Granular Magnetization Switching in Pt/Co/Ti Structure with HfOx Insertion for In-Memory Computing Applications.

Exploring multiple states based on the domain wall (DW) position has garnered increased attention for in-memory computing applications, particularly focusing on the utilization of spin-orbit torque (SOT) to drive DW motion. However, devices relying on the DW position require efficient DW pinning. Here, we achieve granular magnetization switching by incorporating an HfOx insertion layer between the Co/Ti interface. This corresponds to a transition in the switching model from the DW motion to DW nucleation. Compared to the conventional Pt/Co/Ti structure, incorporation of the HfOx layer results in an enhanced SOT efficiency and a lower switching current density. We also realized stable multistate storage and synaptic plasticity by applying pulse current in the Pt/Co/HfOx/Ti device. The simulation of artificial neural networks (ANN) based on the device can perform digital recognition tasks with an accuracy rate of 91%. These results identify that DW nucleation with a Pt/Co/HfOx/Ti based device has potential applications in multistate storage and ANN.

Electric field control of spin-orbit torque in annealed Ta/CoFeB/HfOxheterostructures via interfacial oxidation modulation.

Electric field control of spin-orbit torque (SOT) exhibits promising potential in advanced spintronic devices through interfacial modulation. In this work, we investigate the influence of electric field and interfacial oxidation on SOT efficiency in annealed Ta/CoFeB/HfOxheterostructures. By varying annealing temperatures, the damping-like SOT efficiency reaches its peak at the annealing temperature of 320 °C, with an 80% field-free magnetization switching ratio induced by SOT having been demonstrated. This enhancement is ascribed to the annealing-induced modulation of oxygen ion migration at the CoFeB/HfOxinterface. By applying voltages across the Ta/CoFeB/HfOxheterostructures, which drives the O2‒migration across the interface, a reversible, bipolar, and non-volatile modulation of SOT efficiency was observed. The collective influence of annealing temperature and electric field effects on SOT carried out in this work provides an effective approach into facilitating the optimization and control of SOT in spintronic devices.

The impact of oxygen vacancy defect density on the nonlinearity and short-term plasticity of TiO2-based exponential selector.

The readout margin of the one selector-one RRAM crossbar array architecture is strongly dependent on the nonlinearity of the selector device. In this work, we demonstrated that the nonlinearity of Pt/TiO2/Pt exponential selectors increases with decreasing oxygen vacancy defect density. The defect density is controlled by modulating the sputtering pressure in the oxide deposition process. Our results reveal that the dominant conduction mechanisms of the Pt/TiO2/Pt structure transit from Schottky emission to Poole-Frenkel emission with the increase of sputtering pressure. Such transition is attributed to the rise of oxygen vacancy concentration. In addition, the short-term plasticity feature of the Pt/TiO2/Pt selector is shown to be enhanced with a lower defect density. These results suggest that low defect density is necessary for improved exponential selector performances.

Enhancement of temperature-modulated NbO2-based relaxation oscillator via interfacial and bulk treatments.

This work demonstrates oscillation frequency modulation in a NbO2-based relaxation oscillator device, in which the oscillation frequency increases with operating temperature and source voltage, and decreases with load resistance. An annealing-induced oxygen diffusion at 373 K was carried out to optimize the stoichiometry of the bulk NbO2to achieve consistent oscillation frequency shift with device temperature. The device exhibits stable self-sustained oscillation in which the frequency can be modulated between 2 and 33 MHz, and a wider operating voltage range can be obtained. An additional surface treatment step was employed during fabrication to reduce the surface roughness of the bottom electrode and to remove surface contaminants that affect the interfacial properties of the device. The device frequency tunability coupled with high oscillating frequency and high endurance capability of more than 1.5 × 108cycles indicates that the Pt/NbO2/Pt device is particularly suitable for applications in an oscillatory neural network.

Operando Direct Observation of Filament Formation in Resistive Switching Devices Enabled by a Topological Transformation Molecule.

