Strength and elastic modulus enhancement in Mg-Li-Al matrix composites reinforced by ex situ TiB2 particles via stir casting

A novel Mg^(-1)0Li-3Al(wt.%,LA103)matrix composite reinforced by ex situ micron TiB_(2) particles was developed in the present study.The ball milling and cold pressing pretreatment of the reinforcements made it feasible to prepare this material under stir casting conditions with good dispersion.The microstructure and mechanical properties of the composites prepared by different pretreatment methods were analyzed in detail.The TiB_(2) particles in the Al-TiB_(2)/LA103 composite using the pretreatment process were uniformly distributed in the microstructure due to the formation of highly wettable core-shell units in the melt.Compared with the matrix alloys,the Al-TiB_(2)/LA103 composite exhibited effective strength and elastic modulus improvements while maintaining acceptable elongation.The strengthening effect in the composites was mainly attributed to the strong grain refining effect of TiB2.This work shows a balance of high specific modulus(36.1 GPa·cm^(3)·g^(-1))and elongation(8.4%)with the conventional stir casting path,which is of considerable application value.

A novel relationship between elastic modulus and void ratio associated with principal stress for coral calcareous sand

Elastic moduli,e.g.shear modulus G and bulk modulus K,are important parameters of geotechnical materials,which are not only the indices for the evaluation of the deformation ability of soils but also the important basic parameters for the development of the constitutive models of geotechnical materials.In this study,a series of triaxial loading-unloading-reloading shear tests and isotropic loading-unloadingreloading tests are conducted to study several typical mechanical properties of coral calcareous sand(CCS),and the void ratio evolution during loading,unloading and reloading.The test results show that the stress-strain curves during multiple unloading processes are almost parallel,and their slopes are much greater than the deformation modulus at the initial stage of loading.The relationship between the confining pressure and the volumetric strain can be defined approximately by a hyperbolic equation under the condition of monotonic loading of confining pressure.Under the condition of confining pressure unloading,the evolution of void ratio is linear in the e-lnp0 plane,and these lines are a series of almost parallel lines if there are multiple processes of unloading.Based on the experimental results,it is found that the modified Hardin formulae for the elastic modulus estimation have a significant deviation from the tested values for CCS.Based on the experimental results,it is proposed that the elastic modulus of soils should be determined by the intersection line of two spatial surfaces in the G/K-e-p’/pa space(pa:atmosphere pressure).“Ye formulation”is further proposed for the estimation of the elastic modulus of CCS.This new estimation formulation for soil elastic modulus would provide a new method to accurately describe the mechanical behavior of granular soils.

Effects of Initial Defects on Effective Elastic Modulus of Concrete with Mesostructure

An exquisite mesostructure model was presented to predict the effective elastic modulus of concrete,in which concrete is realized as a four-phase composite material consisting of coarse aggregates,mortar matrix,interfacial transition zone(ITZ),and initial defects.With the three-dimensional(3D)finite element(FE)simulation,the highly heterogeneous composite elastic behavior of concrete was modeled,and the predicted results were compared with theoretical estimations for validation.Monte Carlo(MC)simulations were performed with the proposed mesostructure model to investigate the various factors of initial defects influencing the elastic modulus of concrete,such as the shape and concentration(pore volume fraction or crack density)of microspores and microcracks.It is found that the effective elastic modulus of concrete decreases with the increase of initial defects concentration,while the distribution and shape characteristics also exert certain influences due to the stress concentration caused by irregular inclusion shape.

Numerical Analysis for High⁃Throughput Elastic Modulus Measurement of Substrate⁃Supported Thin Films

