arXiv subjects

Punyashloka Debashis

Publications and source records attributed to Punyashloka Debashis.

10 recordsLinked to original sources

arXiv2025

Material-Limited Switching in Nanoscale Ferroelectrics

The ferroelectric switching speed has been experimentally obfuscated by the interaction between the measurement circuit and the ferroelectric switching itself. This has prohibited the observation of real material responses at nanosecond timescales and lower. Here, fundamental polarization switching speeds in ferroelectric materials with the perovskite, fluorite, and wurtzite structures are reported. Upon lateral scaling of island capacitors from micron to nanoscales, a clear transition from circuit-limited switching to a material-limited switching regime is observed. In La$_{0.15}$Bi$_{0.85}$FeO$_{3}$ capacitors, switching is as fast as ~150 ps, the fastest switching time reported. For polycrystalline Hf$_{0.5}$Zr$_{0.5}$O$_{2}$ capacitors, a fundamental switching limit of ~210 ps is observed. Switching times for Al$_{0.92}$B$_{0.08}$N are near 20 ns, limited by the coercive and breakdown electric fields. The activation field, instantaneous pseudo-resistivity, and energy-delay are reported in this material-limited regime. Lastly, a criterion for reaching the material-limited regime is provided. This regime enables observation of intrinsic material properties and favorable scaling trends for high-performance computing.

cond-mat.mtrl-sci↗

arXiv2024

Voltage-based magnetization switching and reading in magnetoelectric spin-orbit nanodevices

As CMOS technologies face challenges in dimensional and voltage scaling, the demand for novel logic devices has never been greater, with spin-based devices offering scaling potential, at the cost of significantly high switching energies. Alternatively, magnetoelectric materials are predicted to enable low-power magnetization control, a solution with limited device-level results. Here, we demonstrate voltage-based magnetization switching and reading in nanodevices at room temperature, enabled by exchange coupling between multiferroic BiFeO$_3$ and ferromagnetic CoFe, for writing, and spin-to-charge current conversion between CoFe and Pt, for reading. We show that upon the electrical switching of the BiFeO$_3$, the magnetization of the CoFe can be reversed, giving rise to different voltage outputs. Through additional microscopy techniques, magnetization reversal is linked with the polarization state and antiferromagnetic cycloid propagation direction in the BiFeO$_3$. This study constitutes the building block for magnetoelectric spin-orbit logic, opening a new avenue for low-power beyond-CMOS technologies.

cond-mat.mes-hall↗

arXiv2023

Quantification of spin-charge interconversion in highly resistive sputtered Bi$_x$Se$_{1-x}$ with non-local spin valves

The development of spin-orbitronic devices, such as magneto-electric spin-orbit logic devices, calls for materials with a high resistivity and a high spin-charge interconversion efficiency. One of the most promising candidates in this regard is sputtered Bi$_x$Se$_{1-x}$. Although there are several techniques to quantify spin-charge interconversion, to date reported values for sputtered Bi$_x$Se$_{1-x}$ have often been overestimated due to spurious effects related to local currents combined with a lack of understanding of the effect of the interfaces and the use of approximations for unknown parameters, such as the spin diffusion length. In the present study, non-local spin valves are used to inject pure spin currents into Bi$_x$Se$_{1-x}$, allowing us to directly obtain its spin diffusion length as well as its spin Hall angle, from 10 K up to 300 K. These values, which are more accurate than those previously reported in sputtered Bi$_x$Se$_{1-x}$, evidence that the efficiency of this material is not exceptional. Indeed, the figure of merit for spin-charge interconversion, given by the product of these two parameters, is slightly under 1 nm. Our work demonstrates the importance of considering all material parameters and interfaces when quantifying the spin transport properties of materials with strong spin-orbit coupling.

cond-mat.mes-hall↗

arXiv2022

All-electrical spin-to-charge conversion in sputtered Bi$_x$Se$_{1-x}$

One of the major obstacles to realizing spintronic devices such as MESO logic devices is the small signal magnitude used for magnetization readout, making it important to find materials with high spin-to-charge conversion efficiency. Although intermixing at the junction of two materials is a widely occurring phenomenon, its influence on material characterization and the estimation of spin-to-charge conversion efficiencies is easily neglected or underestimated. Here, we demonstrate all electrical spin-to-charge conversion in Bi$_x$Se$_{1-x}$ nanodevices and show how the conversion efficiency can be overestimated by tens of times depending on the adjacent metal used as a contact. We attribute this to the intermixing-induced compositional change and the properties of a polycrystal that lead to drastic changes in resistivity and spin Hall angle. Strategies to improve the spin-to-charge conversion signal in similar structures for functional devices are discussed.

cond-mat.mes-hall↗

arXiv2021

Gaussian Random Number Generator with Reconfigurable Mean and Variance using Stochastic Magnetic Tunnel Junctions

Generating high-quality random numbers with a Gaussian probability distribution function is an important and resource consuming computational task for many applications in the fields of machine learning and Monte Carlo algorithms. Recently, CMOS-based digital hardware architectures have been explored as specialized Gaussian random number generators (GRNGs). These CMOS-based GRNGs have a large area and require entropy sources at their input which increase the computing cost. Here, we propose a GRNG that works on the principle of the Boltzmann law in a physical system made from an interconnected network of thermally unstable magnetic tunnel junctions. The proposed hardware can produce multi-bit Gaussian random numbers at a gigahertz speed and can be configured to generate distributions with a desired mean and variance. An analytical derivation of the required interconnection and bias strengths is provided followed by numerical simulations to demonstrate the functionalities of the GRNG.

