Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Gyroid Triply Periodic Minimal Surface Lattice Structure Enables Improved Superelasticity of CuAlMn Shape Memory Alloy

Improving the shape memory effect and superelasticity of Cu-based shape memory alloys(SMAs)has always been a research hotspot in many countries.This work systematically investigates the effects of Gyroid triply periodic minimal surface(TPMS)lattice structures with different unit sizes and volume fractions on the manufacturing viability,compressive mechanical response,superelasticity and heating recovery properties of CuAlMn SMAs.The results show that the increased specific surface area of the lattice structure leads to increased powder adhesion,making the manufacturability proportional to the unit size and volume fraction.The compressive response of the CuAlMn SMAs Gyroid TPMS lattice structure is negatively correlated with the unit size and positively correlated with the volume fraction.The superelastic recovery of all CuAlMn SMAs with Gyroid TPMS lattice structures is within 5%when the cyclic cumulative strain is set to be 10%.The lattice structure shows the maximum superelasticity when the unit size is 3.00 mm and the volume fraction is 12%,and after heating recovery,the total recovery strain increases as the volume fraction increases.This study introduces a new strategy to enhance the superelastic properties and expand the applications of CuAlMn SMAs in soft robotics,medical equipment,aerospace and other fields.

Advanced noble-metal-free bifunctional electrocatalysts for metal-air batteries

The sluggish reaction kinetics at the oxygen cathode is one of the important issues hindering the commercialization of the metal-air batteries.Although the noble metal can be used as the high-efficiency electrocatalyst to solve the problems to some extent,the high cost and scarcity of these noble-metal catalysts have limited their application in electrocatalysis.In this review,we discussed the mecha-nisms of the ORR and OER,and proposed the principles for the bifunctional electrocatalysts firstly,and then the state-of-the-art bifunctional catalysts,including carbon-based materials and transition-metal-based materials.On the basis of that,the self-supporting 3D noble-metal-free bifunctional ORR/OER catalysts were also discussed.Finally,the perspectives for the bifunctional electrocatalysts were discussed.

Enhanced superelasticity of Cu-Al-Ni shape memory alloys with strong orientation prepared by horizontal continuous casting

The preparation of large-scale Cu-Al-Ni shape memory alloys with excellent microstructure and texture is a significant challenge in this field.In this study,large-scale Cu-Al-Ni shape memory alloy(SMA)slabs with good surface quality and strong orientation were prepared by the horizontal continuous casting(HCC).The microstructure and mechanical properties were compared with the ordinary casting(OC)Cu-Al-Ni alloy.The results showed that the microstructure of OC Cu-Al-Ni alloy was equiaxed grains with randomly orientation,which had no obvious superelasticity.The alloys producedby Hcchad herringbone grains withstrong orientation near(100)and the cumulative tensile superelasticity of 4.58%.The superelasticity of the alloy produced by HCC has been improved by 4-5 times.This work has preliminarily realized the production of large-scale Cu-Al-Ni SMA slab with good superelasticity,which lays a foundation forexpanding the industrial production and application of Cu-based SMAs.