Conductive filaments (CFs) play a critical role in the mechanism of resistive random-access memory (ReRAM) devices. However, in situ detection and visualization of the precise location of CFs are still key challenges. We demonstrate for the first time the use of a π-conjugated molecule which can transform between its twisted and planar states upon localized Joule heating generated within filament regions, thus reflecting the locations of the underlying CFs. Customized patterns of CFs were induced and observed by the π-conjugated molecule layer, which confirmed the hypothesis. Additionally, statistical studies on filaments distribution were conducted to study the effect of device sizes and bottom electrode heights, which serves to enhance the understanding of switching behavior and their variability at device level. Therefore, this approach has great potential in aiding the development of ReRAM technology.

Antiferromagnetic skyrmion repulsion based artificial neuron device.

Magnetic skyrmions are potential candidates for neuromorphic computing due to their inherent topologically stable particle-like behavior, low driving current density, and nanoscale size. Antiferromagnetic skyrmions are favored as they can be driven parallel to in-plane electrical currents as opposed to ferromagnetic skyrmions which exhibit the skyrmion Hall effect and eventually cause their annihilation at the edge of nanotracks. In this paper, an antiferromagnetic skyrmion based artificial neuron device consisting of a magnetic anisotropy barrier on a nanotrack is proposed. It exploits inter-skyrmion repulsion, mimicking the integrate-fire (IF) functionality of a biological neuron. The device threshold represented by the maximum number of skyrmions that can be pinned by the barrier can be tuned based on the particular current density employed on the nanotrack. The corresponding neuron spiking event occurs when a skyrmion overcomes the barrier. By raising the device threshold, lowering the barrier width and height, the operating current density of the device can be decreased to further enhance its energy efficiency. The proposed device paves the way for developing energy-efficient neuromorphic computing in antiferromagnetic spintronics.

A depth dose study between AAA and AXB algorithm against Monte Carlo simulation using AIP CT of a 4D dataset from a moving phantom.

AIM: To identifying depth dose differences between the two versions of the algorithms using AIP CT of a 4D dataset. BACKGROUND: Motion due to respiration may challenge dose prediction of dose calculation algorithms during treatment planning. MATERIALS AND METHODS: The two versions of depth dose calculation algorithms, namely, Anisotropic Analytical Algorithm (AAA) version 10.0 (AAAv10.0), AAA version 13.6 (AAAv13.6) and Acuros XB dose calculation (AXB) algorithm version 10.0 (AXBv10.0), AXB version 13.6 (AXBv13.6), were compared against a full MC simulated 6X photon beam using QUASAR respiratory motion phantom with a moving chest wall. To simulate the moving chest wall, a 4 cm thick wax mould was attached to the lung insert of the phantom. Depth doses along the central axis were compared in the anterior and lateral beam direction for field sizes 2 × 2 cm2, 4 × 4 cm2 and 10 × 10 cm2. RESULTS: For the lateral beam direction, the moving chest wall highlighted differences of up to 105% for AAAv10.0 and 40% for AXBv10.0 from MC calculations in the surface and buildup doses. AAAv13.6 and AXBv13.6 agrees with MC predictions to within 10% at similar depth. For anterior beam doses, dose differences predicted for both versions of AAA and AXB algorithm were within 7% and results were consistent with static heterogeneous studies. CONCLUSIONS: The presence of the moving chest wall was capable of identifying depth dose differences between the two versions of the algorithms. These differences could not be identified in the static chest wall as shown in the anterior beam depth dose calculations.

Spin-based magnetic random-access memory for high-performance computing.

Spin-based memory technology is now available as embedded magnetic random access memory (eMRAM) for fast, high-density and non-volatile memory products, which can significantly boost computing performance and ignite the development of new computing architectures.

Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices.

