arXiv subjects

Alejandro Schulman

Publications and source records attributed to Alejandro Schulman.

8 recordsLinked to original sources

arXiv2026

Exploring Multifunctionality in MgO-Based Magnetic Tunnel Junctions with Coexisting Magnetoresistance and Memristive Properties

Magnetic tunnel junctions (MTJs) and memristors are two key emerging nanotechnologies that attracted significant interest for potential applications at the forefront of the digital revolution, including sensing, data storage, and non-conventional computation. The co-integration of these phenomena into a single multifunctional device is an important step toward harnessing the re-programmability of memristive systems with the high yield and varied functionality of MTJs. This study demonstrates the co-existence of magnetoresistance and memristive properties on MgO-based MTJs. These devices show a magnetoresistance with a linear response as a function of a magnetic field and no hysteresis, which are the requirements for good magnetic field sensors, as well as demonstrating a non-volatile and quasi-analogue memristive behavior as a function of an applied electrical field down to nanosecond pulses. Furthermore, by doping the oxide barrier, the memristive power consumption is lowered by 20% giving the multi-functionality of the devices a promising scalability potential. This study also shows that, memristive switching can be reversibly used to completely suppress and recover the spintronic functionalities. These results can pave the way for a seamless co-integration of memristors and spintronic devices in complex reprogrammable circuits addressing applications such as reprogrammable multifunctional field sensor arrays and neuromorphic computing.

cond-mat.mtrl-sci↗

arXiv2023

The impact of local pinning sites in magnetic tunnel junctions with non-homogeneous free layers

Pinning at local defects is a significant road block for the successful implementation of technological paradigms which rely on the dynamic properties of non-trivial magnetic textures. In this report a comprehensive study of the influence of local pinning sites for non-homogeneous magnetic layers integrated as the free layer of a magnetic tunnel junction is presented, both experimentally and with corresponding micromagnetic simulations. The pinning sites are found to be extremely detrimental to the frequency controllability of the devices, a key requirement for their use as synapses in a frequency multiplexed artificial neural networks. In addition to describing the impact of the local pinning sites in the more conventional NiFe, a vortex-based magnetic tunnel junction with an amorphous free layer is presented which shows significantly improved frequency selectivity, marking a clear direction for the design of future low power devices.

cond-mat.mes-hall↗

arXiv2023

Enhancing Spin Transfer Torque in Magnetic Tunnel Junction Devices: Exploring the Influence of Capping Layer Materials and Thickness on Device Characteristics

We have developed and optimized two categories of spin transfer torque magnetic tunnel junctions (STT-MTJs) that exhibit a high tunnel magnetoresistance (TMR) ratio, low critical current, high outputpower in the micro watt range, and auto-oscillation behavior. These characteristics demonstrate the potential of STT-MTJs for low-power, high-speed, and reliable spintronic applications, including magnetic memory, logic, and signal processing. The only distinguishing factor between the two categories, denoted as A-MTJs and B-MTJs, is the composition of their free layers, 2 CoFeB/0.21 Ta/6 CoFeSiB for A-MTJs and 2 CoFeB/0.21 Ta/7 NiFe for B-MTJs. Our study reveals that B-MTJs exhibit lower critical currents for auto-oscillation than A-MTJs. We found that both stacks have comparable saturation magnetization and anisotropy field, suggesting that the difference in auto-oscillation behavior is due to the higher damping of A-MTJs compared to B-MTJs. To verify this hypothesis, we employed the all-optical time-resolved magneto-optical Kerr effect (TRMOKE) technique, which confirmed that STT-MTJs with lower damping exhibited auto-oscillation at lower critical current values. Additionally, our study aimed to optimize the STT-MTJ performance by investigating the impact of the capping layer on the device's response to electronic and optical stimuli.

