Magnetic and mechanical hardening of nano-lamellar magnets using thermo-magnetic fields.

High-performance magnetic materials based on rare-earth intermetallic compounds are critical for energy conversion technologies. However, the high cost and supply risks of rare-earth elements necessitate the development of affordable alternatives. Another challenge lies in the inherent brittleness of current magnets, which limits their applications for high dynamic mechanical loading conditions during service and complex shape design during manufacturing towards high efficiency and sustainability.

Sustainable high-entropy materials?

High-entropy materials (HEMs) show inspiring structural and functional properties due to their multi-elemental compositions. However, most HEMs are burdened by cost-, energy-, and carbon-intensive extraction, synthesis, and manufacturing protocols. Recycling and reusing HEMs are challenging because their design relies on high fractions of expensive and limited-supply elements in massive solid solutions.

Two-gigapascal-strong ductile soft magnets.

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.

Strong and ductile Resinvar alloys with temperature- and time-independent resistivity.

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.

Thermodynamics-Guided High-Throughput Discovery of Eutectic High-Entropy Alloys for Rapid Solidification.

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.

Strong and ductile high temperature soft magnets through Widmanstätten precipitates.

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.

Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography.

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.

Machine learning-enabled constrained multi-objective design of architected materials.

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.

A mechanically strong and ductile soft magnet with extremely low coercivity.

Soft magnetic materials (SMMs) serve in electrical applications and sustainable energy supply, allowing magnetic flux variation in response to changes in applied magnetic field, at low energy loss. The electrification of transport, households and manufacturing leads to an increase in energy consumption owing to hysteresis losses. Therefore, minimizing coercivity, which scales these losses, is crucial.

Ultrastrong and Ductile Soft Magnetic High-Entropy Alloys via Coherent Ordered Nanoprecipitates.

The lack of strength and damage tolerance can limit the applications of conventional soft magnetic materials (SMMs), particularly in mechanically loaded functional devices. Therefore, strengthening and toughening of SMMs is critically important. However, conventional strengthening concepts usually significantly deteriorate soft magnetic properties, due to Bloch wall interactions with the defects used for hardening.