Neuromorphic platforms are gaining popularity due to their superior efficiency, low power consumption, and adaptable parallel signal processing capabilities, overcoming the limitations of traditional von Neumann architecture. We conduct an in-depth investigation into the factors influencing the resistive switching mechanism in memristor devices utilizing lead iodide (PbI2). We establish correlations between device performance and morphological features, unveiling synaptic like behaviour of device making it suitable for range of flexible neuromorphic applications. Notably, a highly reliable unipolar switching mechanism is identified, exhibiting stability even under mechanical strain (with a bending radius of approximately 4 mm) and in high humidity environment (at 75% relative humidity) without the need for encapsulation. The investigation delves into the complex interplay of charge transport, ion migration and the active interface, elucidating the factors contributing to the remarkable resistive switching observed in PbI2-based memristors. The detailed findings highlight synaptic behaviors akin to the modulation of synaptic strengths, with an impressive potentiation and depression of 2 × 104 cycles, emphasizing the role of spike time-dependent plasticity (STDP). The flexible platform demonstrates exceptional performance, achieving a simulated accuracy rate of 95.06% in recognizing modified patterns from the National Institute of Standards and Technology (MNIST) dataset with just 30 training epochs. Ultimately, this research underscores the potential of PbI2-based flexible memristor devices as versatile component for neuromorphic computing. Moreover, it demonstrate the robustness of PbI2 memristors in terms of their resistive switching capabilities, showcasing resilience both mechanically and electrically. This underscores their potential in replicating synaptic functions for advanced information processing systems.

Control-Etched Ti3C2Tx MXene Nanosheets for a Low-Voltage-Operating Flexible Memristor for Efficient Neuromorphic Computation.

Hardware neural networks with mechanical flexibility are promising next-generation computing systems for smart wearable electronics. Overcoming the challenge of developing a fully synaptic plastic network, we demonstrate a low-operating-voltage PET/ITO/p-MXene/Ag flexible memristor device by controlling the etching of aluminum metal ions in Ti3C2Tx MXene. The presence of a small fraction of Al ions in partially etched MXene (p-Ti3C2Tx) significantly suppresses the operating voltage to 1 V compared to 7 V from fully Al etched MXene (f-Ti3C2Tx)-based devices. Former devices exhibit excellent non-volatile data storage properties, with a robust ∼103 ON/OFF ratio, high endurance of ∼104 cycles, multilevel resistance states, and long data retention measured up to ∼106 s. High mechanical stability up to ∼73° bending angle and environmental robustness are confirmed with consistent switching characteristics under increasing temperature and humid conditions. Furthermore, a p-Ti3C2Tx MXene memristor is employed to mimic the biological synapse by measuring the learning-forgetting pattern for ∼104 cycles as potentiation and depression. Spike time-dependent plasticity (STDP) based on Hebb's Learning rules is also successfully demonstrated. Moreover, a remarkable accuracy of ∼95% in recognizing modified patterns from the National Institute of Standards and Technology (MNIST) data set with just 29 training epochs is achieved in simulation. Ultimately, our findings underscore the potential of MXene-based flexible memristor devices as versatile components for data storage and neuromorphic computing.

NIR and magnetism dual-response multi-core magnetic vortex nanoflowers for boosting magneto-photothermal cancer therapy.

Due to the relatively low efficiency of magnetic hyperthermia and photothermal conversion, it is rather challenging for magneto-photothermal nanoagents to be used as an effective treatment during tumor hyperthermal therapy. The advancement of magnetic nanoparticles exhibiting a vortex-domain structure holds great promise as a viable strategy to enhance the application performance of conventional magnetic nanoparticles while retaining their inherent biocompatibility. Here, we report the development of Mn0.5Zn0.5Fe2O4 nanoflowers with ellipsoidal magnetic cores, and show them as effective nanoagents for magneto-photothermal synergistic therapy. Comparative studies were conducted on the heating performance of anisometric Mn0.5Zn0.5Fe2O4 (MZF) nanoparticles, including nanocubes (MZF-C), hollow spheres (MZF-HS), nanoflowers consisting of ellipsoidal magnetic cores (MZF-NFE), and nanoflowers consisting of needle-like magnetic cores (MZF-NFN). MZF-NFE exhibits an intrinsic loss parameter (ILP) of up to 15.3 N h m2 kg-1, which is better than that of commercial equivalents. Micromagnetic simulations reveal the magnetization configurations and reversal characteristics of the various MZF shapes. Additionally, all nanostructures displayed a considerable photothermal conversion efficiency rate of more than 18%. Our results demonstrated that by combining the dual exposure of MHT and PTT for hyperthermia treatments induced by MZF-NFE, BT549, MCF-7, and 4T1 cell viability can be significantly decreased by ∼95.7% in vitro.

