Microstructure and mechanical properties of non-equiatomic(CuNi)_(100-x)Co_(x)(x=15,20,25 and 30,at.%)medium-entropy alloys(MEAs)prepared by vacuum arc-melting were investigated.Results show that all the as-cast MEAs ...Microstructure and mechanical properties of non-equiatomic(CuNi)_(100-x)Co_(x)(x=15,20,25 and 30,at.%)medium-entropy alloys(MEAs)prepared by vacuum arc-melting were investigated.Results show that all the as-cast MEAs exhibit dual face-centered cubic(fcc)solid-solution phases with identical lattice constant,showing typical dendrite structure consisting of(Ni,Co)-rich phase in dendrites and Cu-rich phase in inter-dendrites.The positive enthalpy of mixing among Cu and Ni-Co elements is responsible for the segregation of Cu.With the increase of Co content,the volume fraction of(Ni,Co)-rich phase increases while the Cu-rich phase decreases,resulting in an increment of yield strength and a decrement of elongation for the(CuNi)_(100-x)Co_(x) MEAs.Nano-indentation test results show a great difference of microhardness between the two fcc phases of the MEAs.The measured microhardness value of the(Ni,Co)-rich phase is almost twofold as compared to that of the Cu-rich phase in all the(CuNi)_(100-x)Co_(x) MEAs.During the deformation of the MEAs,the Cu-rich phase bears the main plastic strain,whereas the(Ni,Co)-rich phase provides more pronounced strengthening.展开更多
During powder production,the pre-alloyed powder composition often deviates from the target composition leading to undesirable properties of additive manufacturing(AM)components.Therefore,we developed a method to perfo...During powder production,the pre-alloyed powder composition often deviates from the target composition leading to undesirable properties of additive manufacturing(AM)components.Therefore,we developed a method to perform high-throughput calculation and uncertainty quantification by using a CALPHAD-based ICME framework(CALPHAD:calculations of phase diagrams,ICME:integrated computational materials engineering)to optimize the composition,and took the high-strength low-alloy steel(HSLA)as a case study.We analyzed the process–structure–property relationships for 450,000 compositions around the nominal composition of HSLA-115.Properties that are critical for the performance,such as yield strength,impact transition temperature,and weldability,were evaluated to optimize the composition.With the same uncertainty as to the initial composition,and optimized average composition has been determined,which increased the probability of achieving successful AM builds by 44.7%.The present strategy is general and can be applied to other alloy composition optimization to expand the choices of alloy for additive manufacturing.Such a method also calls for high-quality CALPHAD databases and predictive ICME models.展开更多
基金the financial supports from the National Natural Science Foundation of China (No. 52103360)the Basic and Applied Basic Research Foundation of Guangdong Province, China (No. 2020A1515111104)+1 种基金the Key-Area Research and Development Program of Guangdong Province (No. 2018B090905002)the technical support of Sinoma Institute of Materials Research (Guangzhou) Co., Ltd. (China)。
基金supported by the Key-Area Research and Development Program of Guangdong Province(Grant No.2018B090905002)the National Natural Science Foundation of China(Grant No.52103360)the Basic Research Foundation of Guangzhou City(Grant No.201804020071).
文摘Microstructure and mechanical properties of non-equiatomic(CuNi)_(100-x)Co_(x)(x=15,20,25 and 30,at.%)medium-entropy alloys(MEAs)prepared by vacuum arc-melting were investigated.Results show that all the as-cast MEAs exhibit dual face-centered cubic(fcc)solid-solution phases with identical lattice constant,showing typical dendrite structure consisting of(Ni,Co)-rich phase in dendrites and Cu-rich phase in inter-dendrites.The positive enthalpy of mixing among Cu and Ni-Co elements is responsible for the segregation of Cu.With the increase of Co content,the volume fraction of(Ni,Co)-rich phase increases while the Cu-rich phase decreases,resulting in an increment of yield strength and a decrement of elongation for the(CuNi)_(100-x)Co_(x) MEAs.Nano-indentation test results show a great difference of microhardness between the two fcc phases of the MEAs.The measured microhardness value of the(Ni,Co)-rich phase is almost twofold as compared to that of the Cu-rich phase in all the(CuNi)_(100-x)Co_(x) MEAs.During the deformation of the MEAs,the Cu-rich phase bears the main plastic strain,whereas the(Ni,Co)-rich phase provides more pronounced strengthening.
基金The financial support received from the Office of Naval Research,Office of Naval Research(ONR)Additive Manufacturing Alloys for Naval Environments(AMANE)program(Contract no.N00014-17-1-2586)is gratefully acknowledged for performing the current research.
文摘During powder production,the pre-alloyed powder composition often deviates from the target composition leading to undesirable properties of additive manufacturing(AM)components.Therefore,we developed a method to perform high-throughput calculation and uncertainty quantification by using a CALPHAD-based ICME framework(CALPHAD:calculations of phase diagrams,ICME:integrated computational materials engineering)to optimize the composition,and took the high-strength low-alloy steel(HSLA)as a case study.We analyzed the process–structure–property relationships for 450,000 compositions around the nominal composition of HSLA-115.Properties that are critical for the performance,such as yield strength,impact transition temperature,and weldability,were evaluated to optimize the composition.With the same uncertainty as to the initial composition,and optimized average composition has been determined,which increased the probability of achieving successful AM builds by 44.7%.The present strategy is general and can be applied to other alloy composition optimization to expand the choices of alloy for additive manufacturing.Such a method also calls for high-quality CALPHAD databases and predictive ICME models.
