All-electrical skyrmionic magnetic tunnel junction.

Topological whirls or 'textures' of spins such as magnetic skyrmions represent the smallest realizable emergent magnetic entities1-5. They hold considerable promise as robust, nanometre-scale, mobile bits for sustainable computing6-8. A longstanding roadblock to unleashing their potential is the absence of a device enabling deterministic electrical readout of individual spin textures9,10. Here we present the wafer-scale realization of a nanoscale chiral magnetic tunnel junction (MTJ) hosting a single, ambient skyrmion. Using a suite of electrical and multimodal imaging techniques, we show that the MTJ nucleates skyrmions of fixed polarity, whose large readout signal-20-70% relative to uniformly magnetized states-corresponds directly to skyrmion size. The MTJ exploits complementary nucleation mechanisms to stabilize distinctly sized skyrmions at zero field, thereby realizing three non-volatile electrical states. Crucially, it can electrically write and delete skyrmions to both uniform states with switching energies 1,000 times lower than the state of the art. Here, the applied voltage emulates a magnetic field and, in contrast to conventional MTJs, it reshapes both the energetics and kinetics of the switching transition, enabling deterministic bidirectional switching. Our stack platform enables large readout and efficient switching, and is compatible with lateral manipulation of skyrmionic bits, providing the much-anticipated backbone for all-electrical skyrmionic device architectures9,10. Its wafer-scale realizability provides a springboard to harness chiral spin textures for multibit memory and unconventional computing8,11.

Magnetization dynamics and its scattering mechanism in thin CoFeB films with interfacial anisotropy.

Studies of magnetization dynamics have incessantly facilitated the discovery of fundamentally novel physical phenomena, making steady headway in the development of magnetic and spintronics devices. The dynamics can be induced and detected electrically, offering new functionalities in advanced electronics at the nanoscale. However, its scattering mechanism is still disputed. Understanding the mechanism in thin films is especially important, because most spintronics devices are made from stacks of multilayers with nanometer thickness. The stacks are known to possess interfacial magnetic anisotropy, a central property for applications, whose influence on the dynamics remains unknown. Here, we investigate the impact of interfacial anisotropy by adopting CoFeB/MgO as a model system. Through systematic and complementary measurements of ferromagnetic resonance (FMR) on a series of thin films, we identify narrower FMR linewidths at higher temperatures. We explicitly rule out the temperature dependence of intrinsic damping as a possible cause, and it is also not expected from existing extrinsic scattering mechanisms for ferromagnets. We ascribe this observation to motional narrowing, an old concept so far neglected in the analyses of FMR spectra. The effect is confirmed to originate from interfacial anisotropy, impacting the practical technology of spin-based nanodevices up to room temperature.

Multistate Compound Magnetic Tunnel Junction Synapses for Digital Recognition.

The quest to mimic the multistate synapses for bioinspired computing has triggered nascent research that leverages the well-established magnetic tunnel junction (MTJ) technology. Early works on the spin transfer torque MTJ-based artificial neural network (ANN) are susceptible to poor thermal reliability, high latency, and high critical current densities. Meanwhile, work on spin-orbit torque (SOT) MTJ-based ANN mainly utilized domain wall motion, which yields negligibly small readout signals differentiating consecutive states and has designs that are incompatible with technological scale-up. Here, we propose a multistate device concept built upon a compound MTJ consisting of multiple SOT-MTJs (number of MTJs, n = 1-4) on a shared write channel, mimicking the spin-based ANN. The n + 1 resistance states representing varying synaptic weights can be tuned by varying the voltage pulses (±1.5-1.8 V), pulse duration (100-300 ns), and applied in-plane fields (5.5-10.5 mT). A large TMR difference of more than 13.6% is observed between two consecutive states for the 4-cell compound MTJ, a 4-fold improvement from reported state-of-the-art spin-based synaptic devices. The ANN built upon the compound MTJ shows high learning accuracy for digital recognition tasks with incremental states and retraining, achieving test accuracy as high as 95.75% in the 4-cell compound MTJ. These results provide an industry-compatible platform to integrate these multistate SOT-MTJ synapses directly into neuromorphic architecture for in-memory and unconventional computing applications.

Bimodal alteration of cognitive accuracy for spintronic artificial neural networks.