Micro/nano-thin films are widely used in the fields of micro/nano-electromechanical system(MEMS/NEMS)and flexible electronics,and their mechanical properties have an important impact on the stability and reliability of components.However,accurate characterization of the mechanical properties of thin films still faces challenges due to the complexity of film-substrate structure,and the characterization efficiency of traditional techniques is insufficient.In this paper,a high-throughput determination method of the elastic modulus of thin films is proposed based on the strain variance method,the feasibility of which is analyzed by the finite element method(FEM),and the specific tensile configuration with array-distributed thin films is designed and optimized.Based on the strain difference between the film-substrate region and the uncoated region,the elastic modulus of multiple films is obtained simultaneously,and the influences of film width,spacing,thickness,and distribution on the measurement of elastic modulus are elucidated.The results show that the change in film width has a more obvious effect on the elastic modulus determination than film spacing and thickness,i.e.,the larger the film width is,the closer the calculation results are to the theoretical value,and the change in calculation results tends to be stabilized when the film width increases to a certain length.Specifically,the simultaneous measurement of the elastic modulus of eight metal films on a polyimide(PI)substrate with a length of 110 mm and a width of 30 mm can be realized,and the testing throughput can be further increased with the extension of the substrate length.This study provides an efficient and low-cost method for measuring the elastic modulus of thin films,which is expected to accelerate the development of new thin film materials.

High-modulus solid electrolyte interphase layer with gradient composition enables long-cycle all-solid-state lithium-sulfur batteries

All-solid-state lithium-sulfur batteries(ASSLSBs) have become one of the most potential candidates for the next-generation high-energy systems due to their intrinsic safety and high theoretical energy density.However, PEO-based ASSLSBs face the dilemma of insufficient Coulombic efficiency and long-term stability caused by the coupling problems of dendrite growth of anode and polysulfide shuttle of cathode. In this work, 1,3,5-trioxane(TOX) is used as a functional additive to design a PEO-based composite solidstate electrolyte(denoted as TOX-CSE), which realizes the stable long-term cycle of an ASSLSB. The results show that TOX can in-situ decompose on the anode to form a composite solid electrolyte interphase(SEI) layer with rich-organic component. It yields a high average modulus of 5.0 GPa, greatly improving the mechanical stability of the SEI layer and thus inhibiting the growth of dendrites. Also,the robust SEI layer can act as a barrier to block the side reaction between polysulfides and lithium metal.As a result, a Li-Li symmetric cell assembled with a TOX-CSE exhibits prolonged cycling stability over 2000 h at 0.2 m A cm^(-2). The ASSLSB also shows a stable cycling performance of 500 cycles at 0.5 C.This work reveals the structure–activity relationship between the mechanical property of interface layer and the battery's cycling stability.

Interconnected microstructure and flexural behavior of Ti_(2)C-Ti composites with superior Young’s modulus

To enhance the Young’s modulus(E)and strength of titanium alloys,we designed titanium matrix composites with intercon-nected microstructure based on the Hashin-Shtrikman theory.According to the results,the in-situ reaction yielded an interconnected microstructure composed of Ti_(2)C particles when the Ti_(2)C content reached 50vol%.With widths of 10 and 230 nm,the intraparticle Ti lamellae in the prepared composite exhibited a bimodal size distribution due to precipitation and the unreacted Ti phase within the grown Ti_(2)C particles.The composites with interconnected microstructure attained superior properties,including E of 174.3 GPa and ultimate flexural strength of 1014 GPa.Compared with that of pure Ti,the E of the composite was increased by 55% due to the high Ti_(2)C content and interconnected microstructure.The outstanding strength resulted from the strong interfacial bonding,load-bearing capacity of interconnected Ti_(2)C particles,and bimodal intraparticle Ti lamellae,which minimized the average crack driving force.Interrupted flexural tests revealed preferential crack initiation along the{001}cleavage plane and grain boundary of Ti_(2)C in the region with the highest tensile stress.In addition,the propagation can be efficiently inhibited by interparticle Ti grains,which prevented the brittle fracture of the composites.

Regularity analysis of resilient modulus for hot-mix asphalt with large temperature fluctuations

To evaluate the regularity of resilient modulus for hot-mix asphalt(HMA)under large temperature fluctuations,back propagation(BP)neural network technology was used to analyze the continuous change of HMA resilient modulus.Firstly,based on the abundant data,the training model of HMA resilient modulus was established by using BP neural network technology.Subsequently,BP neural network prediction and regression analysis were performed,and the prediction model of HMA resilient modulus at different temperatures(50C to 60C)was obtained,which fully considered multi-factor and nonlinearity.Finally,the fitted theoretical model can be used to evaluate the HMA performance under the condition of large temperature fluctuations,and the rationality of theoretical model was verified by taking Harbin region as an example.It was found that the relationship between HMA resilient modulus and temperatures can be described by inverse tangent function.And the key parameters of theoretical model can be used to evaluate the continuous change characteristics of HMA resilient modulus with large temperature fluctuations.The results can further improve the HMA performance evaluation system and have certain theoretical value.