Unraveling the origins of the coexisting localized-interfacial mechanism in oxide-based memristors in CMOS-integrated synaptic device implementations.

The forefront of neuromorphic research strives to develop devices with specific properties, i.e., linear and symmetrical conductance changes under external stimuli. This is paramount for neural network accuracy when emulating a biological synapse. A parallel exploration of resistive memory as a replacement for conventional computing memory ensues. In search of a holistic solution, the proposed memristive device in this work is uniquely poised to address this elusive gap as a unified memory solution. Opposite biasing operations are leveraged to achieve stable abrupt and gradual switching characteristics within a single device, addressing the demands for lower latency and energy consumption for binary switching applications, and graduality for neuromorphic computing applications. We evaluated the underlying principles of both switching modes, attributing the anomalous gradual switching to the modulation of oxygen-deficient layers formed between the active electrode and oxide switching layer. The memristive cell (1R) was integrated with 40 nm transistor technology (1T) to form a 1T-1R memory cell, demonstrating a switching speed of 50 ns with a pulse amplitude of ±2.5 V in its forward-biased mode. Applying pulse trains of 20 ns to 490 ns in the reverse-biased mode exhibited synaptic weight properties, obtaining a nonlinearity (NL) factor of <0.5 for both potentiation and depression. The devices in both modes also demonstrated an endurance of >106 cycles, and their conductance states were also stable under temperature stress at 85 °C for 104 s. With the duality of the two switching modes, our device can be used for both memory and synaptic weight-storing applications.

Effects of modern aesthetic dental fillings on proton therapy.

Background and purpose: High-density dental fillings pose a non-negligible impact on head and neck cancer treatment. For proton therapy, stopping power ratio (SPR) prediction will be significantly impaired by the associated image artifacts. Dose perturbation is also inevitable, compromising the treatment plan quality. While plenty of work has been done on metal or amalgam fillings, none has touched on composite resin (CR) and glass ionomer cement (GIC) which have seen an increasing usage. Hence, this work aims to provide a detailed characterisation of SPR and dose perturbation in proton therapy caused by CR and GIC. Materials and methods: Four types of fillings were used: CR, Fuji Bulk (FB), Fuji II (FII) and Fuji IX (FIX). The latter three belong to GIC category. Measured SPR were compared with SPR predicted using single-energy computed tomography (SECT) and dual-energy computed tomography (DECT). Dose perturbation of proton beams with lower- and higher-energy levels was also quantified using Gafchromic films. Results: The measured SPR for CR, FB, FII and FIX were 1.68, 1.77, 1.77 and 1.76, respectively. Overall, DECT could predict SPR better than SECT. The lowest percentage error achieved by DECT was 19.7 %, demonstrating the challenge in estimating SPR, even for fillings with relatively lower densities. For both proton beam energies and all four fillings of about 4.5 mm thickness, the maximum dose perturbation was 3 %. Conclusion: This study showed that dose perturbation by CR and GIC was comparatively small. We have measured and recommended the SPR values for overriding the fillings in TPS.

High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing.

