The good combination of mechanical and wear properties for cemented carbides is crucial.In this work,the wear behavior of functionally graded cemented carbide(FGCC)and non-graded cemented carbide(CC),with CoNiFeCr mul...The good combination of mechanical and wear properties for cemented carbides is crucial.In this work,the wear behavior of functionally graded cemented carbide(FGCC)and non-graded cemented carbide(CC),with CoNiFeCr multi-principal-element alloy(MPEA)binder,has been investigated by performing sliding wear tests and composition characterization.The results showed that compared with CC,FGCC had higher hardness,stronger fracture toughness,better wear performance,and similar TRS.FGCCs exhibited lower wear rates(3.44×10^(−7)–6.95×10^(−6)mm^(3)/(N m))and coefficients of friction(COFs)(0.27–0.39)than CCs from RT to 600℃due to mitigation of multiple risks caused by binder removal,fragmentation and pull-out of WC grains,high-temperature oxidation and softening.In the low-temperature wear stage,the MPEA binder underwent dynamic recrystallization(DRX)and twinning deformation before removing from the surface.The binder removal caused dislocation pile-ups and stacking faults(SFs)to form under high stress,resulting in fragmentation and pull-out of WC grains.The low-temperature wear was dominated by abrasive wear and adhesive wear,with a low wear rate and a high and unstable COF.In the high-temperature wear stage,initial pitting oxidation of WC grains generated many subgrain boundaries,reducing heat transfer and exacerbating oxidation,resulting in an oxide layer enriched with WO3,Mx Oy,and MWO4.High-temperature wear was dominated by oxidation wear and high-temperature softening,with a high wear rate and a low and smooth COF.The results from the present study do not only provide theoretical guidance for an understanding of the antiwear mechanism of WC-CoNiFeCr,but also a new approach for the preparation of cemented carbides with high wear resistance.展开更多
Machine learning(ML)has become a powerful tool for accelerating the design and development of new materials.Among various traditional ML algorithms,decision tree-based ensemble learning methods are frequently chosen f...Machine learning(ML)has become a powerful tool for accelerating the design and development of new materials.Among various traditional ML algorithms,decision tree-based ensemble learning methods are frequently chosen for their strong predictive capabilities.However,decision trees are limited in regression tasks to interpolating within the data range of the training set,which restricts their usefulness for designing materials with enhanced properties.Herein,we focused on predicting and optimizing the L1_(2)-phase solvus temperature(T_(L12))and density,two critical properties for multi-principal-element superalloys(MPESAs).To achieve this,we employed the piecewise symbolic regression tree(PS-Tree),which demonstrates excellent extrapolation capability.Our model successfully predicted high T_(L12)values exceeding the training data range(1242℃),with four candidate alloys achieving TL12values of 1246,1249,1254,and 1274℃.Experimental validation confirmed the accuracy of these predictions,verifying the robust extrapolative capability of the PS-Tree method.Notably,one alloy exhibited a T_(L12)of 1267℃and a density of 7.94 g cm^(-3),outperforming most MPESAs.Additionally,another alloy exhibited a compressive yield strength of 897 MPa at 750℃,with a specific yield strength at this temperature higher than that of most L1_(2)-strengthened alloys and Co/Ni-based superalloys.Moreover,the model provided generalized insights,indicating that alloys with δ_(r)>5.3 and ΔH_(mix)<-12.8 J mol^(-1)K^(-1)tend to favor higher T_(L12).展开更多
Additive manufacturing is believed to open up a new era in precise microfabrication,and the dynamic microstructure evolution during the process as well as the experiment-simulation correlated study is conducted on a p...Additive manufacturing is believed to open up a new era in precise microfabrication,and the dynamic microstructure evolution during the process as well as the experiment-simulation correlated study is conducted on a prototype multi-principal-element alloys FeCrNi fabricated using selective laser melting(SLM).Experimental results reveal that columnar crystals grow across the cladding layers and the dense cellular structures develop in the filled crystal.At the micron scale,all constituent elements are evenly distributed,while at the near-atomic scale,Cr element is obviously segregated.Simulation results at the atomic scale illustrate that i)the solid-liquid interface during the grain growth changes from horizontal to arc due to the radial temperature gradient;ii)the precipitates,microscale voids,and stacking faults also form dynamically as a result of the thermal gradient,leading to the residual stress in the SLMed structure.In addition,we established a microstructure-based physical model based on atomic simulation,which indicates that strong interface strengthening exists in the tensile deformation.The present work provides an atomic-scale understanding of the microstructural evolution in the SLM process through the combination of experiment and simulation.展开更多