cs.ET↗

arXiv2021

Electric field control of interaction between magnons and quantum spin defects

Hybrid systems coupling quantum spin defects (QSD) and magnons can enable unique spintronic device functionalities and probes for magnetism. Here, we add electric field control of magnon-QSD coupling to such systems by integrating ferromagnet-ferroelectric multiferroic with nitrogen-vacancy (NV) center spins. Combining quantum relaxometry with ferromagnetic resonance measurements and analytical modeling, we reveal that the observed electric-field tuning results from ferroelectric polarization control of the magnon-generated fields at the NV. Exploiting the demonstrated control, we also propose magnon-enhanced hybrid electric field sensors with improved sensitivity.

cond-mat.mes-hall↗

arXiv2020

Spin orbit torque controlled stochastic oscillators with synchronization and frequency tunability

Stochastic oscillators based on emerging nanodevices are attractive because of their ultra-low power requirement and ability to exhibit stochastic resonance, a phenomenon where synchronization to weak input signals is enabled due to ambient noise. In this work, a low barrier nanomagnet based stochastic oscillator is demonstrated, whose output jumps spontaneously between two states by harnessing the ambient thermal noise, requiring no additional power. Utilizing spin orbit torque in a three terminal device configuration, phase synchronization of these oscillators to weak periodic drives of particular frequencies is demonstrated. Experiments are performed to show the tunability of this synchronization frequency by controlling an electrical feedback parameter. The current required for synchronization is more than 8 times smaller than that required for deterministic switching of similar nanomagnetic devices. A model based on Kramers' transition rate in a symmetric double well potential is adopted and dynamical simulations are performed to explain the experimental results.

cond-mat.mes-hall↗

arXiv2020

Hardware implementation of Bayesian network building blocks with stochastic spintronic devices

Bayesian networks are powerful statistical models to understand causal relationships in real-world probabilistic problems such as diagnosis, forecasting, computer vision, etc. For systems that involve complex causal dependencies among many variables, the complexity of the associated Bayesian networks become computationally intractable. As a result, direct hardware implementation of these networks is one promising approach to reducing power consumption and execution time. However, the few hardware implementations of Bayesian networks presented in literature rely on deterministic CMOS devices that are not efficient in representing the inherently stochastic variables in a Bayesian network. This work presents an experimental demonstration of a Bayesian network building block implemented with naturally stochastic spintronic devices. These devices are based on nanomagnets with perpendicular magnetic anisotropy, initialized to their hard axes by the spin orbit torque from a heavy metal under-layer utilizing the giant spin Hall effect, enabling stochastic behavior. We construct an electrically interconnected network of two stochastic devices and manipulate the correlations between their states by changing connection weights and biases. By mapping given conditional probability tables to the circuit hardware, we demonstrate that any two node Bayesian networks can be implemented by our stochastic network. We then present the stochastic simulation of an example case of a four node Bayesian network using our proposed device, with parameters taken from the experiment. We view this work as a first step towards the large scale hardware implementation of Bayesian networks.

cond-mat.mes-hall↗

arXiv2020

Electrically-Tunable Stochasticity for Spin-based Neuromorphic Circuits: Self-Adjusting to Variation

Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures. Using a Magnetoresistive Random Access Memory (MRAM) probabilistic device (p-bit) as the basis of neuronal structures in Deep Belief Networks (DBNs), the impact of reducing the Magnetic Tunnel Junction's (MTJ's) energy barrier is assessed and optimized for the resulting stochasticity present in the learning system. This can mitigate the process variation sensitivity of stochastic DBNs which encounter a sharp drop-off when energy barriers exceed near-zero kT. As evaluated for the MNIST dataset for energy barriers at near-zero kT to 2.0 kT in increments of 0.5 kT, it is shown that the stability factor changes by 5 orders of magnitude. The self-compensating circuit developed herein provides a compact, and low complexity approach to mitigating process variation impacts towards practical implementation and fabrication.

cs.ET↗

arXiv2019

Correlated fluctuations in spin orbit torque-coupled perpendicular nanomagnets

Low barrier nanomagnets have attracted a lot of research interest for their use as sources of high quality true random number generation. More recently, low barrier nanomagnets with tunable output have been shown to be a natural hardware platform for unconventional computing paradigms such as probabilistic spin logic. Efficient generation and tunability of high quality random bits is critical for these novel applications. However, current spintronic random number generators are based on superparamagnetic tunnel junctions (SMTJs) with tunability obtained through spin transfer torque (STT), which unavoidably leads to challenges in designing concatenated networks using these two terminal devices. The more recent development of utilizing spin orbit torque (SOT) allows for a three terminal device design, but can only tune in-plane magnetization freely, which is not very energy efficient due to the needs of overcoming a large demagnetization field. In this work, we experimentally demonstrate for the first time, a stochastic device with perpendicular magnetic anisotropy (PMA) that is completely tunable by SOT without the aid of any external magnetic field. Our measurements lead us to hypothesize that a tilted anisotropy might be responsible for the observed tunability. We carry out stochastic Landau-Lifshitz-Gilbert (sLLG) simulations to confirm our experimental observation. Finally, we build an electrically coupled network of two such stochastic nanomagnet based devices and demonstrate that finite correlation or anti-correlation can be established between their output fluctuations by a weak interconnection, despite having a large difference in their natural fluctuation time scale. Simulations based on a newly developed dynamical model for autonomous circuits composed of low barrier nanomagnets show close agreement with the experimental results.

physics.app-ph↗