Despite impressive demonstrations of memristive behavior with halide perovskites, no clear pathway for material and device design exists for their applications in neuromorphic computing. Present approaches are limited to single element structures, fall behind in terms of switching reliability and scalability, and fail to map out the analog programming window of such devices. Here, we systematically design and evaluate robust pyridinium-templated one-dimensional halide perovskites as crossbar memristive materials for artificial neural networks. We compare two halide perovskite 1D inorganic lattices, namely (propyl)pyridinium and (benzyl)pyridinium lead iodide. The absence of conjugated, electron-rich substituents in PrPyr+ prevents edge-to-face type π-stacking, leading to enhanced electronic isolation of the 1D iodoplumbate chains in (PrPyr)[PbI3], and hence, superior resistive switching performance compared to (BnzPyr)[PbI3]. We report outstanding resistive switching behaviours in (PrPyr)[PbI3] on the largest flexible crossbar implementation (16 × 16) to date - on/off ratio (>105), long term retention (105 s) and high endurance (2000 cycles). Finally, we put forth a universal approach to comprehensively map the analog programming window of halide perovskite memristive devices - a critical prerequisite for weighted synaptic connections in artificial neural networks. This consequently facilitates the demonstration of accurate handwritten digit recognition from the MNIST database based on spike-timing-dependent plasticity of halide perovskite memristive synapses.

Deformable anthropomorphic pelvis phantom for dose accumulation verification.

Objective.The validation of deformable image registration (DIR) for contour propagation is often done using contour-based metrics. Meanwhile, dose accumulation requires evaluation of voxel mapping accuracy, which might not be accurately represented by contour-based metrics. By fabricating a deformable anthropomorphic pelvis phantom, we aim to (1) quantify the voxel mapping accuracy for various deformation scenarios, in high- and low-contrast regions, and (2) identify any correlation between dice similarity coefficient (DSC), a commonly used contour-based metric, and the voxel mapping accuracy for each organ.Approach. Four organs, i.e. pelvic bone, prostate, bladder and rectum (PBR), were 3D printed using PLA and a Polyjet digital material, and assembled. The latter three were implanted with glass bead and CT markers within or on their surfaces. Four deformation scenarios were simulated by varying the bladder and rectum volumes. For each scenario, nine DIRs with different parameters were performed on RayStation v10B. The voxel mapping accuracy was quantified by finding the discrepancy between true and mapped marker positions, termed the target registration error (TRE). Pearson correlation test was done between the DSC and mean TRE for each organ.Main results. For the first time, we fabricated a deformable phantom purely from 3D printing, which successfully reproduced realistic anatomical deformations. Overall, the voxel mapping accuracy dropped with increasing deformation magnitude, but improved when more organs were used to guide the DIR or limit the registration region. DSC was found to be a good indicator of voxel mapping accuracy for prostate and rectum, but a comparatively poorer one for bladder. DSC > 0.85/0.90 was established as the threshold of mean TRE ⩽ 0.3 cm for rectum/prostate. For bladder, extra metrics in addition to DSC should be considered.Significance. This work presented a 3D printed phantom, which enabled quantification of voxel mapping accuracy and evaluation of correlation between DSC and voxel mapping accuracy.

Strain-induced degradation and recovery of flexible NbOx-based threshold switching device.

We investigate the functionality of NbOx-based selector devices on a flexible substrate. It was observed that the failure mechanism of cyclic tensile strain is from the disruption of atom arrangements, which essentially led to the crack formation of the film. When under cyclic compressive strain, buckling delamination of the film occurs as the compressed films have debonded from their neighboring layers. By implementing an annealing process after the strain-induced degradation, recovery of the device is observed with reduced threshold and hold voltages. The physical mechanism of the device is investigated through Poole-Frenkel mechanism fitting, which provides insights into the switching behavior after mechanical strain and annealing process. The result demonstrates the potential of the NbOx device in flexible electronics applications with a high endurance of up to 105 cycles of cyclic bending strain and the recovery of the device after degradation.

Proton-Assisted Redox-Based Three-Terminal Memristor for Synaptic Device Applications.

Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it can concurrently execute signal transmission and memory operations. In this work, we present a complementary metal-oxide-semiconductor-compatible 3TM with highly linear weight update characteristics and a dynamic range of ∼15. The switching mechanism is governed by the migration of oxygen ions and protons in and out of the channel under an external gate electric field. The involvement of the protonic defects in the electrochemical reactions is proposed based on the bipolar pulse trains required to initiate the oxidation process and the device electrical characteristics under different humidity levels. For the synaptic operation, an excellent endurance performance with over 256k synaptic weight updates was demonstrated while maintaining a stable dynamic range. Additionally, the synaptic performance of the 3TM is simulated and implemented into a four-layer neural network (NN) model, achieving an accuracy of ∼92% in MNIST handwritten digit recognition. With such desirable conductance modulation characteristics, our proposed 3T-memristor is a promising synaptic device candidate to realize the hardware implementation of the artificial NN.

