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Abstract Soft magnetic materials (SMMs) are indispensable for electromechanical energy conversion in high-efficiency applications, but they are exposed to increasing mechanical loading conditions in electric motors due to higher rotational speeds. Enhancing the yield strength of SMMs is essential to prevent the degradation in magnetic performance and failure from plastic deformation, yet most SMMs have yield strengths far below one gigapascal. Here, we present a multicomponent nanostructuring strategy that doubles the yield strength of SMMs while maintaining ductility. We introduce morphologically anisotropic nanoprecipitates through dislocation-driven precipitation induced by preceding deformation during heat treatment in an iron–nickel–cobalt–tantalum material. With all dimensions of the precipitates below the magnetic domain wall width, we achieve a high precipitate number density with a large specific surface area, small interprecipitate spacing, and high lattice mismatch, which impede dislocation glide and strengthen the material. Both the matrix and precipitates are ferromagnetic, yielding a high magnetic moment. This nanostructuring approach offers a pathway to two-gigapascal-strong ductile SMMs with moderately increased coercivity that can be tolerated in exchange for significantly improved mechanical performance for sustainable electrification.

Abstract Materials with well-defined electrical resistivity that does not change with temperature or time are important in robotics, communication and automation. However, the challenge of designing such materials has remained elusive due to the temperature-dependent electron-phonon scattering. Moreover, resistive electrical conductors used in flexible and mobile systems under high mechanical loads must possess both high strength and ductility. Achieving such multi-properties presents a fundamental challenge. Here, we solve this problem by combining multicomponent alloy design with atomic-scale chemistry tuning. We term the resultant material ‘Resinvar’ alloy, due to its invariable resistivity (148 μΩ·cm) over wide temperature ranges from room temperature to 723 K. The alloy also has high tensile strength (948 MPa) at large tensile elongation (53%). The distorted lattice, chemical short-range order and ordered coherent nanoprecipitates in the material enable the invariant resistivity via promoting temperature-independent inelastic electron scattering, and contribute to the excellent strength-ductility synergy by manipulating dislocation slip.

Abstract Excellent castability, significantly refined microstructure, and good mechanical properties make eutectic high‐entropy alloys (EHEAs) a natural fit for rapid solidification processes, e.g., additive manufacturing. Previous investigations have focused on developing EHEAs through trial and error and mixing known binary eutectic materials. However, eutectic compositions obtained from near‐equilibrium conditions do not guarantee a fully eutectic microstructure under rapid solidifications. In this work, a thermodynamically guided high‐throughput framework is proposed to design EHEAs for rapid solidification. Empirical formulas derived from past experimental observations and thermodynamic computations are applied and considered phase growth kinetics under rapid solidification (skewed phase diagram). The designed alloy candidate, Co25.6Fe17.9Ni22.4Cr19.1Ta8.9Al6.1 (wt.%), contains nanostructured eutectic lamellar and shows a high Vickers hardness of 675 Hv. In addition to this specific composition, the alloy design toolbox enables the development of new EHEAs for rapid solidification without the limitation of previous knowledge.

Abstract Fast growth of sustainable energy production requires massive electrification of transport, industry and households, with electrical motors as key components. These need soft magnets with high saturation magnetization, mechanical strength, and thermal stability to operate efficiently and safely. Reconciling these properties in one material is challenging because thermally-stable microstructures for strength increase conflict with magnetic performance. Here, we present a material concept that combines thermal stability, soft magnetic response, and high mechanical strength. The strong and ductile soft ferromagnet is realized as a multicomponent alloy in which precipitates with a large aspect ratio form a Widmanstätten pattern. The material shows excellent magnetic and mechanical properties at high temperatures while the reference alloy with identical composition devoid of precipitates significantly loses its magnetization and strength at identical temperatures. The work provides a new avenue to develop soft magnets for high-temperature applications, enabling efficient use of sustainable electrical energy under harsh operating conditions.

Abstract Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix to form particular atomic neighbourhoods. CSRO is typically characterized indirectly, using volume-averaged or through projection microscopy techniques that fail to capture the three-dimensional atomistic architectures. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography enabling three-dimensional imaging of multiple CSROs. We showcase our approach by addressing a long-standing question encountered in body-centred-cubic Fe-Al alloys that see anomalous property changes upon heat treatment. We use it to evidence non-statistical B2-CSRO instead of the generally-expected D03-CSRO. We introduce quantitative correlations among annealing temperature, CSRO, and nano-hardness and electrical resistivity. Our approach is further validated on modified D03-CSRO detected in Fe-Ga. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in different materials and help design future high-performance materials.

Abstract Architected materials that consist of multiple subelements arranged in particular orders can demonstrate a much broader range of properties than their constituent materials. However, the rational design of these materials generally relies on experts’ prior knowledge and requires painstaking effort. Here, we present a data-efficient method for the high-dimensional multi-property optimization of 3D-printed architected materials utilizing a machine learning (ML) cycle consisting of the finite element method (FEM) and 3D neural networks. Specifically, we apply our method to orthopedic implant design. Compared to uniform designs, our experience-free method designs microscale heterogeneous architectures with a biocompatible elastic modulus and higher strength. Furthermore, inspired by the knowledge learned from the neural networks, we develop machine-human synergy, adapting the ML-designed architecture to fix a macroscale, irregularly shaped animal bone defect. Such adaptation exhibits 20% higher experimental load-bearing capacity than the uniform design. Thus, our method provides a data-efficient paradigm for the fast and intelligent design of architected materials with tailored mechanical, physical, and chemical properties.

A Co25.1Cr18.8Fe23.3Ni22.6Ta8.5Al1.7 (at. %) eutectic high-entropy alloy (EHEA) consisting of face-centered-cubic (FCC) and C14 Laves phases was produced by powder metallurgy. The EHEA shows an equiaxed morphology that is different from eutectic lamellar structure. Nanometer L12 phase (4–5 nm) further precipitates in FCC matrix. The microstructure is highly stable upon annealing at 1000°C for 100 h, which leads to attractive high-temperature strength. The fracture behaviour is observed to be modified by the equiaxed Laves phase, which contains microcracks induced by multiple dislocation slips. The diversified cracking modes help to relieve stress concentration and therefore enhance ductility at high temperatures.

We developed a eutectic high-entropy alloy (EHEA) with appreciable high-temperature strength-plasticity balance. Structural characterizations of the as-cast sample revealed a lamellar structure with austenite (face-centered-cubic, FCC) and Laves phases. Upon annealing at 873 K, precipitation of nanoscale (Ni, Al, and Zr)-rich L12 phase from the FCC phase took place, which eventually transformed into a martensitic (hexagonal, ε) phase with rearrangement of atomic species. Compressive properties revealed a brittle behavior at temperatures below 873 K, but changed to a ductile behavior with considerable strain hardening at 973 K, due to the formation of a high density of deformation twins observed by transmission electron microscopy.