Related papers: A Ferroelectric Tunnel Junction-based Integrate-an…
Ferroelectric tunnel junctions (FTJ) based on hafnium zirconium oxide (Hf1-xZrxO2; HZO) are a promising candidate for future applications, such as low-power memories and neuromorphic computing. The tunneling electroresistance (TER) is…
Ferroelectric tunneling junctions (FTJ) are considered to be the intrinsically most energy efficient memristors. In this work, specific electrical features of ferroelectric hafnium-zirconium oxide based FTJ devices are investigated.…
HfO2-based ferroelectric tunnel junctions (FTJs) exhibit attractive properties for adoption in neuromorphic applications. The combination of ultra-low-power multi-level switching capability together with the low on-current density suggests…
Ferroelectric tunnel junctions (FTJs) harness the unique combination of ferroelectricity and quantum tunneling, and thus herald new opportunities in next-generation nonvolatile memory technologies. Recent advancements in the fabrication of…
The human brain achieves exceptional energy efficiency by co-locating memory and processing, yet reproducing this principle in hardware remains challenging because many neuromorphic devices require standby power, offer limited…
We present a low barrier magnet based compact hardware unit for analog stochastic neurons and demonstrate its use as a building-block for neuromorphic hardware. By coupling circular magnetic tunnel junctions (MTJs) with a CMOS based analog…
This paper proposes a novel spiking artificial neuron design based on a combined spin valve/magnetic tunnel junction (SV/MTJ). Traditional hardware used in artificial intelligence and machine learning faces significant challenges related to…
CMOS-compatible HfO2-based ferroelectric tunnel junction (FTJ) has attracted significant attention as a promising candidate for in-memory computing (IMC) due to its extremely low power consumption. However, conventional FTJs face inherent…
The multiple ferroelectric polarization tuned by external electric field could be used to simulate the biological synaptic weight. Ferroelectric synaptic devices have two advantages compared with other reported ones: One is the intrinsic…
In ferroelectric materials, spontaneous symmetry breaking leads to a switchable electric polarization, which offers significant promise for nonvolatile memories. In particular, ferroelectric tunnel junctions (FTJs) have emerged as a new…
Antiferromagnetic Tunnel Junctions (AFMTJs) enable picosecond switching and femtojoule writes through ultrafast sublattice dynamics. We present the first end-to-end AFMTJ simulation framework integrating multi-sublattice…
We present an in-house modelling framework for Ferroelectric Tunnelling Junctions (FTJ), and an insightful study of the design of FTJs as synaptic devices. Results show that a moderately low-k tunnelling dielectric (e.g. SiO2) can increase…
The desire to empower resource-limited edge devices with computer vision (CV) must overcome the high energy consumption of collecting and processing vast sensory data. To address the challenge, this work proposes an energy-efficient…
The electrically readable complex dynamics of robust and scalable magnetic tunnel junctions (MTJs) offer promising opportunities for advancing neuromorphic computing. In this work, we present an MTJ design with a free layer and two…
The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) make SNNs promising for edge applications that require high energy efficiency. To realize SNNs in hardware, spintronic neuron implementations can bring…
Ferroelectric tunnel junctions (FTJs) leverage polarization-dependent tunneling through ultrathin barriers to enable two-terminal, non-volatile memory and logic. Although conceptually appealing, the practical implementation of conventional…
We present the design and numerical simulation of a spiking neuron capable of on-chip machine learning. Built within the CMOS+X framework, the spiking neuron consists of an NMOS transistor combined with a magnetic tunnel junction (MTJ).…
Brain-inspired computing architectures attempt to mimic the computations performed in the neurons and the synapses in the human brain in order to achieve its efficiency in learning and cognitive tasks. In this work, we demonstrate the…
Electrical-controllable antiferromagnet tunnel junction is a key goal in spintronics, holding immense promise for ultra-dense and ultra-stable antiferromagnetic memory with high processing speed for modern information technology. Here, we…
Antiferromagnetic Tunnel Junctions (AFMTJs) offer picosecond switching and high integration density for in-memory computing, but their ultrafast dynamics and low tunnel magnetoresistance (TMR) make state-of-the-art MRAM interfaces…