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Reversible logic has received great attention in the recent years due to their ability to reduce the power dissipation which is the main requirement in low power digital design. It has wide applications advanced computing, low power CMOS…
Programmable materials are desirable for a variety of functional applications that range from biomedical devices, actuators and soft robots to adaptive surfaces and deployable structures. However, current smart materials are often designed…
Many types of molecular motors have been proposed and synthesized in recent years, displaying different kinds of motion, and fueled by different driving forces such as light, heat, or chemical reactions. We propose a new type of molecular…
Quantum-dot cellular automata (QCA) is a paradigm for low-power, general-purpose, classical computing designed to overcome the challenges facing CMOS in the extreme limits of scaling. A molecular implementation of QCA offers nanometer-scale…
In-memory computing is a promising alternative to traditional computer designs, as it helps overcome performance limits caused by the separation of memory and processing units. However, many current approaches struggle with unreliable…
In rule-based systems, goal-oriented computations correspond naturally to the possible ways that an observation may be explained. In some applications, we need to compute explanations for a series of observations with the same domain. The…
Superconductor electronics (SCE) is competing to become a platform for efficient implementations of neuromorphic computing and deep learning algorithms (DLAs) with projects mostly concentrating on searching for gates that would better mimic…
Invertible logic can operate in one of two modes: 1) a forward mode, in which inputs are presented and a single, correct output is produced, and 2) a reverse mode, in which the output is fixed and the inputs take on values consistent with…
We report multifunctional operation based on the nonlinear dynamics in a single microelectromechanical system (MEMS) resonator. This Letter focuses on a logic-memory device that uses a closed loop control and a nonlinear MEMS resonator in…
Phase-change memory (PCM) is a scalable and low latency non-volatile memory (NVM) technology that has been proposed to serve as storage class memory (SCM), providing low access latency similar to DRAM and often approaching or exceeding the…
This paper studies an input-driven one-state differential equation model initially developed for an experimentally demonstrated dynamic molecular switch that switches like synapses in the brain do. The linear-in-the-state and…
Reversible logic synthesis is emerging as a major research component for post-CMOS computing devices, in particular Quantum computing. In this work, we link the reversible logic synthesis problem to sorting algorithms. Based on our…
Neuromorphic computing with non-volatile memory (NVM) can significantly improve performance and lower energy consumption of machine learning tasks implemented using spike-based computations and bio-inspired learning algorithms. High…
We have developed a new superconducting digital technology, Reciprocal Quantum Logic, that uses AC power carried on a transmission line, which also serves as a clock. Using simple experiments we have demonstrated zero static power…
Recently, oscillator-based Boolean computation has been proposed for its potentials in noise immunity and energy efficiency. In such a system, logic bits are encoded in the relative phases of oscillating signals and stored in…
Neuromorphic computing has emerged as a promising avenue towards building the next generation of intelligent computing systems. It has been proposed that memristive devices, which exhibit history-dependent conductivity modulation, could…
Charge unbalance is one of the key issues for series-connected Lithium-ion cells. Within this context, model-based optimization strategies have proven to be the most effective. In the present paper, an ad-hoc electrochemical model, tailored…
Neuromorphic engineering makes use of mixed-signal analog and digital circuits to directly emulate the computational principles of biological brains. Such electronic systems offer a high degree of adaptability, robustness, and energy…
Several abilities of biological systems, such as adaptation to natural environment, or of animals to learn patterns when appropriately trained, are features that are extremely useful, if emulated by electronic circuits, in applications…
Understanding charging mechanisms and charge retention dynamics of nanocrystal memory devices is important in optimization of device design. Capacitance spectroscopy on PECVD grown germanium nanocrystals embedded in a silicon oxide matrix…