickness to approximate the desired porosity gradient. Employing Micrometer-scale X-ray CT characterization and pore network modeling, we evaluate the structural features, demonstrating the effectiveness of the design, and quantify essential parameters such as porosity and tortuosity. Furthermore, the cathodes are integrated into lithium anode half-cells and subjected to electrochemical cycling at different rates to assess ion transport and rate capability. Our findings reveal that to achieve the highest discharge spatial energy density above 1C for cathodes approximately 100μm thick, the compressed bottom layer with 30% porosity should have a thickness of 60μm, while the highly porous top layer with around 47% porosity should be 40μm thick.Reference:[1] A. Shodiev et al., “Deconvoluting the benefits of porosity distribution in layered electrodes on the electrochemical performance of Li-ion batteries,” Energy Storage Mater., vol. 47, pp. 462–471, May 2022, doi: 10.1016/j.ensm.2022.01.058.[2] X. Lu et al., “3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling,” Nat. Commun., vol. 11, no. 1, p. 2079, Apr. 2020, doi: 10.1038/s41467-020-15811-x.[3] K. Song, C. Zhang, N. Hu, X. Wu, and L. Zhang, “High performance thick cathodes enabled by gradient porosity,” Electrochimica Acta, vol. 377, p. 138105, May 2021, doi: 10.1016/j.electacta.2021.138105.

Hydrophobic Multilayered PEG@PAN/MXene/PVDF@SiO2 Composite Film with Excellent Thermal Management and Electromagnetic Interference Shielding for Electronic Devices.

With the rapid development of electronic industry, it's pressing to develop multifunctional electromagnetic interference (EMI) shielding materials to ensure the stable operation of electronic devices. Herein, multilayered flexible PEG@PAN/MXene (Ti3C2Tx)/PVDF@SiO2 (PMF) composite film has been constructed from the level of microstructure design via coaxial electrospinning, coating spraying, and uniaxial electrospinning strategies. Benefiting from the effective encapsulation for PEG and high conductivity of MXene coating, PEG@PAN/MXene composite film with MXene coating loading density of 0.70mg cm-2 exhibits high thermal energy storage density of 120.77 J g-1 and great EMI shielding performance (EMI SE of 34.409dB and SSE of 49.086dB cm3 g-1) in X-band (8-12GHz). Therefore, this advanced composite film can not only help electronic devices prevent the influence of electromagnetic pollution in the X-band but also play an important role in electronic device thermal management. Additionally, the deposition of nano PVDF@SiO2 fibers (289±128nm) endowed the PMF composite film with great hydrophobic properties (water contact angle of 126.5°) to ensure the stable working of hydrophilic MXene coating, thereby breaks the limitation of humid application environments. The finding paves a new way for the development of novel multifunctional EMI shielding composite films for electronic devices.

High-thermal free vibration analysis of functionally graded microplates using a new finite element formulation based on TSDT and MSCT

Recent advancements in additive manufacturing (AM) have revolutionized the design and production of complex engineering microstructures. Despite these advancements, their mathematical modeling and computational analysis remain significant challenges. This research aims to develop an effective computational method for analyzing the free vibration of functionally graded (FG) microplates under high temperatures while resting on a Pasternak foundation (PF). This formulation leverages a new third-order shear deformation theory (new TSDT) for improved accuracy without requiring shear correction factors. Additionally, the modified couple stress theory (MCST) is incorporated to account for size-dependent effects in microplates. The PF is characterized by two parameters including spring stiffness () and shear layer stiffness (). To validate the proposed method, the results obtained are compared with those of the existing literature. Furthermore, numerical examples explore the influence of various factors on the high-temperature free vibration of FG microplates. These factors include the length scale parameter (), geometric dimensions, material properties, and the presence of the elastic foundation. The findings significantly enhance our comprehension of the free vibration of FG microplates in high thermal environments. In addition, the findings significantly enhance our comprehension of the free vibration of FG microplates in high thermal environments. In addition, the results of this research will have great potential in military and defense applications such as components of submarines, fighter aircraft, and missiles.

Grain refinement and phase precipitation simultaneously improve the strength and ductility of ultra-high strength titanium alloy sheets

The simultaneous high strength and high plasticity of metastable-β titanium alloy sheets remains a difficult challenge. In this work, a 1.2 ​mm thick sheet of Ti–15Mo–3Al-2.7Nb-0.25Si titanium alloy was obtained after rolling and annealing, and then subjected to a duplex-ageing treatment. The pre-ageing temperatures fell in the range of 300–390 ​°C for 0.5–2h. The re-ageing temperatures were in the range of 500–600 ​°C. After characterization, it was found that the alloy precipitates ω-phases during the pre-ageing process, and the distribution of such ω-phases evolves unevenly and increases in number with the increase of the pre-ageing temperature. Therefore, the strengthening mechanism of the alloy sheet is mainly α-phase nucleation assisted by ω-phase. Moreover, grain refinement appears as a mechanism to ensure the plasticity of the alloy. Finally the ω-phase evolution law is discussed in detail and the strengthening mechanism of the alloy sheet is also analyzed. At this work, a metastable-β titanium alloy sheet with strength of 1445.75 ​MPa and elongation of 6.55 ​% was obtained. This study provides a new idea for the microstructure design and process improvement of the metastable-β titanium alloy sheet.

