Related papers: Monolithically Integrated VO$_2$ Mott Oscillators …
Vanadium dioxide (${\rm VO}_2$) is a phase change material (PCM) that exhibits a large change in complex refractive index on the order of unity upon switching from its dielectric to its metallic phase. Although this property is key for the…
To develop a new generation of high-speed photonic modulators on silicon-technology-based photonics, new materials with large Pockels coefficients have been transferred to silicon substrates. Previous approaches focus on realizing…
An abrupt Mott metal-insulator transition (MIT) rather than the continuous Hubbard MIT near a critical on-site Coulomb energy U/U_c=1 is observed for the first time in VO_2, a strongly correlated material, by inducing holes of about 0.018%…
Optical methods for magnetism manipulation have been considered as a promising strategy for ultralow-power and ultrahigh-speed spin switches, which becomes a hot spot in the field of spintronics. However, a widely applicable and efficient…
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…
Aside from recent advances in artificial intelligence (AI) models, specialized AI hardware is crucial to address large volumes of unstructured and dynamic data. Hardware-based AI, built on conventional complementary metal-oxidesemiconductor…
Neuromorphic systems that densely integrate CMOS spiking neurons and nano-scale memristor synapses open a new avenue of brain-inspired computing. Existing silicon neurons have molded neural biophysical dynamics but are incompatible with…
Semiconducting monolayer of 2D material are able to concatenate multiple interesting properties into a single component. Here, by combining opto-mechanical and electronic measurements, we demonstrate the presence of a partial 2H-1T phase…
Neuromorphic networks of artificial neurons and synapses can solve computational hard problems with energy efficiencies unattainable for von Neumann architectures. For image processing, silicon neuromorphic processors outperform graphic…
A Ferroelectric Analog Non-Volatile Memory based on a WOx electrode and ferroelectric HfZrO$_4$ layer is fabricated at a low thermal budget (~375$^\circ$C), enabling BEOL processes and CMOS integration. The devices show suitable properties…
A theory of the metal-insulator transition in vanadium dioxide from the high-temperature rutile to the low- temperature monoclinic phase is proposed on the basis of cluster dynamical mean field theory, in conjunction with the density…
Abstract: Bionic learning with fused sensing, memory and processing functions outperforms artificial neural networks running on silicon chips in terms of efficiency and footprint. However, digital hardware implementation of bionic learning…
Neuromorphic functionalities in memristive devices are commonly associated with the ability to electrically create local conductive pathways by resistive switching. The archetypal correlated material, VO2, has been intensively studied for…
The XOR Boolean logic gate is widely used in many applications such as encryption (XOR ciphers), binary addition (half- and full-adders), error detection (parity bits), etc. but is challenging to construct because of its demanding…
Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to…
Advanced neural interfaces mediate a bio-electronic link between the nervous system and microelectronic devices, bearing great potential as innovative therapy for various diseases. Spikes from a large number of neurons are recorded leading…
In this work, we propose valley-coupled spin-hall memories (VSH-MRAMs) based on monolayer WSe2. The key features of the proposed memories are (a) the ability to switch magnets with perpendicular magnetic anisotropy (PMA) via VSH effect and…
Spiking Neural Networks (SNNs) are gaining widespread momentum in the field of neuromorphic computing. These network systems integrated with neurons and synapses provide computational efficiency by mimicking the human brain. It is desired…
Micro- and nano-electromechanical resonators are a fundamental building block of modern technology, used in environmental monitoring, robotics, medical tools as well as fundamental science. These devices rely on dedicated electronics to…
Resistive switching is the fundamental process that triggers the sudden change of the electrical properties in solid-state devices under the action of intense electric fields. Despite its relevance for information processing, ultrafast…