Upon ageing of a deformed metal,compositional segregation to dislocations and stacking faults is well known to elevate strength.However,Suzuki segregation effects typically result in a modest strength in-crease on the...Upon ageing of a deformed metal,compositional segregation to dislocations and stacking faults is well known to elevate strength.However,Suzuki segregation effects typically result in a modest strength in-crease on the order of 10 MPa for many substitutional face-centered-cubic solid solutions.Severe pre-deformation can lead to significant hardening but often at the cost of substantial tensile ductility af-ter subsequent aging.Here we propose a novel strategy to improve the Suzuki hardening effect in a single-phase CoCrNi alloy by meticulously controlling repetitive straining and annealing conditions with-out compromising ductility.Our findings revealed that multiple stages of annealing along the way of pre-straining significantly increase the fraction of dislocations that trap partitioning species(i.e.Cr),far exceeding the levels achievable through single-shot annealing after straight pre-deformation to the same accumulative strain(40%).Thermodynamically,the segregation of Cr into stacking faults is driven by re-duced local stacking fault energy(SEF)and system energy.The decreased SFE inhibits dislocation cross-slip,promotes partial dislocation nucleation,and facilitates dislocation intersection,leading to a high den-sity of extended stacking fault ribbons in the multi-pass strained and annealed samples.As a result,the yield strength increments of multi-pass treated samples(75±10 MPa)are four times higher than those of single-pass treated samples(18±8 MPa),while retaining an adequate strain hardening rate,thus pre-serving tensile ductility despite of plastic flow at higher stresses.Our strategy shows promise for broader applications,particularly in scenarios where conventional thermomechanical treatments fail to yield sat-isfactory results.展开更多
基金financially supported by the National Key Research and Development Program of China(No.2021YFB3701800)Special funding support for the Yuelu Mountain National University Science and Technology City“Ranking the Top of the List”Research Project:(Tunnel Boring Machine High-performance Long-life Cutting Tools)the State Key Laboratory of Powder Metallurgy,Central South University,Changsha,China.
文摘The good combination of mechanical and wear properties for cemented carbides is crucial.In this work,the wear behavior of functionally graded cemented carbide(FGCC)and non-graded cemented carbide(CC),with CoNiFeCr multi-principal-element alloy(MPEA)binder,has been investigated by performing sliding wear tests and composition characterization.The results showed that compared with CC,FGCC had higher hardness,stronger fracture toughness,better wear performance,and similar TRS.FGCCs exhibited lower wear rates(3.44×10^(−7)–6.95×10^(−6)mm^(3)/(N m))and coefficients of friction(COFs)(0.27–0.39)than CCs from RT to 600℃due to mitigation of multiple risks caused by binder removal,fragmentation and pull-out of WC grains,high-temperature oxidation and softening.In the low-temperature wear stage,the MPEA binder underwent dynamic recrystallization(DRX)and twinning deformation before removing from the surface.The binder removal caused dislocation pile-ups and stacking faults(SFs)to form under high stress,resulting in fragmentation and pull-out of WC grains.The low-temperature wear was dominated by abrasive wear and adhesive wear,with a low wear rate and a high and unstable COF.In the high-temperature wear stage,initial pitting oxidation of WC grains generated many subgrain boundaries,reducing heat transfer and exacerbating oxidation,resulting in an oxide layer enriched with WO3,Mx Oy,and MWO4.High-temperature wear was dominated by oxidation wear and high-temperature softening,with a high wear rate and a low and smooth COF.The results from the present study do not only provide theoretical guidance for an understanding of the antiwear mechanism of WC-CoNiFeCr,but also a new approach for the preparation of cemented carbides with high wear resistance.
基金financially supported by the National Natural Science Foundation of China(Nos.52371007 and 52301042)the National Key R&D Program of China(No.2020YFB0704503)+2 种基金Shenzhen Science and Technology Program(No.SGDX20210823104002016)Guangdong Basic and Applied Basic Research Foundation(No.2021B1515120071)Shenzhen Basic Research Project(No.JCYJ20241202123504007)
文摘Machine learning(ML)has become a powerful tool for accelerating the design and development of new materials.Among various traditional ML algorithms,decision tree-based ensemble learning methods are frequently chosen for their strong predictive capabilities.However,decision trees are limited in regression tasks to interpolating within the data range of the training set,which restricts their usefulness for designing materials with enhanced properties.Herein,we focused on predicting and optimizing the L1_(2)-phase solvus temperature(T_(L12))and density,two critical properties for multi-principal-element superalloys(MPESAs).To achieve this,we employed the piecewise symbolic regression tree(PS-Tree),which demonstrates excellent extrapolation capability.Our model successfully predicted high T_(L12)values exceeding the training data range(1242℃),with four candidate alloys achieving TL12values of 1246,1249,1254,and 1274℃.Experimental validation confirmed the accuracy of these predictions,verifying the robust extrapolative capability of the PS-Tree method.Notably,one alloy exhibited a T_(L12)of 1267℃and a density of 7.94 g cm^(-3),outperforming most MPESAs.Additionally,another alloy exhibited a compressive yield strength of 897 MPa at 750℃,with a specific yield strength at this temperature higher than that of most L1_(2)-strengthened alloys and Co/Ni-based superalloys.Moreover,the model provided generalized insights,indicating that alloys with δ_(r)>5.3 and ΔH_(mix)<-12.8 J mol^(-1)K^(-1)tend to favor higher T_(L12).