Spintronics-based artificial neural networks (ANNs) exhibiting nonvolatile, fast, and energy-efficient computing capabilities are promising neuromorphic hardware for performing complex cognitive tasks of artificial intelligence and machine learning. Early experimental efforts focused on multistate device concepts to enhance synaptic weight precisions, albeit compromising on cognitive accuracy due to their low magnetoresistance. Here, we propose a hybrid approach based on the tuning of tunnel magnetoresistance (TMR) and the number of states in the compound magnetic tunnel junctions (MTJs) to improve the cognitive performance of an all-spin ANN. A TMR variation of 33-78% is controlled by the free layer (FL) thickness wedge (1.6-2.6 nm) across the wafer. Meanwhile, the number of resistance states in the compound MTJ is manipulated by varying the number of constituent MTJ cells (n = 1-3), generating n + 1 states with a TMR difference between consecutive states of at least 21%. Using MNIST handwritten digit and fashion object databases, the test accuracy of the compound MTJ ANN is observed to increase with the number of intermediate states for a fixed FL thickness or TMR. Meanwhile, the test accuracy for a 1-cell MTJ increases linearly by 8.3% and 7.4% for handwritten digits and fashion objects, respectively, with increasing TMR. Interestingly, a multifarious TMR dependence of test accuracy is observed with the increasing synaptic complexity in the 2- and 3-cell MTJs. By leveraging on the bimodal tuning of multilevel and TMR, we establish viable paths for enhancing the cognitive performance of spintronic ANN for in-memory and neuromorphic computing.

Ultralow Energy Domain Wall Device for Spin-Based Neuromorphic Computing.

Neuromorphic computing (NC) is gaining wide acceptance as a potential technology to achieve low-power intelligent devices. To realize NC, researchers investigate various types of synthetic neurons and synaptic devices, such as memristors and spintronic devices. In comparison, spintronics-based neurons and synapses have potentially higher endurance. However, for realizing low-power devices, domain wall (DW) devices that show DW motion at low energies─typically below pJ/bit─are favored. Here, we demonstrate DW motion at current densities as low as 106 A/m2 by engineering the ß-W spin-orbit coupling (SOC) material. With our design, we achieve ultralow pinning fields and current density reduction by a factor of 104. The energy required to move the DW by a distance of about 18.6 µm is 0.4 fJ, which translates into the energy consumption of 27 aJ/bit for a bit-length of 1 µm. With a meander DW device configuration, we have established a controlled DW motion for synapse applications and have shown the direction to make ultralow energy spin-based neuromorphic elements.

Diode Characteristics in Magnetic Domain Wall Devices via Geometrical Pinning for Neuromorphic Computing.

Neuromorphic computing (NC) is considered a potential vehicle for implementing energy-efficient artificial intelligence. To realize NC, several technologies are being investigated. Among them, the spin-orbit torque (SOT)-driven domain wall (DW) devices are one of the potential candidates. Researchers have proposed different device designs to achieve neurons and synapses, the building blocks of NC. However, the experimental realization of DW device-based NC is only at the primeval stage. Here, we have studied pine-tree DW devices, based on the Laplace pressure on the elastic DWs, for achieving synaptic functionalities and diode-like characteristics. We demonstrate an asymmetric pinning strength for DW motion in two opposite directions to show the potential of these devices as DW diodes. We have used micromagnetic simulations to understand the experimental findings and to estimate the Laplace pressure for various design parameters. The study provides a strategy to fabricate a multifunctional DW device, exhibiting synaptic properties and diode characteristics.

Chiral Interlayer Exchange Coupling for Asymmetric Domain Wall Propagation in Field-Free Magnetization Switching.

The discovery of chiral spin texture has unveiled many unusual yet extraordinary physical phenomena, such as the Néel type domain walls and magnetic skyrmions. A recent theoretical study suggests that a chiral exchange interaction is not limited to a single ferromagnetic layer; instead, three-dimensional spin textures can arise from an interlayer Dzyaloshinskii-Moriya interaction. However, the influence of chiral interlayer exchange coupling on the electrical manipulation of magnetization has rarely been addressed. Here, the coexistence of both symmetric and chiral interlayer exchange coupling between two orthogonally magnetized CoFeB layers in PtMn/CoFeB/W/CoFeB/MgO is demonstrated. Images from polar magneto-optical Kerr effect microscopy indicate that the two types of coupling act concurrently to induce asymmetric domain wall propagation, where the velocities of domain walls with opposite chiralities are substantially different. Based on this microscopic mechanism, field-free switching of the perpendicularly magnetized CoFeB is achieved with a wide range of W thicknesses of 0.6-4.5 nm. This work enriches the understanding of interlayer exchange coupling for spintronic applications.