Microstructural and mechanical behavior of a CoCrFeNiCu_4 non-equiatomic high entropy alloy

High entropy alloy(HEA)-based alloy design is experiencing a conceptual broadening from equiatomic alloys to non-equiatomic alloys.To provide experimental basis for designing Cu-rich non-equiatomic HEAs,in the current study,a dual phase(Cu-rich and CoCrFeNi-rich phases) face-centered cubic CoCrFeNiCu_(4) alloy was systematically investigated.We provided initial and experiment-based understanding of the behavioral change of the alloy during a variety of thermal cycles and thermomechanical processing.The current results indicate that,during heating,preferred precipitation of Cu-rich particles occurs,leading to more pronounced compositional differences between the two constituent FCC phases and increased relative volume fraction of the Cu-rich phase.The Alloy exhibits a continuous melting and discontinuous solidification of the Cu-rich and CoCrFeNi-rich phases.After being cold-rolled to ~90 % thickness reduction,the alloy exhibits a recrystallization temperature higher than 800℃.Annealing at 300 and 500℃ led to strength reduction and/or ductility decrease;further increasing annealing temperature monotonically caused softening and ductilization due to decreased density of pre-existing dislocations.The yield-drop phenomena observed for the 900℃-and 1000℃-annealed specimens are associated with the locking of pre-existing dislocations by some "atmosphere",the nature of which warrants further elucidation.

Strengthening in Al-,Mo-or Ti-doped CoCrFeNi high entropy alloys:A parallel comparison

In the current work,a parallel comparison of the influence of Al,Mo and Ti,on the microstructure and strengthening of the CoCrFeNi alloy was conducted.To achieve this,inconsistencies on variables including the extent of alloying,thermomechanical processing and property-evaluation method were avoided.Microstructurally,following cold-rolling,annealing of the 4 at.%Al-doped alloys at 800-1000℃ did not result in phase separation;nevertheless,that of the 4 at.%Mo-and Ti-doped alloys led to the respective formation ofσandηphase and,consequently,caused extra strengthening through the Orowan dislocation bypassing mechanism.Our systematic qualitative analysis and DFT calculations showed that Al and Ti are more effective than Mo in reducing the stacking fault energy(SFE)of the CoCrFeNi alloy,because they can induce more considerable deformation of electronic density,making the gliding of atomic layers easier.Following identical thermomechnical processing,Al-,Mo-,and Ti-doping causes different extent of solid solution strengthening and grain boundary strengthening.Mo causes the most pronounced solid solution strengthening but does not benefit the grain boundary strengthening;in contrast,the effectiveness of grain boundary strengthening is boosted by the doping Al and Ti.Current analyses support that Labusch instead of Fleischer mechanism is applicable to explain the differences in solid solution strengthening,and the observed differences in grain boundary strengthening arise from the different tendency of Al,Mo and Ti to reduce the SFE of CoCrFeNi.In addition,we determined the value of the dimensionless parameter f in the Labusch model for CoCrFeNi-based alloys and observed a close relation between Hall-Petch slope and SFE.Although more in-depth studies are needed to provide full and mechanistic understandings,both these findings in fact presents significant values toward designing novel singlephase high-strength CoCrFeNi-based alloys through manipulating the solid solution and grain boundary strengthening by compositional tuning.

Copy number variation profile-based genomic typing of premenstrual dysphoric disorder in Chinese

Premenstrual dysphoric disorder(PMDD) affects nearly 5% of women of reproductive age. Symptomatic heterogeneity, together with largely unknown genetics, has greatly hindered its effective treatment. In the present study, analysis of genomic sequencing-based copy number variations(CNVs) called from 100 kb white blood cell DNA sequence windows by means of semisupervized clustering led to the segregation of patient genomes into the D and V groups, which correlated with the depression and invasion clinical types,respectively, with 89.0% consistency. Application of diagnostic CNV features selected using the correlation-based machine learning method enabled the classification of the CNVs obtained into the D group, V group, total patient group, and control group with an average accuracy of 83.0%. The power of the diagnostic CNV features was 0.98 on average, suggesting that these CNV features could be used for the molecular diagnosis of the major clinical types of PMDD. This demonstrated concordance between the CNV profiles and clinical types of PMDD supported the validity of symptom-based diagnosis of PMDD for differentiating between its two major clinical types, as well as the predominantly genetic nature of PMDD with a host of overlaps between multiple susceptibility genes/pathways and the diagnostic CNV features as indicators of involvement in PMDD etiology.

