反应合成法制备FeAl金属间化合物多孔材料的曲折因子(英文)

以Fe、Al元素粉末为原料,采用反应合成方法,利用Kirkendall效应造孔制备的FeAl金属间化合物多孔材料是继陶瓷和金属多孔材料之后发展的一种新型多孔材料。曲折因子是表征多孔材料孔隙特征的重要参数。基于Darcy原理和 Hagen-Poiseuille方程研究FeAl多孔材料的曲折因子。结果表明,FeAl多孔材料的曲折因子小于具有相同孔结构的不锈钢多孔材料的曲折因子。在本研究范围内,根据 Hagen-Poiseuille方程计算得知,FeAl多孔材料的曲折因子为2.26,而具有相同孔结构的不锈钢多孔材料的曲折因子为2.92。并由造孔机理探讨了FeAl多孔材料曲折因子较小的原因。

冬小麦穗发芽抗性及其鉴定方法的研究

1985—1987年在美国爱达荷大学对19个普通小麦(Triticum aestivum L.)品种进行了小麦成熟期穗发芽抗性及其鉴定方法的研究。结果表明,除红粒品种普遍抗穗发芽外,不少白粒品种也具有较强的抗性,特别是中国品种丰产3号的抗性最强,超过美国的软质白粒抗源 Peck 和 Brevor。证明小麦穗发芽与籽粒α-淀粉酶活性高度正相关,而与脱落酸含量无关,培养皿种子发芽法是鉴定穗发芽抗性的简易方法,种子发芽指数是衡量抗性强弱的可靠指标。

(TiAl)+Nb+W+B合金的微观组织演变(英文)

通过磁悬浮法制备含有W、Nb、B的重15kgTiAl合金大锭。此合金大锭与电弧熔炼的0.05kg的小样品相比,存在晶粒大小和相组织结构性质方面的区别。设计了一系列热处理工艺来消除大锭合金的高温残留β相,并获取理想的微观组织。铸态大锭合金在经过适当的热处理工艺后室温伸长率可达1.9%。这种大批量方式生产的TiAl合金,通过新合金设计与相应的热处理后,其力学性能可获得显著提高。

Fe的化学计量比对金属间化合物Ni_3Fe环境氢脆的影响

研究不同Fe化学计量比的无序态、有序态金属间化合物Ni3Fe合金在真空和氢气环境中拉伸的力学性能和断口形貌.结果表明,当Ni3Fe合金的成分偏离化学计量比时,合金的相组成不发生变化,但合金的力学性能和在氢气环境中的氢脆敏感性却随之发生变化.非化学计量的Ni3Fe合金在真空和氢气中的塑性增加,氢脆因子(IH2)降低.不同Fe化学计量比的有序态Ni3Fe合金氢脆敏感性的差异与合金的有序度有关,化学计量的Ni3Fe合金有序度最高,环境氢脆敏感性也最高;非化学计量的Ni3Fe合金有序度降低,环境氢脆敏感性也随之降低.

纳米团簇强化型铁素体钢设计中空位组元的作用

高温下可稳定存在的纳米团簇由于具有科学研究意义及潜在应用价值,已引起了研究者的强烈兴趣。利用原子探针技术在温度接近1400℃(0.92Tm)的铁基合金中观察到了高稳定的纳米团簇,从而打破了人造纳米结构材料高温不稳定性约束。在一种空位作为关键合金组元,同时(Ti+Y)/O比与稳定的TiO2和Y2Ti2O7比率不同的高缺陷新材料中,观察到直径约4nm的富氧、钛和钇纳米团簇。在钛和钇存在的条件下,空位在提高氧溶解度和氧结合能方面具有不可替代的作用,因而导致共格纳米团簇的稳定性。原子探针成像特征和理论预测表明空位可首次被作为一种纳米级组分来设计具有优良高温性能的材料。

Low Temperature Environmental Embrittlement in Ordered Intermetallics

A comprehensive review of low temperature environmental embrittlement in intermetallics is pres- ented. Moisture and hydrogen are shown to severely embrittle many intermetallics, including iron, nickel and titanium aluminides. The roles of composition, microstructure and external test variables are emphasized. Several methods to reduce or avoid embrittlement are described.

