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Down-scaling device dimensions to the nanometer range raises significant challenges to traditional device design, due to potential current leakage across nanoscale dimensions and the need to maintain reproducibility while dealing with…
Resistive switching devices and other components with negative differential resistance (NDR) are emerging as possible electronic constituents of next-generation computing architectures. Due to the NDR effects exhibited, switching operations…
Nonlinear electrical properties, such as negative differential resistance (NDR), are essential in numerous electrical circuits, including memristors. Several physical origins have been proposed to lead to the NDR phenomena in semiconductor…
Current-controlled (also known as "S-type") negative differential resistance (NDR) is of crucial importance to many emerging applications including neuromorphic computing and high-density memristors integration. However, the experimental…
We determine the conditions in which negative differential resistance (NDR) appears in the C$_{60}$-based molecular device of [Phys. Rev. Lett. {\bf 100}, 036807 (2008)] by means of ab-initio electron-transport simulations. Our calculations…
Desirably, the world relies on the devices being compact, as they could drive to the increased functionality of integrated circuits at the provided footstep, that is becoming more reliable. To reduce the scalability over the devices,…
The miniaturization of transistors down to 5nm and beyond, plus the increasing complexity of integrated circuits, significantly aggravate short channel effects, and demand analysis and optimization of more design corners and modes.…
Maintaining benefits of CMOS technology scaling is becoming challenging due to increased manufacturing complexities and unwanted passive power dissipations. This is particularly challenging in SRAM, where manufacturing precision and leakage…
Given the prevalence of superconducting platforms for uses in quantum computing and quantum sensing, the simulation of quantum superconducting circuits has become increasingly important for identifying system characteristics and modeling…
We use the formerly derived explicit analytical expressions for the conductivity of nanostructured superconductors supercooled below the critical temperature in electric field. Computer simulations reveal that the negative differential…
Electron spin qubits in quantum dot devices are promising for scalable quantum computing. However, architectural support is currently hindered by the lack of realistic and performant simulation methods for real devices. Physics-based tools…
A decrease in current with increasing voltage, often referred to as negative differential resistance (NDR), has been observed in many electronic devices and can usually be understood within a one-electron picture. However, NDR has recently…
Nanometallic devices based on amorphous insulator-metal thin films are developed to provide a novel non-volatile resistance-switching random-access memory (RRAM). In these devices, data recording is controlled by a bipolar voltage, which…
Quantum error mitigation (QEM) is vital for improving quantum algorithms' accuracy on noisy near-term devices. A typical QEM method, called Virtual Distillation (VD), can suffer from imperfect implementation, potentially leading to worse…
Non-volatile Memory (NVM) technologies present a promising alternative to traditional volatile memories such as SRAM and DRAM. Due to the limited availability of real NVM devices, simulators play a crucial role in architectural exploration…
By using quantum mechanical effects, quantum computers promise significant speedups in solving problems intractable for conventional computers. However, despite recent progress they remain limited in scaling and availability-making quantum…
The operation of a novel nonvolatile memory device based on a conductive ferroelectric/non-ferroelectric thin film multilayer stack is simulated numerically. The simulation involves the self-consistent steady state solution of Poisson's…
Neuromorphic computing systems uses non-volatile memory (NVM) to implement high-density and low-energy synaptic storage. Elevated voltages and currents needed to operate NVMs cause aging of CMOS-based transistors in each neuron and synapse…
The silicon nanowire transistor (SNWT) is a promising device structure for future integrated circuits, and simulations will be important for understanding its device physics and assessing its ultimate performance limits. In this work, we…
Computing-in-memory with emerging non-volatile memory (nvCiM) is shown to be a promising candidate for accelerating deep neural networks (DNNs) with high energy efficiency. However, most non-volatile memory (NVM) devices suffer from…