Hollow spherical Mn0.5Zn0.5Fe2O4 nanoparticles with a magnetic vortex configuration for enhanced magnetic hyperthermia efficacy.

Conventional magnetic nanoagents in cancer hyperthermia therapy suffer from a low magnetic heating efficiency. To address this issue, researchers have pursued magnetic nanoparticles with topological magnetic domain structures, such as the vortex-domain structure, to enhance the magnetic heating performance of conventional nanoparticles while maintaining excellent biocompatibility. In this study, we synthesized hollow spherical Mn0.5Zn0.5Fe2O4 (MZF-HS) nanoparticles using a straightforward solvothermal method, yielding samples with an average outer diameter of approximately 350 nm and an average inner diameter of about 220 nm. The heating efficiency of the nanoparticles was experimentally verified, and the specific absorption rate (SAR) value of the hollow MZF was found to be approximately 1.5 times that of solid MZF. The enhanced heating performance is attributed to the vortex states in the hollow MZF structure as validated with micromagnetic simulation studies. In vitro studies demonstrated the lower cell viability of breast cancer cells (MCF-7, BT549, and 4T1) after MHT in the presence of MZF-HS. The synthesized MZF caused 51% cell death after MHT, while samples of MZF-HS resulted in 77% cell death. Our findings reveal that magnetic particles with a vortex state demonstrate superior heating efficiency, highlighting the potential of hollow spherical particles as effective heat generators for MHT applications.

Switching the memory behaviour from binary to ternary by triggering S62- relaxation in polysulfide-bearing zinc-organic complex molecular memories.

The use of crystalline metal-organic complexes with definite structures as multilevel memories can enable explicit structure-property correlations, which is significant for designing the next generation of memories. Here, four Zn-polysulfide complexes with different degrees of conjugation have been fabricated as memory devices. ZnS6(L)2-based memories (L = pyridine and 3-methylpyridine) can exhibit only bipolar binary memory performances, but ZnS6(L)-based memories (L = 2,2'-bipyridine and 1,10-phenanthroline) illustrate non-volatile ternary memory performances with high ON2/ON1/OFF ratios (104.22/102.27/1 and 104.85/102.58/1) and ternary yields (74% and 78%). Their ON1 states stem from the packing adjustments of organic ligands upon the injection of carriers, and the ON2 states are a result of the ring-to-chain relaxation of S62- anions. The lower conjugated degrees in ZnS6(L)2 result in less compact packing; consequently, the adjacent S62- rings are too long to trigger the S62- relaxation. The deep structure-property correlation in this work provides a new strategy for implementing multilevel memory by triggering polysulfide relaxation based on the conjugated degree regulation of organic ligands.

A bi-functional three-terminal memristor applicable as an artificial synapse and neuron.

Due to their significant resemblance to the biological brain, spiking neural networks (SNNs) show promise in handling spatiotemporal information with high time and energy efficiency. Two-terminal memristors have the capability to achieve both synaptic and neuronal functions; however, such memristors face asynchronous programming/reading operation issues. Here, a three-terminal memristor (3TM) based on oxygen ion migration is developed to function as both a synapse and a neuron. We demonstrate short-term plasticity such as pair-pulse facilitation and high-pass dynamic filtering in our devices. Additionally, a 'learning-forgetting-relearning' behavior is successfully mimicked, with lower power required for the relearning process than the first learning. Furthermore, by leveraging the short-term dynamics, the leaky-integrate-and-fire neuronal model is emulated by the 3TM without adopting an external capacitor to obtain the leakage property. The proposed bi-functional 3TM offers more process compatibility for integrating synaptic and neuronal components in the hardware implementation of an SNN.