Related papers: Ultra-High Density, High-Performance and Energy-Ef…
The research challenge of current Wireless Sensor Networks (WSNs) is to design energy-efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such as environmental monitoring. Traditional WSNs consist of low…
Integrated optically-inspired wave-based processing is envisioned to outperform digital architectures in specific tasks, such as image processing and speech recognition. In this view, spin-waves represent a promising route due to their…
Electrical manipulation of spin textures inside antiferromagnets represents a new opportunity for developing spintronics with superior speed and high device density. Injecting spin currents into antiferromagnets and realizing efficient…
Efficient manipulation of magnetic materials is essential for spintronics. In spin-current generator/magnet bilayers, the efficiency of spin-orbit torques per magnetic layer thickness scales inversely with the magnetic layer thickness,…
Spin-polarized antiferromagnets (AFMs), including altermagnets, noncollinear AFMs, and two-dimensional layer-polarized AFMs, have emerged as transformative materials for next-generation spintronic and optoelectronic technologies. These…
In comparison to the conventional complementary pull-up and pull-down logic structure, the pass transistor logic (PTL) family reduces the number of transistors required to perform logic functions, thereby reducing both area and power…
Soft magnetic materials (SMMs) serve in electrical applications and sustainable energy supply, allowing magnetic flux variation in response to changes in applied magnetic field, at low energy loss1. The electrification of transport,…
Superconducting circuits are promising candidates for future computational architectures, however, practical applications require fast operation. Here, we demonstrate fast, gate-based switching of an Al nanowire-based superconducting switch…
Ultrafast magnetization dynamics are governed by energy flow between electronic, magnetic, and lattice degrees of freedom. A quantitative understanding of these dynamics must be based on a model that agrees with experimental results for all…
In magnonics, an emerging branch of wave physics characterized by low-energy consumption, it is highly desirable to realize circuit elements within the scope of spin-wave computing. Here, based on numerical simulations, we demonstrate the…
Electronic transport through a single-wall metallic carbon nanotube weakly coupled to one ferromagnetic and one nonmagnetic lead is analyzed in the sequential tunneling limit. It is shown that both the spin and charge currents flowing…
Spiking Neural Networks (SNNs) have gained significant research attention in the last decade due to their potential to drive resource-constrained edge devices. Though existing SNN accelerators offer high efficiency in processing sparse…
Altermagnets, a newly discovered class of magnets, integrate the advantages of both ferromagnets and antiferromagnets, such as enabling anomalous transport without stray fields and supporting ultrafast spin dynamics, offering exciting…
One-shot neural architecture search (NAS) substantially improves the search efficiency by training one supernet to estimate the performance of every possible child architecture (i.e., subnet). However, the inconsistency of characteristics…
Spin waves are excitations in ferromagnetic media that have been proposed as information carriers in hybrid spintronic devices with much lower operation power than conventional charge-based electronics. Their wave nature can be exploited in…
Altermagnetic (AM) materials have recently attracted significant interest due to the non-relativistic momentum-dependent spin splitting of their electronic band structure which may be useful for antiferromagnetic (AFM) spintronics. So far,…
The development of energy-efficient neuromorphic hardware using spintronic devices based on antiferromagnetic (AFM) skyrmion motion on nanotracks has gained considerable interest. Owing to its properties such as robustness against external…
We investigated a possible use of the magnonic interferometric switches in multi-valued logic circuits. The switch is a three-terminal device consisting of two spin channels where input, control, and output signals are spin waves. Signal…
On-device machine learning (ODML) enables intelligent applications on resource-constrained devices. However, power consumption poses a major challenge, forcing a trade-off between model accuracy and power efficiency that often limits model…
To date, endeavors in nanoscale spintronics are dominated by the use of single-electron or single-spin transistors having at their heart a semiconductor, metallic or molecular quantum dot who's localized states are non-spin-degenerate and…