Enhanced asphalt dynamic modulus prediction: A detailed analysis of artificial hummingbird algorithm-optimised boosted trees

This study introduces and evaluates a novel artificial hummingbird algorithm-optimised boosted tree(AHAboosted)model for predicting the dynamic modulus(E*)of hot mix asphalt concrete.Using a substantial dataset from NCHRP Report-547,the model was trained and rigorously tested.Performance metrics,specifically RMSE,MAE,and R2,were employed to assess the model's predictive accuracy,robustness,and generalisability.When benchmarked against well-established models like support vector machines(SVM)and gaussian process regression(GPR),the AHA-boosted model demonstrated enhanced performance.It achieved R2 values of 0.997 in training and 0.974 in testing,using the traditional Witczak NCHRP 1-40D model inputs.Incorporating features such as test temperature,frequency,and asphalt content led to a 1.23%increase in the test R2,signifying an improvement in the model's accuracy.The study also explored feature importance and sensitivity through SHAP and permutation importance plots,highlighting binder complex modulus|G*|as a key predictor.Although the AHA-boosted model shows promise,a slight decrease in R2 from training to testing indicates a need for further validation.Overall,this study confirms the AHA-boosted model as a highly accurate and robust tool for predicting the dynamic modulus of hot mix asphalt concrete,making it a valuable asset for pavement engineering.

Prediction of constrained modulus for granular soil using 3D discrete element method and convolutional neural networks

To efficiently predict the mechanical parameters of granular soil based on its random micro-structure,this study proposed a novel approach combining numerical simulation and machine learning algorithms.Initially,3500 simulations of one-dimensional compression tests on coarse-grained sand using the three-dimensional(3D)discrete element method(DEM)were conducted to construct a database.In this process,the positions of the particles were randomly altered,and the particle assemblages changed.Interestingly,besides confirming the influence of particle size distribution parameters,the stress-strain curves differed despite an identical gradation size statistic when the particle position varied.Subsequently,the obtained data were partitioned into training,validation,and testing datasets at a 7:2:1 ratio.To convert the DEM model into a multi-dimensional matrix that computers can recognize,the 3D DEM models were first sliced to extract multi-layer two-dimensional(2D)cross-sectional data.Redundant information was then eliminated via gray processing,and the data were stacked to form a new 3D matrix representing the granular soil’s fabric.Subsequently,utilizing the Python language and Pytorch framework,a 3D convolutional neural networks(CNNs)model was developed to establish the relationship between the constrained modulus obtained from DEM simulations and the soil’s fabric.The mean squared error(MSE)function was utilized to assess the loss value during the training process.When the learning rate(LR)fell within the range of 10-5e10-1,and the batch sizes(BSs)were 4,8,16,32,and 64,the loss value stabilized after 100 training epochs in the training and validation dataset.For BS?32 and LR?10-3,the loss reached a minimum.In the testing set,a comparative evaluation of the predicted constrained modulus from the 3D CNNs versus the simulated modulus obtained via DEM reveals a minimum mean absolute percentage error(MAPE)of 4.43%under the optimized condition,demonstrating the accuracy of this approach.Thus,by combining DEM and CNNs,the variation of soil’s mechanical characteristics related to its random fabric would be efficiently evaluated by directly tracking the particle assemblages.

