Related papers: CVD grown bilayer MoS2 based artificial optoelectr…
Artificial neuronal devices are the basic building blocks for neuromorphic computing systems, which have been motivated by realistic brain emulation. Aiming for these applications, various device concepts have been proposed to mimic the…
In the last decade, a 2-terminal passive circuit element called a memristor has been developed for non-volatile resistive random access memory and has more recently shown promise for neuromorphic computing. Compared to flash memory,…
Neuromorphic in-memory computing requires area-efficient architecture for seamless and low latency parallel processing of large volumes of data. Here, we report a compact, vertically integrated/stratified field-effect transistor (VSFET)…
The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS…
Highly efficient information processing in brain is based on processing and memory components called synapses, whose output is dependent on the history of the signals passed through them. Here we have developed an artificial synapse with…
Neurons with internal memory have been proposed for biological and bio-inspired neural networks, adding interesting functionality. We propose and model a nanoscale optoelectronic neural node with charge-based time-limited memory and signal…
Two-dimensional (2D) materials like transition metal dichalcogenides (TMD) have proved to be serious candidates to replace silicon in several technologies with enhanced performances. In this respect, the two remaining challenges are the…
Large capacitance enhancement is useful for increasing the gate capacitance of field-effect transistors (FETs) to produce low-energy-consuming devices with improved gate controllability. We report strong capacitance enhancement effects in a…
Memristors can mimic the functions of biological synapse, where it can simultaneously store the synaptic weight and modulate the transmitted signal. Here, we report Nb/Nb2O5/Pt based memristors with bipolar resistive switching, exhibiting…
Semiconducting 2D materials, such as molybdenum disulfide (MoS2) and other members of the transition metal dichalcogenide family, have emerged as promising materials for applications in high performance nanoelectronics that exhibit…
Non-volatile memory devices have been limited to flash architectures that are complex devices. Here, we present a unique photomemory effect in MoS$_2$ transistors. The photomemory is based on a photodoping effect - a controlled way of…
The neuromorphic BrainScaleS-2 ASIC comprises mixed-signal neurons and synapse circuits as well as two versatile digital microprocessors. Primarily designed to emulate spiking neural networks, the system can also operate in a vector-matrix…
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…
We demonstrate high accuracy classification for handwritten digits from the MNIST dataset ($\sim$98.00$\%$) and RGB images from the CIFAR-10 dataset ($\sim$86.80$\%$) by using resistive memories based on a 2D van-der-Waals semiconductor:…
Atomically thin semiconductors have versatile future applications in the information and communication technologies for the ultimate miniaturization of electronic components. In particular, the ongoing research demands not only a…
We report, for CVD-grown monolayer MoS2, the very first results on temporal degradation of material and device performance under electrical stress. Both low and high field regimes of operation are explored at different temperatures, gate…
Memristors are prominent passive circuit elements with promising futures for energy-efficient in-memory processing and revolutionary neuromorphic computation. State-of-the-art memristors based on two-dimensional (2D) materials exhibit…
Two-dimensional layered semiconductors have recently emerged as attractive building blocks for next-generation low-power non-volatile memories. However, challenges remain in the controllable sub-micron fabrication of bipolar resistively…
Ferroelectric field-effect transistors (FeFET) with two-dimensional (2D) semiconductor channels are promising low-power, embedded non-volatile memory (NVM) candidates for next-generation in-memory computing. However, the performance of…
Neuromorphic Computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation of artificial intelligence. Towards realizing NC, fabrication, and investigations of hardware elements such as…