physics.optics↗

arXiv2022

Multilayer spintronic neural networks with radio-frequency connections

Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These dynamical nanodevices could transform artificial intelligence hardware, provided that they implement state-of-the art deep neural networks. However, there is today no scalable way to connect them in multilayers. Here we show that the flagship nano-components of spintronics, magnetic tunnel junctions, can be connected into multilayer neural networks where they implement both synapses and neurons thanks to their magnetization dynamics, and communicate by processing, transmitting and receiving radio frequency (RF) signals. We build a hardware spintronic neural network composed of nine magnetic tunnel junctions connected in two layers, and show that it natively classifies nonlinearly-separable RF inputs with an accuracy of 97.7%. Using physical simulations, we demonstrate that a large network of nanoscale junctions can achieve state-of the-art identification of drones from their RF transmissions, without digitization, and consuming only a few milliwatts, which is a gain of more than four orders of magnitude in power consumption compared to currently used techniques. This study lays the foundation for deep, dynamical, spintronic neural networks.

cs.ET↗

arXiv2022

Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses

Extracting information from radiofrequency (RF) signals using artificial neural networks at low energy cost is a critical need for a wide range of applications from radars to health. These RF inputs are composed of multiples frequencies. Here we show that magnetic tunnel junctions can process analogue RF inputs with multiple frequencies in parallel and perform synaptic operations. Using a backpropagation-free method called extreme learning, we classify noisy images encoded by RF signals, using experimental data from magnetic tunnel junctions functioning as both synapses and neurons. We achieve the same accuracy as an equivalent software neural network. These results are a key step for embedded radiofrequency artificial intelligence.

cond-mat.mes-hall↗

arXiv2017

Sign-changing non-monotonic voltage gain of HfO2/Parylene-C/SrTiO3 field-effect transistor due to percolative insulator to two-dimensional metal transition

Controlling the insulator-to-2D-metal transition is a promising key to overcome the scaling problem that silicon-based electronic devices will face in the near future. In this context, we examine the channel formation of SrTiO3-based solid-gated field-effect devices in which a 2D metal phase coexists with a semiconductor phase. A non-monotonic voltage-gain transfer characteristic with negative and positive slope regions is observed. We introduce a numerical model that helps to rationalize the experimental findings in terms of the established physics of field-effect transistors and percolation. Our numerical study not only reproduces the experimental results but also provides non-trivial predictions, which we verify experimentally.

cond-mat.str-el↗

arXiv2015

Poole-Frenkel effect and Variable-Range Hopping conduction in metal / YBCO resistive switching devices

Current-voltage (IV) characteristics and the temperature dependence of the contact resistance [$R(T)$] of Au / YBa$_2$Cu$_3$O$_{7-δ}$ (optimally doped YBCO) interfaces have been studied at different resistance states. This states were produced by resistive switching after accumulating cyclic electrical pulses of increasing number and voltage amplitude. The IV characteristics and the $R(T)$ dependence of the different states are consistent with a Poole-Frenkel (P-F) emission mechanism with trapping-energy levels $E_t$ in the 0.06-0.11 eV range. $E_t$ remains constant up to a number-of-pulses-dependent critical voltage and increases linearly with further increasing the voltage amplitude of the pulses. The observation of a P-F mechanism reveals the existence of an oxygen-depleted layer of YBCO near the interface. A simple electrical transport scenario is discussed, where the degree of disorder, the trap energy level and the temperature range determine an electrical conduction dominated by non-linear effects, or by a P-F emission or by a Variable-Range Hopping regime.

cond-mat.supr-con↗

arXiv2013

Cyclic electric field stress on bipolar resistive switching devices

We have studied the effects of accumulating cyclic electrical pulses of increasing amplitude on the non-volatile resistance state of interfaces made by sputtering a metal (Au, Pt) on top of the surface of a cuprate superconductor YBa$_2$Cu$_3$O$_{7-δ}$ (YBCO). We have analyzed the influence of the number of applied pulses $N$ on the relative amplitude of the remnant resistance change between the high ($R_H$) and the low ($R_L$) state [$α=(R_{H}-R_{L})/R_{L}$] at different temperatures ($T$). We show that the critical voltage ($V_c$) needed to produce a resistive switching (RS, i.e. $α>0$) decreases with increasing $N$ or $T$. We also find a power law relation between the voltage of the pulses and the number of pulses $N_{α_0}$ required to produce a RS of $α=α_0$. This relation remains very similar to the Basquin equation used to describe the stress-fatigue lifetime curves in mechanical tests. This points out to the similarity between the physics of the RS, associated with the diffusion of oxygen vacancies induced by electrical pulses, and the propagation of defects in materials subjected to repeated mechanical stress.

cond-mat.mtrl-sci↗