Modelling of the variation of granular base materials resilient modulus with material characteristics and humidity conditions

This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses.The fines content and the percentage of fractured coarse aggregates were identified as direct indicators of the resilient modulus susceptibility to changes in water content.The results showed that the percentage of fractured coarse aggregates particles(FR)has a more significant impact on the resilient modulus(Er)of crushed granular materials used in pavement construction than the combined indicator of the fines content and sample volumetrics(nf).Crushed granular materials with a higher percentage of fractured coarse aggregates are relatively insensitive to changes in the degree of saturation,but become more sensitive as the fine fraction porosity decreases.An adjusted model was proposed based on the existing formulation,but considers a complex parameter to describe and adjust the sensitivity of base granular materials to variations in moisture content with respect to fabrication charac-teristics,fines content and volumetric properties.The model shows that the variation of Er values is below10%for fully crushed granular materials.However,it reaches approximately±12%for materials with 75%of crushed coarse aggregates andþ40%and-25%for materials with FR=50%.This model could help select good ag-gregates characteristics and adjust grain-size distribution for environments where significant moisture content variations can occur in the pavement system,such as in the Province of Quebec(Canada).As it is based on pa-rameters that can be easily determined or estimated,it also represents a valuable tool for detailed design and analysis that can consider material characteristics.

Zeta Potential of Aggregate and Dynamic Modulus of HMA Estimation Using Aggregate Silica Content

The mineralogical composition of an aggregate influences its adhesion with bitumen and therefore its dynamic modulus. However, few studies have been conducted on this aspect. One of the most used properties to describe the impact of aggregate on the adhesiveness phenomena is the zeta potential. In this study, the first mineralogical and chemical properties were considered through the percentage of silica in the rock source of aggregates and the electric aggregate particles charge zeta. Dynamic modulus values used for regression process are determined from complex modulus test on nine asphalt concretes mix designed with aggregate types (basalt of Diack, quartzite of Bakel and Limestone of Bandia). The results showed that aggregate with high percentage of silica have higher zeta potential than aggregate with low percentage of silica. The development of a zeta potential predictive model showed a strong sensitivity to silica. The results of the complex modulus tests showed that Hot Mixture Asphalt (HMA) mixed with aggregate containing high silica contents gave better results than those mixed with aggregates containing low percentage of silica. The dynamic modulus predictive models of HMA developed shows that it is the properties of bitumen that influence more. However, the effect of silica although low, is very marked at low temperatures and high frequencies.

Integrated Computational Materials Engineering for the Development and Design of High Modulus Al Alloys

Integrated computational materials engineering(ICME)is to integrate multi-scale computational simulations and key experimental methods such as macroscopic,mesoscopic,and microscopic into the whole process of Al alloys design and development,which enables the design and development of Al alloys to upgrade from traditional empirical to the integration of compositionprocess-structure-mechanical property,thus greatly accelerating its development speed and reducing its development cost.This study combines calculation of phase diagram(CALPHAD),Finite element calculations,first principle calculations,and microstructure characterization methods to predict and regulate the formation and structure of composite precipitates from the design of highmodulus Al alloy compositions and optimize the casting process parameters to inhibit the formation of micropore defects in the casting process,and the final tensile strength of Al alloys reaches420 MPa and Young's modulus reaches more than 88 GPa,which achieves the design goal of the high strength and modulus Al alloys,and establishes a new mode of the design and development of the strength/modulus Al alloys.

Numerical analysis of bending property of bi-modulus materials and a new method for measurement of tensile elastic modulus

In nature,there are widely distributed bi-modulus materials with different deformation characteristics under compressive and tensile stress states,such as concrete,rock and ceramics.Due to the lack of constitutive model that could reasonably consider the bi-modulus property of materials,and the lack of simple and reliable measurement methods for the tensile elastic parameters of materials,scientists and engineers always neglect the effect of the bi-modulus property of materials in engineering design and numerical simulation.To solve this problem,this study utilizes the uncoupled strain-driven constitutive model proposed by Latorre and Montáns(2020)to systematically study the distributions and magnitudes of stresses and strains of bi-modulus materials in the three-point bending test through the numerical method.Furthermore,a new method to synchronously measure the tensile and compressive elastic moduli of materials through the four-point bending test is proposed.The numerical results show that the bi-modulus property of materials has a significant effect on the stress,strain and displacement in the specimen utilized in the three-point and four-point bending tests.Meanwhile,the results from the numerical tests,in which the elastic constitutive model proposed by Latorre and Montáns(2020)is utilized,also indicate that the newly proposed measurement method has a good reliability.Although the new measurement method proposed in this study can synchronously and effectively measure the tensile and compressive elastic moduli,it cannot measure the tensile and compressive Poisson’s ratios.