Multi-interfaced FeCoNi@C/carbon cloth composites for eliminating electromagnetic wave pollution

To tackle the increasing electromagnetic pollution, new and efficient electromagnetic wave absorption (EWA) and shielding (EWS) materials are urgently needed. Multi-component synergism and complex microstructure design are effective measures to improve the EWA and EWS properties. However, how to implement the above designs still faces huge challenges. Herein, multi-interface carbon-coated FeCoNi nanoneedles grown on carbon cloth (FeCoNi@C/CC) were synthesized by a combination of hydrothermal process and chemical vapor deposition (CVD) technology with the concept of “green synthesis”. Using acetylene as the carbon source and atmosphere, the FeCoNi ternary hydroxide can be transformed into a multiple magnetic component (Fe3O4, Ni, and Co metals) by simple annealing. Simultaneously, a uniform carbon layer is formed on the surface, resulting in a composite system with a variety of heterogeneous interfaces and loss mechanisms. Additionally, the dielectric and magnetic loss capacities can be effectively adjusted by changing the temperature of CVD. The optimized FeCoNi@C/CC as filler exhibits remarkable EWA performance with a minimum reflection loss of −69.3 ​dB at a thickness of 1.82 ​mm and a maximum effective absorption bandwidth of 6.80 ​GHz. Moreover, the composites as an integrated component also show a fascinating electromagnetic interference shielding efficiency of 42.2 ​dB. This work provides a guide for the structural design of high-performance electromagnetic protection materials with multi-heterogeneous interfaces.

Study on Effect of Surface Micro-Texture of Cemented Carbide on Tribological Properties of Bovine Cortical Bone.

In bone-milling surgical procedures, the intense friction between the tool and bone material often results in high cutting temperatures, leading to the thermal necrosis of bone cells. This paper aims to investigate the effect of micro-texture on the tribological properties of YG8 cemented carbide in contact with bone. The main objective is to guide the design of tool surface microstructures to reduce frictional heat generation. To minimize experimental consumables and save time, numerical simulations are first conducted to determine the optimal machining depth for the texture. Subsequently, micro-textures with different shapes and pitches are prepared on the surface of YG8 cemented carbide. These textured samples are paired with bovine cortical bone pins featuring various bone unit arrangements, and friction and wear tests are conducted under physiological saline lubrication. The experimental results indicate that the appropriate shape and pitch of the micro-texture can minimize the coefficient of friction. The parallel arrangement of bone units exhibits a lower coefficient of friction compared to the vertical arrangement. This study holds significant implications for the design and fabrication of future micro-texture milling cutters.

Twinning, slip and size effect of phase-transforming ferroelectric nanopillars

Ferroelectric materials are widely used in energy applications due to their field-driven multiferroic properties. The stress-induced phase transformation plays an important role in the functionality over repeated and consecutive operation cycles, especially at the micro/nanoscales. Here we report a systematic in-situ uniaxial compression tests on cuboidal Barium titanate (BaTiO3) nanopillars with size varying from 100 nm to 3000 nm, by which we explore the stress-induced transformation and its interplay with plastic deformation. We confirm the superelasticity achieved in pillars by martensitic phase transformation from tetragonal to orthorhombic. There exists a critical size, 330 nm, for the yield stress. Above 330 nm, martensitic phase transformation aids slip along the plane with a low Schmid factor, in turn, the pseudo-compatible twins form within the shear band. The scaling exponent of size-dependent yield strength is found to be exactly 1. For nanopillars smaller than 330 nm, no twins form, only slips with large Schmid factors are activated, and size effect vanishes. All pillars with sizes from 100 nm to 300 nm achieve the theoretical yield limit around 9 GPa. Our experimental results uncover the interplay between twins and slips in BaTiO3 nanopillars, which pave the way for the optimization of microstructure design of ferroelectric materials for microelectronic applications at small scales.

Strong SiC@Carbon nanowire aerogel metamaterials for efficient electromagnetic interference shielding

Lightweight, high-strength and efficient electromagnetic interference shielding materials are in urgent demand for aerospace vehicles such as lunar and Mars rovers. SiC nanowire aerogels exhibit low density, chemical stability, and adjustable dielectric properties, rendering them as ideal candidates for high-performance electromagnetic wave protecting materials. However, developing SiC nanowire aerogels with simultaneous strong mechanical properties and efficient electromagnetic interference shielding performance remains challenging. Herein, a class of strong SiC@carbon nanowire aerogel metamaterials with both mechanical robustness and efficient electromagnetic interference shielding are obtained through microstructure design and compositional optimization. The aerogels with designed meta-structures are fabricated by 3D printing followed with chemical vapor deposition of graphene-like carbon. The optimized compressive strength and Young's modulus of the aerogel metamaterial reach up to 1.581 MPa and 46.230 MPa, respectively, showing an increase of about 50–60 times. It also exhibits an electromagnetic interference shielding effectiveness of 38.39 dB and specific shielding effectiveness of 666.53 dBcm3g−1. These good properties are attributed to the synergistic effects of the hierarchical meta-structure and the SiC@carbon nanowires composite constituents, which provides a feasible pathway toward further design of high-performance electromagnetic interference protection materials.