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Neuromorphic computing (NC) is a promising candidate for artificial intelligence applications. To realize NC, electronic analogues of brain components, such as synapses and neurons, must be designed. In spintronics, domain wall (DW) based magnetic tunnel junctions - which offer both synaptic and neuronal functionalities - are one of the promising candidates. An electronic neuron should exhibit leaky-integrate-fire functions similar to their biological counterparts. However, most experimental studies focused only on the integrate-and-fire functions, overlooking the leaky function. Here, we report on a domain wall neuron device that achieves integration using spin-orbit torque-induced domain wall motion and a leaky function via synthetic antiferromagnetic coupling. By fabricating Hall bar devices in a special geometry, we could achieve these two functionalities. During the leaky process, the maximum DW velocity achieved was 2500 {\mu}m/s. The proposed design utilizes materials used in STT-MRAM fabrication and is compatible with CMOS fabrication. Therefore, this neuron can be readily integrated into NC., Comment: 15 pages, 4 Figures, 1 Table

In alignment with the increasing demand for larger storage capacity and longer data retention, electrical control of magnetic anisotropy has been a research focus in the realm of spintronics. Typically, magnetic anisotropy is determined by grain dimensionality, which is set during the fabrication of magnetic thin films. Despite the intrinsic correlation between magnetic anisotropy and grain dimensionality, there is a lack of experimental evidence for electrically controlling grain dimensionality, thereby impeding the efficiency of magnetic anisotropy modulation. Here, we demonstrate an electric field control of grain dimensionality and prove it as the active mechanism for tuning interfacial magnetism. The reduction in grain dimensionality is associated with a transition from ferromagnetic to superparamagnetic behavior. We achieve a non-volatile and reversible modulation of the coercivity in both the ferromagnetic and superparamagnetic regimes. Subsequent electrical and elemental analysis confirms the variation in grain dimensionality upon the application of gate voltages, revealing a transition from a multidomain to a single-domain state accompanied by a reduction in grain dimensionality. Furthermore, we exploit the influence of grain dimensionality on domain wall motion, extending its applicability to multilevel magnetic memory and synaptic devices. Our results provide a strategy for tuning interfacial magnetism through grain size engineering for advancements in high-performance spintronics.

Ambient magnetic skyrmions stabilized in multilayer nanostructures are of immense interest due to their relevance to magnetic tunnel junction (MTJ) devices for memory and unconventional computing applications. However, existing skyrmionic nanostructures built using conventional metallic or oxide multilayer nanodots are unable to concurrently fulfill the requirements of nanoscale skyrmion stability and feasibility of all-electrical readout and manipulation. Here, we develop a few-repeat hybrid multilayer platform consisting of metallic [Pt/CoB/Ir]3 and oxide [Pt/CoB/MgO] components that are coupled to evolve together as a single, composite stack. Zero-field (ZF) skyrmions with sizes as small as 50 nm are stabilized in the hybrid multilayer nanodots, which are smoothly modulated by up to 2.5x by varying CoB thickness and dot sizes. Meanwhile, skyrmion multiplets are also stabilized by small bias fields. Crucially, we observe higher order 'target' skyrmions with varying magnetization rotations in moderately-sized, low anisotropy nanodots. These results provide a viable route to realize long-sought skyrmionic MTJ devices and new possibilities for multi-state skyrmionic device concepts.

Controlling multiple skyrmions in nanowires is important for their implementation in racetrack memory or neuromorphic computing. Here, we report on the dynamical behavior of two interacting skyrmions in confined devices with a comparison to a single skyrmion case. Although the two skyrmions shrink near the edges and follow a helical path, their behavior is different. Because the leading skyrmion is between the edge and the trailing one, its size is reduced further and collapses at a lower current density compared to the single skyrmion case. For higher current density, both skyrmions are annihilated with a core-collapse mechanism for the leading one followed by a bubble-collapse mechanism for the trailing one.

Neuromorphic computing (NC) architecture has shown its suitability for energy-efficient computation. Amongst several systems, spin-orbit torque (SOT) based domain wall (DW) devices are one of the most energy-efficient contenders for NC. To realize spin-based NC architecture, the computing elements such as synthetic neurons and synapses need to be developed. However, there are very few experimental investigations on DW neurons and synapses. The present study demonstrates the energy-efficient operations of neurons and synapses by using novel reading and writing strategies. We have used a W/CoFeB-based energy-efficient SOT mechanism to drive the DWs at low current densities. We have used the concept of meander devices for achieving synaptic functions. By doing this, we have achieved 9 different resistive states in experiments. We have experimentally demonstrated the functional spike and step neurons. Additionally, we have engineered the anomalous Hall bars by incorporating several pairs, in comparison to conventional Hall crosses, to increase the sensitivity as well as signal-to-noise ratio (SNR). We performed micromagnetic simulations and transport measurements to demonstrate the above-mentioned functionalities.