3D bioprinting of complex biological structures with tunable elastic modulus and porosity using freeform reversible embedding of suspended hydrogels

Three-dimensional(3D)bioprinting has been used widely for the construction of hard tissues such as bone and cartilage.However,constructing soft tissues with complex structures remains a challenge.In this study,complex structures characterized by both tunable elastic modulus and porosity were printed using freeform reversible embedding of suspended hydrogels(FRESHs)printing methods.A mixture of alginate and gelatin was used as the main functional component of the bioink.Rheological analysis showed that this bioink possesses shear thinning and shear recovery properties,supporting both cryogenic and FRESH printing methods.Potential printing capabilities and limitations of cryogenic and FRESH printing were then analyzed by printability tests.A series of complex structures were printed by FRESH printing methods which could not be realized using conventional approaches.Mechanical tests and scanning electron microscopy analysis showed that the printed structure is of excellent flexibility and could be applied in various conditions by adjusting its mechanical modulus and porosity.L929 fibroblast cells maintained cell viability in cell-laden-printed structures,and the addition of collagen further improved the hydrogels’biocompatibility.Overall,all results provided useful insight into the building of human soft tissue organ blocks.

明胶/氧化纳米纤维素高弹性模量高孔隙皮肤支架的3D打印工艺

背景:在采用主动修复治疗手段应对皮肤创伤时,需要使用组织工程技术生成新的组织来代替坏死组织,皮肤支架在创伤修复领域具有良好的应用前景。皮肤支架需要呈现具有一定力学强度的三维多孔结构,以满足细胞增殖分裂的需求,而目前使用的明胶基生物材料力学强度弱,无法达到皮肤支架的使用要求。目的:针对明胶/氧化纳米纤维素复合材料制备组织工程皮肤支架时使用的3D打印工艺进行研究,重点研究不同工艺参数下制备皮肤支架的孔隙率与其力学强度之间的关系。方法:从葎草中提取10%浓度的氧化纳米纤维素晶须,再与5%的明胶复合得到明胶/氧化纳米纤维素复合材料,检测明胶与明胶/氧化纳米纤维素复合材料的弹性模量。以明胶/氧化纳米纤维素复合材料为基材,采用3D打印挤压成型方法制备皮肤支架,通过对材料进行力学性能测试和流变特性测试确定挤压成型工艺参数(填充间隙1.5-2.5 mm,0.1 mm均布;气压160-200 kPa),并以此制备具有三维多孔结构的皮肤支架。对皮肤支架进行了抗压性能的测试并与有限元分析结果相对比,论证了支架打印时的填充间隙与支架孔隙率及力学强度之间的关系。结果与结论:①通过实验得出,加入10%浓度的氧化纳米纤维素晶须使5%明胶的弹性模量度提升了8.84倍;在气压160 kPa下挤出成型可以得到1 mm直径的丝状凝胶,此时填充间隙从1.5 mm增大到2.5 mm会使支架的理论孔隙率从33%上升到60%,但抗压强度从230000 Pa降低到95000 Pa;②结果显示,使用2 mm填充间隙制备得到了理论孔隙率为50%、弹性模量160000 Pa的皮肤支架,该支架具有清晰的三维多孔结构。

单双向循环荷载作用下砂砾料动模量和阻尼比试验研究

通过大型振动三轴试验,研究了单双向循环荷载作用下砂砾料动弹性模量和阻尼比的变化规律,分析围压和径向循环动应力对砂砾料动力参数的影响。研究结果表明:在双向振动三轴试验中,砂砾料的轴向动应变受径向动应力的影响较小,动应变主要与施加的轴向动应力大小有关;单双向振动下砂砾料的动弹性模量均随着动应变的增大而逐渐降低,双向振动时砂砾料动弹性模量随动应变的衰减速率基本不变,在相同动应变下双向振动的动模量均低于单向振动;砂砾料在双向振动时的阻尼比大于单向振动,双向振动时消耗的动应变能更大。通过对两种试验条件下的最大动弹性模量、动模量比进行分析,建立了表述单双向试验条件下最大动弹性模量的换算关系式和双向振动试验中动模量比和动应变的修正模型。

