Explore the vast range of titles available.

Room-temperature skyrmions in magnetic multilayers are considered to be promising candidates for the next-generation spintronic devices. Several approaches have been developed to control skyrmions, but they either cause significant heat dissipation or require ultrahigh electric fields near the breakdown threshold. Here, we demonstrate electric-field control of skyrmions through strain-mediated magnetoelectric coupling in ferromagnetic/ferroelectric multiferroic heterostructures. We show the process of non-volatile creation of multiple skyrmions, reversible deformation and annihilation of a single skyrmion by performing magnetic force microscopy with in situ electric fields. Strain-induced changes in perpendicular magnetic anisotropy and interfacial Dzyaloshinskii–Moriya interaction strength are characterized experimentally. These experimental results, together with micromagnetic simulations, demonstrate that strain-mediated magnetoelectric coupling (via strain-induced changes in both the perpendicular magnetic anisotropy and interfacial Dzyaloshinskii–Moriya interaction is responsible for the observed electric-field control of skyrmions. Our work provides a platform to investigate electric-field control of skyrmions in multiferroic heterostructures and paves the way towards more energy-efficient skyrmion-based spintronics. The common approaches to control of skymions cause significant heat dissipation or require high electric fields near the breakdown threshold. Here, the authors demonstrate electric-field control of skyrmions through strain-mediated magnetoelectric coupling in multiferroic heterostructures.

Various machine learning models have been used to predict the properties of polycrystalline materials, but none of them directly consider the physical interactions among neighboring grains despite such microscopic interactions critically determining macroscopic material properties. Here, we develop a graph neural network (GNN) model for obtaining an embedding of polycrystalline microstructure which incorporates not only the physical features of individual grains but also their interactions. The embedding is then linked to the target property using a feed-forward neural network. Using the magnetostriction of polycrystalline Tb0.3Dy0.7Fe2 alloys as an example, we show that a single GNN model with fixed network architecture and hyperparameters allows for a low prediction error of ~10% over a group of remarkably different microstructures as well as quantifying the importance of each feature in each grain of a microstructure to its magnetostriction. Such a microstructure-graph-based GNN model, therefore, enables an accurate and interpretable prediction of the properties of polycrystalline materials.

With its extremely strong capability of data analysis, machine learning has shown versatile potential in the revolution of the materials research paradigm. Here, taking dielectric capacitors and lithium‐ion batteries as two representative examples, we review substantial advances of machine learning in the research and development of energy storage materials. First, a thorough discussion of the machine learning framework in materials science is presented. Then, we summarize the applications of machine learning from three aspects, including discovering and designing novel materials, enriching theoretical simulations, and assisting experimentation and characterization. Finally, a brief outlook is highlighted to spark more insights on the innovative implementation of machine learning in materials science. Machine learning is transforming the research paradigm of materials science in recent years. This review summarizes the recent advances of machine learning in the research and development of energy storage materials and provides some insights on the innovative implementation of machine learning in materials science.

The main bottlenecks limiting the practical applications of current magnetoresistive random access memory (MRAM) technology are its low storage density and high writing energy consumption. Although a number of proposals have been reported for voltage-controlled memory device in recent years, none of them simultaneously satisfy the important device attributes: high storage capacity, low power consumption and room temperature operation. Here we present, using phase-field simulations, a simple and new pathway towards high-performance MRAMs that display significant improvements over existing MRAM technologies or proposed concepts. The proposed nanoscale MRAM device simultaneously exhibits ultrahigh storage capacity of up to 88 Gb inch −2 , ultralow power dissipation as low as 0.16 fJ per bit and room temperature high-speed operation below 10 ns. Magnetoresistive random access memory offers significant promise as a next-generation memory technology. Nan and colleagues present a design concept for a device that simultaneously possesses ultrahigh storage capacity, ultralow power dissipation, and high-speed operation at room temperature.

Magnetic skyrmions are swirling spin structures stabilized typically by the Dyzaloshinskii-Moriya interaction. The existing control of magnetic skyrmions has often relied on the use of an electric current, which may cause overheating in densely packed devices. Here we demonstrate, using phase-field simulations, that an isolated Néel skyrmion in a magnetic nanodisk can be repeatedly created and deleted by voltage-induced strains from a juxtaposed piezoelectric. Such a skyrmion switching is non-volatile, and consumes only ~0.5 fJ per switching which is about five orders of magnitude smaller than that by current-induced spin-transfer-torques. It is found that the strain-mediated skyrmion creation occurs through an intermediate vortex-like spin structure, and that the skyrmion deletion occurs though a homogenous shrinkage during which the Néel wall is temporarily transformed to a vortex-wall. These findings are expected to stimulate experimental research into strain-mediated voltage control of skyrmions, as well as other chiral spin structures for low-power spintronics.