基金supported by the National Natural Science Foundation of China(Nos.52020105013,51871092,and 11902113)the Natural Science Foundation of Hunan Province(Nos.2019JJ50068 and 2021JJ40032)+1 种基金the Changsha Municipal Natu-ral Science Foundation(No.kq2014126)support from the National Science Foundation(Nos.DMR-1611180 and 1809640).
文摘Additive manufacturing is believed to open up a new era in precise microfabrication,and the dynamic microstructure evolution during the process as well as the experiment-simulation correlated study is conducted on a prototype multi-principal-element alloys FeCrNi fabricated using selective laser melting(SLM).Experimental results reveal that columnar crystals grow across the cladding layers and the dense cellular structures develop in the filled crystal.At the micron scale,all constituent elements are evenly distributed,while at the near-atomic scale,Cr element is obviously segregated.Simulation results at the atomic scale illustrate that i)the solid-liquid interface during the grain growth changes from horizontal to arc due to the radial temperature gradient;ii)the precipitates,microscale voids,and stacking faults also form dynamically as a result of the thermal gradient,leading to the residual stress in the SLMed structure.In addition,we established a microstructure-based physical model based on atomic simulation,which indicates that strong interface strengthening exists in the tensile deformation.The present work provides an atomic-scale understanding of the microstructural evolution in the SLM process through the combination of experiment and simulation.
基金sponsored by the National Key Research and Development Program,Major Scientific Instrument Special Pro-gram for Basic Research-Development and Application of All-domestic Three-dimensional Atom Probe Precision Measurement Instrument Project(No.2023YFF0716200)the State Key Lab-oratory of Powder Metallurgy,Central South University,Changsha,China.Q.Cheng was supported by the China Postdoctoral Science Foundation(No.2023M741111,No.GZC20230752)+2 种基金E.Ma acknowl-edges the National Natural Science Foundation of China(Grant No.52231001)J.Ding was supported by the Natural Science Founda-tion of China(Grant No.12004294)the National Youth Talents Program and the HPC platform of Xi’an Jiaotong University.M.W.Chen was supported by the U.S.National Science Foundation grant DMR-1804320.J.H.Chen acknowledges the financial support from the National Natural Science Foundation of China(No.51831004)。
文摘Upon ageing of a deformed metal,compositional segregation to dislocations and stacking faults is well known to elevate strength.However,Suzuki segregation effects typically result in a modest strength in-crease on the order of 10 MPa for many substitutional face-centered-cubic solid solutions.Severe pre-deformation can lead to significant hardening but often at the cost of substantial tensile ductility af-ter subsequent aging.Here we propose a novel strategy to improve the Suzuki hardening effect in a single-phase CoCrNi alloy by meticulously controlling repetitive straining and annealing conditions with-out compromising ductility.Our findings revealed that multiple stages of annealing along the way of pre-straining significantly increase the fraction of dislocations that trap partitioning species(i.e.Cr),far exceeding the levels achievable through single-shot annealing after straight pre-deformation to the same accumulative strain(40%).Thermodynamically,the segregation of Cr into stacking faults is driven by re-duced local stacking fault energy(SEF)and system energy.The decreased SFE inhibits dislocation cross-slip,promotes partial dislocation nucleation,and facilitates dislocation intersection,leading to a high den-sity of extended stacking fault ribbons in the multi-pass strained and annealed samples.As a result,the yield strength increments of multi-pass treated samples(75±10 MPa)are four times higher than those of single-pass treated samples(18±8 MPa),while retaining an adequate strain hardening rate,thus pre-serving tensile ductility despite of plastic flow at higher stresses.Our strategy shows promise for broader applications,particularly in scenarios where conventional thermomechanical treatments fail to yield sat-isfactory results.