Enhanced helium ion irradiation tolerance in a Fe-Co-Ni-Cr-Al-Ti high-entropy alloy with L12 nanoparticles

L12-strengthened high entropy alloys(HEAs)with excellent room and high-temperature mechanical prop-erties have been proposed as promising candidates as structural materials for advanced nuclear systems.However,knowledge about their radiation response is fairly limited.In the present work,a novel HEA with a high density of L12 nanoparticles was irradiated with He ion at 500°C.Transmission electron microscope(TEM)and atom probe tomography(APT)were employed to study the evolution of mi-crostructural stability and radiation-induced segregation.Similar to the single-phase FeCoNiCr HEA,the main microstructural features were numerous large faulted dislocation loops and helium bubbles.While the irradiation resistance of the present L12-strengthened HEA is much improved in terms of reduced bubble size,which could be attributed to the considerable He trapping efficiency of the coherent pre-cipitate/matrix interface and the enhanced capability of the interface for damage elimination when the matrix channel width is narrow.APT analysis revealed that an inverse-Kirkendall-mechanism-dominated radiation-induced segregation(RIS)occurs around bubbles,where a significant Co enrichment and Ni de-pletion can be clearly observed.In addition,the competing dynamics of ballistic mixing and elemental clustering that raised from the irradiation-enhanced diffusion in a highly supersaturated matrix,along with the low precipitation nucleation barrier due to the small lattice misfit,lead to a dynamical pre-cipitation dissolution and re-precipitation appears under irradiation.Such a promising phenomenon is expected to promote a potential self-healing effect and could in turn provide a sustainable irradiation tolerance over the operational lifetime of a reactor.

Micro-scaled plastic yielding and shear-banding dynamics in metallic glasses

Shear-banding behavior in metallic glasses plays a key role in the operation of plastic deformation,which is associated with yield strength.In a micro-scale,the shear-banding behavior must be affected by many factors from the test machine and the substrate.Therefore,in this study,comprehensively considering a machine compliance,a geometry imperfection of micro-pillar,and a substrate sink-in the machine-sample-substrate system,we developed a plastic-strength model at a micrometer scale in this study,which is evidenced by the microscale compressive properties of 18 kinds of metallic glasses.The the-oretical model provides a guidance for the elastic limits and shear-banding dynamics of metallic glasses at the micro-scale,which can be applicable to characterize the microscale deformation behavior of other amorphous materials.

Off-stoichiometry-guided design of high-strength chemically complex intermetallic-based alloys with outstanding ductility

1.Introduction The lasting drive for improved energy efficiency in power gen-eration encourages the innovative design of advanced structural materials with superb mechanical properties[1-6].Among these materials,ordered intermetallic alloys[7-9],as a unique class of metallic materials,have drawn increasing concern from both the scientific and industrial communities due to their intriguing high-temperature properties,strong chemical binding,and low atomic mobility[10,11].However,in light of the insufficient number of slip systems and/or intrinsically weak grain boundary(GB),they are usually brittle at ambient temperature,severely hindering their practical use in engineering systems[12].Previous studies reported that the change in alloy stoichiometry has a significant beneficial effect on the ductility of intermetallic alloys.For instance,Liu et al.