The anomalous Hall effect (AHE) is a quantum coherent transport phenomenon that conventionally vanishes at elevated temperatures because of thermal dephasing. Therefore, it is puzzling that the AHE can survive in heavy metal (HM)/antiferromagnetic (AFM) insulator (AFMI) heterostructures at high temperatures yet disappears at low temperatures. In this paper, an unconventional high‐temperature AHE in HM/AFMI is observed only around the Néel temperature of AFM, with large anomalous Hall resistivity up to 40 nΩ cm is reported. This mechanism is attributed to the emergence of a noncollinear AFM spin texture with a non‐zero net topological charge. Atomistic spin dynamics simulation shows that such a unique spin texture can be stabilized by the subtle interplay among the collinear AFM exchange coupling, interfacial Dyzaloshinski–Moriya interaction, thermal fluctuation, and bias magnetic field. An unconventional high‐temperature anomalous Hall effect was achieved in NiO‐based heavy metal/antiferromagnetic insulator heterostructures by controlling the antiferromagnetic‐paramagnetic transition. The anomalous Hall resistivity reached up to 40 nΩ cm. Atomistic spin dynamics simulations show that a noncollinear antiferromagnetic spin texture with a non‐zero net topological charge can be stabilized and cause such a significant anomalous Hall effect.

Magnetoelectric composites and heterostructures integrate magnetic and dielectric materials to produce new functionalities, e.g., magnetoelectric responses that are absent in each of the constituent materials but emerge through the coupling between magnetic order in the magnetic material and electric order in the dielectric material. The magnetoelectric coupling in these composites and heterostructures is typically achieved through the exchange of magnetic, electric, or/and elastic energy across the interfaces between the different constituent materials, and the coupling effect is measured by the degree of conversion between magnetic and electric energy in the absence of an electric current. The strength of magnetoelectric coupling can be tailored by choosing suited materials for each constituent and by geometrical and microstructural designs. In this article, we discuss recent progresses on the understanding of magnetoelectric coupling mechanisms and the design of magnetoelectric heterostructures guided by theory and computation. We outline a number of unsolved issues concerning magnetoelectric heterostructures. We compile a relatively comprehensive experimental dataset on the magnetoelecric coupling coefficients in both bulk and thin-film magnetoelectric composites and offer a perspective on the data-driven computational design of magnetoelectric composites at the mesoscale microstructure level.

Multiferroic magnetoelectric nanostructures with coupled magnetization and electric polarization across their interfaces have stimulated intense research activities over the past decade. Such interface-based magnetoelectric coupling can be exploited to significantly improve the performance of many devices such as memories, tunable radio-frequency/microwave devices, and magnetic sensors. In this article, we introduce a number of current or developing technologies and discuss their limitations. We describe how the use of magnetoelectric nanostructures can overcome these limitations to optimize device performance. We also present challenges that need to be addressed in pursuing practical applications of magnetoelectric devices.

Excitation of coherent high-frequency magnons (quanta of spin waves) is critical to the development of high-speed magnonic devices. Here we computationally demonstrate the excitation of coherent sub-terahertz (THz) magnons in ferromagnetic (FM) and antiferromagnetic (AFM) thin films by a photoinduced picosecond acoustic pulse. Analytical calculations are also performed to reveal the magnon excitation mechanism. Through spin pumping and spin-charge conversion, these magnons can inject sub-THz charge current into an adjacent heavy-metal film which in turn emits electromagnetic (EM) waves. Using a dynamical phase-field model that considers the coupled dynamics of acoustic waves, spin waves, and EM waves, we show that the emitted EM wave retains the spectral information of all the sub-THz magnon modes and has a sufficiently large amplitude for near-field detection. These predictions indicate that the excitation and detection of sub-THz magnons can be realized in rationally designed FM or AFM thin-film heterostructures via ultrafast optical-pump THz-emission-probe spectroscopy.

Thermochemical processes are considered as a promising technology for sewage sludge management, which could achieve volume reduction, energy and resource recovery, and effective destruction of pathogens. However, there are still many technology limitations and challenges of the thermochemical processes toward industrialization and commercialization. This review first briefly discusses the impact of sewage sludge on environmental sustainability and its current treatment and disposal methods. Typical thermochemical conversion technologies i.e., incineration/combustion, pyrolysis, gasification, and hydrothermal liquefaction for energy and resource recovery from sewage sludge are then comprehensively summarized. Subsequently, the technical challenges of thermochemical conversion of sewage sludge and the solutions that have been and/or are being developed to address the challenges are in-depth analyzed. Meanwhile, the prospects and future directions of the thermochemical technologies are outlined. In addition, the economic analysis and life cycle assessment of thermochemical conversion technologies are evaluated. Finally, the conclusions are put forward.