arXiv subjects

Hasibur Rahaman

Publications and source records attributed to Hasibur Rahaman.

6 recordsLinked to original sources

arXiv2026

Spin splitting torque enabled artificial neuron with self-reset via synthetic antiferromagnetic coupling

Spintronic artificial neurons are intriguing building blocks for energy efficient Neuromorphic Computing (NC). Nevertheless, most contemporary implementations rely on symmetry breaking external in plane magnetic fields (H_X) for neuron operation, which limits scalability and hardware practicality. We experimentally demonstrate an altermagnet/Synthetic Antiferromagnetic Coupling (SAF) based spintronic neuron that uses out of plane spin ({\sigma}_Z) polarized spin-splitting torque to eliminate the necessity of an external H_X. The neuron device also features intrinsic self-reset function facilitated by built-in exchange coupling. Furthermore, the proposed device is validated for Spiking Neural Network (SNN) applications by achieving test accuracies of 95.99% and 94.36% on the MNIST and N-MNIST datasets, respectively. These results demonstrate the hardware feasibility and compatibility of the proposed spintronic neuron, highlighting its potential for compact, scalable and energy-efficient neuromorphic computing systems.

physics.app-ph↗

arXiv2026

Synergy of fivefold boost SOT efficiency and field-free magnetization switching with broken inversion symmetry: Toward neuromorphic computing

Non-volatile Neuromorphic Computing (NC) elements utilizing Spin Orbit Torque (SOT) provide a viable solution to alleviate the memory wall bottleneck in contemporary computing systems. However, the two challenges, low SOT efficiency and the need for in plane symmetry breaking field for perpendicular magnetization switching, greatly limit its practical implementation. In this work, the enhanced SOT efficiency of Platinum (Pt) SOT layer and field free perpendicular magnetization switching are achieved by integrating thin Ruthenium Oxide (RuO2) layer in our material stack. The optimal RuO2 thickness (0.5 nm) enhances 5.2 times Damping Like (DL) SOT efficiency compared with pure SOT layer (Pt), as determined by hysteresis loop shift measurements, with a relatively low resistivity (90 micro-Ohm-cm). Moreover, we achieve 3 times reduction of critical magnetization switching current density compared to reference sample. Our experimental findings also demonstrate Rashba-induced substantial field-free magnetization switching in the presence of an emergent built-in interfacial field. Notably, reliable multi resistance synaptic states are achieved by tailoring the synergistic effects of enhanced SOT and interfacial magnetism. The functionality of synaptic states has been further evaluated by implementing an artificial neural network and achieved image recognition accuracies of approximately 95% and 87% on the MNIST and Fashion-MNIST datasets, respectively. This systematic study paves the way to energy-efficient, field-free SOT synapses for practical NC applications.

cond-mat.mes-hall↗

arXiv2025

Magnetic Orbital Hall Effect in Altermagnet RuO$_2$

Orbital angular momentum provides an alternative channel for current-induced magnetization switching beyond conventional spin--orbit coupling. While orbital Hall effects have been observed in several nonmagnetic materials, their manifestation in symmetry-compensated magnetic systems remains unexplored. Here, we report experimental evidence for a magnetic orbital Hall effect in RuO$_2$. In RuO$_2$(101)/Pt/Co heterostructures, we observe a pronounced unconventional torque characterized by a large out-of-plane component, strong crystalline anisotropy, and deterministic field-free switching of a perpendicular ferromagnet over a wide range of RuO$_2$ thicknesses. The torque exhibits a non-monotonic dependence on Pt thickness, reaching a maximum at 1.5~nm, and displays a long-range RuO$_2$ thickness ($t_{\mathrm{RuO}_2}$) dependence that saturates for $t_{\mathrm{RuO}_2}>100~\mathrm{nm}$. These features cannot be reconciled with conventional spin-current mechanisms. Rather, they indicate a magnetic orbital Hall effect in RuO$_2$ that could originate from exchange-induced momentum-dependent band splitting and its interplay with spin--orbit and crystal-field coupling, with the generated orbital current converted into torque in Pt. Our findings establish altermagnets as intrinsic sources of orbital currents and extend orbitronics to symmetry-compensated magnetic systems.

cond-mat.mes-hall↗

arXiv2024

Leaky-Integrate-Fire Neuron via Synthetic Antiferromagnetic Coupling and Spin-Orbit Torque

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.

physics.app-ph↗

arXiv2022

Emulation of Neuron and Synaptic Functions in Spin-Orbit Torque Domain Wall Devices

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.

cond-mat.mes-hall↗

arXiv2018

Unraveling the Mystery of Indian Summer Monsoon Prediction: Improved Estimate of Predictability Limit

Large socio-economic impact of the Indian Summer Monsoon (ISM) extremes motivated numerous attempts at its long range prediction over the past century. However, a rather estimated low potential predictability limit (PPL) of seasonal prediction of the ISM, contributed significantly by 'internal' interannual variability was considered insurmountable. Here we show that the 'internal' variability contributed by the ISM sub-seasonal (synoptic + intra-seasonal) fluctuations, so far considered chaotic, is partly predictable as found to be tied to slowly varying forcing (e.g. El Nino and Southern Oscillation). This provides a scientific basis for predictability of the ISM rainfall beyond the conventional estimates of PPL. We establish a much higher actual limit of predictability (r~0.82) through an extensive re-forecast experiment (1920 years of simulation) by improving two major physics in a global coupled climate model, which raises a hope for a very reliable dynamical seasonal ISM forecasting in the near future.

physics.ao-ph↗