Nature of CoCrFeMnNi/Fe and CoCrFeMnNi/Al Solid/Solid Interface

To shed light into the application potential of high-entropy alloys as"interlayer"materials for Al-steel solid-state joining,we investigated the nature of the CoCrFeMnNi/Fe and CoCrFeMnNi/Al solid/solid interfaces,focusing on the bonding behavior and phase components.Good metallurgical bonding without the formation of hard and brittle IMC can be achieved for CoCrFeMnNi/Fe solid/solid interface.In contrast to the formation of Al5 Fe2 phase at the Fe/Al interface,Al13Fe4-type IMC,in which the Fe site is co-occupied equally by Co,Cr,Fe,Mn and Ni,dominates the CoCrFeMnNi/Al interface.Although the formation of IMC at the CoCrFeMnNi/Al interface is not avoidable,the thickness and hardness of the Al13(CoCrFeMnNi)4 phase formed at the CoCrFeMnNi/Al interface are significantly lower than the Al5 Fe2 phase formed at the Fe/Al interface.The activation energies for the interdiffusion of Fe/Al and CoCrFeMnNi/Al static diffusion couple are 341.6 kJ/mol and 329.5 kJ/mol,respectively.Despite this similarity,under identical static annealing condition,the interdiffusion coe fficient of the CoCrFeMnNi/Al diffusion couple is significantly lower than that of the Fe/Al diffusion couple.This is thus mainly a result of the reduced atomic mobility/diffusivity caused by the compositional complexity in CoCrFeMnNi high-entropy alloy.

Stress-controlled fatigue of HfNbTaTiZr high-entropy alloy and associated deformation and fracture mechanisms

The stress-controlled fatigue tests are carried out at a stress ratio of 0.1 and a frequency of 10 Hz,and span both low-cycle and high-cycle regimes by varying the applied stress amplitudes.The high-cycle fa-tigue regime gives a fatigue strength of 497 MPa and a fatigue ratio of 0.44.At equivalent conditions,the alloy’s fatigue strength is greater than all other high-entropy alloys(HEAs)with reported high-cycle fatigue data,dilute body-centered cubic alloys,and many structural alloys such as steels,titanium al-loys,and aluminum alloys.Through in-depth analyses of crack-propagation trajectories,fracture-surface morphologies and deformation plasticity by means of various microstructural analysis techniques and theoretical frameworks,the alloy’s remarkable fatigue resistance is attributed to delayed crack initiation in the high-cycle regime,which is achieved by retarding the formation of localized persistent slip bands,and its good resistance to crack propagation in the low-cycle regime,which is accomplished by intrin-sic toughening backed up by extrinsic toughening.Moreover,the stochastic nature of the fatigue data is neatly captured with a 2-parameter Weibull model.

Corrigendum to“Stress-controlled fatigue of HfNbTaTiZr high-entropy alloy and associated deformation and fracture mechanisms”[Journal of Materials Science&Technology,114(2022)191-205]

The authors regret<to remove Prof.Jien-Wei Yeh from the authorship for some reason.The removal is agreed by Prof.Jien-Wei Yeh>.The authors would like to apologise for any inconvenience caused.

Design high-entropy carbide ceramics from machine learning

High-entropy ceramics(HECs)have shown great application potential under demanding conditions,such as high stresses and temperatures.However,the immense phase space poses great challenges for the rational design of new high-performance HECs.In this work,we develop machine-learning(ML)models to discover high-entropy ceramic carbides(HECCs).Built upon attributes of HECCs and their constituent precursors,our ML models demonstrate a high prediction accuracy(0.982).Using the well-trained ML models,we evaluate the single-phase probability of 90 HECCs that are not experimentally reported so far.Several of these predictions are validated by our experiments.We further establish the phase diagrams for non-equiatomic HECCs spanning the whole composition space by which the single-phase regime can be easily identified.Our ML models can predict both equiatomic and non-equiatomic HECs based solely on the chemical descriptors of constituent transition-metal-carbide precursors,which paves the way for the high-throughput design of HECCs with superior properties.