Among various types of neuromorphic devices towards artificial intelligence, the electrochemical synaptic transistor emerges, in which the channel conductance is modulated by the insertion of ions according to the history of gate voltage across the electrolyte. Despite the striking progress in exploring novel channel materials, few studies report on the ferromagnetic metal-based synaptic transistors, limiting the development of spin-based neuromorphic devices. Here, we present synaptic modulation of both conductivity as well as magnetism based on an electrochemical transistor with a metallic channel of ferromagnetic CoPt alloy. We first demonstrate its essential synaptic functionalities in the transistor, including depression and potentiation of synaptic weight, and paired-pulse facilitation. Then, we show a short- to long-term plasticity transition induced by different gate parameters, such as amplitude, duration, and frequency. Furthermore, the device presents multilevel and reversible nonvolatile states in both conductivity and coercivity. The results demonstrate simultaneous modulation of conductivity and magnetism, paving the way for building future spin-based multifunctional synaptic devices.

Neuromorphic computing (NC) is considered as a potential vehicle for implementing energy-efficient artificial intelligence (AI). To realize NC, several materials systems are being investigated. Among them, the spin-orbit torque (SOT) -driven domain wall (DW) devices are one of the potential candidates. To implement these devices as neurons and synapses, the building blocks of NC, researchers have proposed different device designs. However, the experimental realization of DW device-based NC is only at the primeval stage. In this study, we have proposed and investigated pine-tree-shaped DW devices, based on the Laplace force on the elastic DWs, for achieving the synaptic functionalities. We have successfully observed multiple magnetization states when the DW was driven by the SOT current. The key observation is the asymmetric pinning strength of the device when DW moves in two opposite directions (defined as, xhard and xeasy). This shows the potential of these DW 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 leads to the path of device fabrication, where synaptic properties are achieved with asymmetric pinning potential.

Neuromorphic Computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation of artificial intelligence. Towards realizing NC, fabrication, and investigations of hardware elements such as synaptic devices and neurons are essential. Electrolyte gating has been widely used for conductance modulation by massive carrier injections and has proven to be an effective way of emulating biological synapses. Synaptic devices, in the form of synaptic transistors, have been studied using a wide variety of materials. However, studies on metallic channel based synaptic transistors remain vastly unexplored. Here, we have demonstrated a three-terminal cobalt-based synaptic transistor to emulate biological synapse. We realized gating controlled multilevel, nonvolatile conducting states in the proposed device. The device could successfully emulate essential synaptic functions demonstrating short-term and long-term plasticity. A transition from short-term memory to long-term memory has been realized by tuning gate pulse amplitude and duration. The crucial cognitive behavior viz., learning, forgetting, and relearning, has been emulated, showing resemblance to the human brain. Along with learning and memory, the device showed dynamic filtering behavior. These results provide an insight into the design of metallic channel based synaptic transistors for 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 domain wall (DW) devices. In comparison, DW-based neurons and synapses have potentially higher endurance. However, for realizing low-power devices, DW motion at low energies - typically below pJ/bit - are needed. Here, we demonstrate domain wall motion at current densities as low as 1E6 A/m2 by tailoring the beta-W spin Hall material. With our design, we achieve ultra-low pinning fields and current density reduction by a factor of 10000. The energy required to move the domain wall by a distance of about 20 micrometers is 0.4 fJ, which translates into energy consumption of 0.4 aJ/bit for a bit-length of 20 nm. With a meander domain wall device configuration, we have established a controlled DW motion for synapse applications and have shown the direction to make ultra-low energy spin-based neuromorphic elements., Comment: 17 pages, 4 figures

The growing demand for storage, due to big data applications, cannot be met by hard disk drives. Domain wall (DW) memory devices such as racetrack memory offer an alternative route to achieve high capacity storage. In DW memory, control of domain wall positions and their motion using spin-transfer torque are important challenges. In this paper, we demonstrate controlled domain wall motion using spin-transfer torque in staggered magnetic nanowires. The devices, fabricated using electron-beam lithography, were tested using a magneto-optical Kerr microscopy and electrical transport measurements. The depinning current, pinning potential and thermal stability were found to depend on the device dimensions of the staggering nanowires. Thus, the proposed staggering configuration helps to fine-tune the properties of domain wall devices for memory applications.

The Dzyaloshinskii Moriya Interaction (DMI) has laid the foundation for many novel chiral structures such as Skyrmions. In most of the studies so far, the DMI is present in the whole of the magnetic layer. Here, we report our investigations on a ferromagnetic nanowire where DMI is confined to a nanoscale region. We observe that the local modulation of magnetic properties causes oscillation of domain walls under the influence of spin-transfer torque. The oscillation frequency is tunable within a few GHz, making this observation potentially useful for applications in neuromorphic computing.

Magnetization dynamics driven by an electric field could provide long-term benefits to information technologies because of its ultralow power consumption. Meanwhile, the Dzyaloshinskii-Moriya interaction in interfacially asymmetric multilayers consisting of ferromagnetic and heavy-metal layers can stabilize topological spin textures, such as chiral domain walls, skyrmions, and skyrmion bubbles. These topological spin textures can be controlled by an electric field, and hold promise for building advanced spintronic devices. Here, we present an experimental and numerical study on the electric field-induced creation and directional motion of topological spin textures in magnetic multilayer films and racetracks with thickness gradient and interfacial Dzyaloshinskii-Moriya interaction at room temperature. We find that the electric field-induced directional motion of chiral domain wall is accompanied with the creation of skyrmion bubbles at certain conditions. We also demonstrate that the electric field variation can induce motion of skyrmion bubbles. Our findings may provide opportunities for developing skyrmion-based devices with ultralow power consumption., Comment: 26 pages, 6 figures