多因素影响下预崩解炭质泥岩动回弹特性研究

为探究多因素影响下预崩解炭质泥岩的动回弹特性,通过动三轴试验研究偏应力、最小体应力、含水率、压实度和干湿循环次数对动态回弹模量的影响,并建立考虑上述因素影响的动回弹模量预测模型。研究表明:动回弹模量与最小体应力、压实度呈正相关关系,与偏应力、含水率呈负相关关系;在同一围压下,动回弹模量随偏应力增加而降低,降幅区间为14.1%~30.7%;含水率为6%时对应的动回弹模量最大;在围压和偏应力相同时,含水率从6%递增至10%,动回弹模量降幅区间为18.6%~35.5%;压实度从93%递增至96%时,动回弹模量增幅区间为4.47%~20.64%。采用干湿循环损伤因子表征干湿循环次数对动回弹模量的影响,发现损伤因子随干湿循环次数N增加可分为3个阶段,即快速增长阶段(N=0~1)、缓慢增长阶段(N=1~6)和增长稳定阶段(N=6~9)。各因素按显著性由高到低排序依次为:压实度、干湿循环、含水率、偏应力、最小体应力。建立的综合考虑约束效应、剪切效应、压实度、含水率和干湿循环的预测模型具有较高地准确性和适用性,可有效评估和预测湿热地区炭质泥岩路堤的动回弹模量。

低弹模混凝土防渗墙材料参数统计特性及相关分布模型

为获取低弹模混凝土防渗墙渗透系数、弹模和抗压强度3个材料参数的统计特性及相关分布模型,基于2座土石坝的检测数据,根据赤池信息准则(AIC)识别材料参数的最优分布类型及相关分布模型的最优Copula函数、Bootstrap方法模拟识别结果的统计不确定性。结果表明,抗压强度、渗透系数和弹模分别服从极值Ⅰ型、对数正态、威布尔或极值Ⅰ型分布,变异系数均值分别为0.17、0.40、0.11;抗压强度与渗透系数、弹模与抗压强度、弹模与渗透系数之间的Pearson相关系数均值分别为-0.79、0.67、-0.55,最优Copula函数分别为Plackett Copula、Gaussian Copula、Gaussian Copula。研究结果可为低弹模混凝土防渗墙的渗流和强度可靠度计算提供参考。

可视化金属丝弹性模量测量平台设计

设计的可视化金属丝弹性模量测量平台,利用干涉法测量光程差原理,开发了一套干涉光斑测量装置,准确地测量出了金属材料拉伸过程中的微小形变量。引入机器视觉方法,实现了金属材料截面积的可视化测量。所搭建的传动结构可连续、稳定地施加拉力,为平台所开发的图形化操作界面,使测量过程可视化,通过观察材料表面形貌特征位移来验证拉伸变化。平台提高了实验测量精度,测量结果相对误差为3.3%。该测量平台可作为综合性实验仪器应用于大学物理实验教学当中。

超大粒径沥青混合料的黏弹特性及温度影响

为精准表征超大粒径沥青混合料(LSAM-50)柔性基层路面的动态黏弹力学响应,对LSAM-50进行动态模量试验,分析了温度对LSAM-50黏弹参数的影响,构建了基于广义对数Sigmoidal模型的黏弹参数主曲线以及基于广义Maxwell模型的黏弹性本构关系.结果表明:温度对LSAM-50黏弹参数的影响显著,温度升高后LSAM-50模量的变化由集料嵌挤力主导,动态模量与存储模量随着温度的升高逐渐降低后趋于稳定;由于LSAM-50具有更大的粒径和集料嵌挤力,其高温抗变形能力比AC-20和AC-13更强;可用广义Maxwell模型构建LSAM-50的黏弹本构关系,其相关性不低于0.99.