Segregation enabled outstanding combination of mechanical and corrosion properties in a FeCrNi medium entropy alloy manufactured by selective laser melting

Selective laser melting(SLM)has the advantage in preparing supersaturated solid solutions due to its unique thermal field and high solidification rate.In this study,a face-centered cubic single-phase FeCrNi medium entropy alloy(MEA)with an ultrahigh Cr content(~35 at.%)was additively manufactured by SLM.The as-built MEA shows a hierarchical microstructure of coarse columnar grains and submicron dislocation cell structures,where the cell boundaries are probed segregated with Cr and C and decorated with nano carbides.The appearance of these dislocation barriers results in an excellent combination of strength(σ_(0.2)=745 MPa,σ_(UTS)=1007 MPa)and ductility(ε_(f)=31%).The current MEA also shows a superb corrosion resistance with a corrosion current density of 0.06μA cm^(−2) in 3.5 wt.%NaCl solution,which is far lower than that of 316 L.The high content of solutioned Cr in the MEA ensures sufficient Cr supply to form an integrated Cr_(2)O_(3) passive film,and the large number of cell boundaries acting as the diffusion channels lead to the fast formation of a stable passive film over the alloy surface.

Structure Heterogeneity in Metallic Glass: Modeling and Experiment

Despite the great efforts dedicated to metallic glasses （MGs）, their structure still remains a mystery to be understood. With comparison to the existing mJciomechanical models, such as the free-volume and shear transformation zone （STZ） models, we first discuss in this article our recently proposed ＇core-shell＇ model, which contains a solid-like matrix and liquid-like inclusions. This serves as the theoretical basis to understand the structural heterogeneity in MGs in our analytical framework. After that, a scanning ultrafast nanoindentation technique is used to map out the structure heterogeneity in a Zr-based bulk metallic glass （BMG）. With these ongoing research efforts, we hope that more research work could be stimulated in the pursuit of the structure-property relation in MGs.

Tailoring nanoprecipitates for ultra-strong high-entropy alloys via machine learning and prestrain aging

The multi-principal-component concept of high-entropy alloys(HEAs) generates numerous new alloys.Among them,nanoscale precipitated HEAs have achieved superior mechanical properties and shown the potentials for structural applications.However,it is still a great challe nge to find the optimal alloy within the numerous candidates.Up to now,the reported nanoprecipitated HEAs are mainly designed by a trialand-error approach with the aid of phase diagram calculations,limiting the development of structural HEAs.In the current work,a novel method is proposed to accelerate the development of ultra-strong nanoprecipitated HEAs.With the guidance of physical metallurgy,the volume fraction of the required nanoprecipitates is designed from a machine learning of big data with thermodynamic foundation while the morphology of precipitates is kinetically tailored by prestrain aging.As a proof-of-principle study,an HEA with superior strength and ductility has been designed and systematically investigated.The newly developed γ’-strengthened HEA exhibits 1.31 GPa yield strength,1.65 GPa ultimate tensile strength,and 15% tensile elongation.Atom probe tomography and transmission electron microscope characterizations reveal the well-controlled high γ’ volume fraction(52%) and refined precipitate size(19 nm).The refinement of nanoprecipitates originates from the accelerated nucleation of the γ’ phase by prestrain aging.A deeper understanding of the excellent mechanical properties is illustrated from the aspect of strengthening mecha nisms.Finally,the versatility of the current design strategy to other precipitation-hardened alloys is discussed.

Rational design of chemically complex metallic glasses by hybrid modeling guided machine learning

The compositional design of metallic glasses(MGs)is a long-standing issue in materials science and engineering.However,traditional experimental approaches based on empirical rules are time consuming with a low efficiency.In this work,we successfully developed a hybrid machine learning(ML)model to address this fundamental issue based on a database containing~5000 different compositions of metallic glasses(either bulk or ribbon)reported since 1960s.Unlike the prior works relying on empirical parameters for featurization of data,we designed modeling guided data descriptors in line with the recent theoretical models on amorphization in chemically complex alloys for the development of the hybrid classification-regression ML algorithms.Our hybrid ML modeling was validated both numerically and experimentally.Most importantly,it enabled the discovery of MGs(either bulk or ribbon)through the ML-aided deep search of a multitude of quaternary to scenery alloy compositions.The computational framework herein established is expected to accelerate the design of MG compositions and expand their applications by probing the complex and multi-dimensional compositional space that has never been explored before.