Dataset Information

Computational elements based on coupled VO₂ oscillators via tunable thermal triggering.

ABSTRACT: Computational technologies based on coupled oscillators are of great interest for energy efficient computing. A key to developing such technologies is the tunable control of the interaction among oscillators which today is accomplished by additional electronic components. Here we show that the synchronization of closely spaced vanadium dioxide (VO₂) oscillators can be controlled via a simple thermal triggering element that itself is formed from VO₂. The net energy consumed by the oscillators is lower during thermal coupling compared with the situation where they are oscillating independently. As the size of the oscillator shrinks from 6 μm to 200 nm both the energy efficiency and the oscillator frequency increases. Based on such oscillators with active tuning, we demonstrate AND, NAND, and NOR logic gates and various firing patterns that mimic the behavior of spiking neurons. Our findings demonstrate an innovative approach towards computational techniques based on networks of thermally coupled oscillators.

SUBMITTER: Li G

PROVIDER: S-EPMC11236964 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Computational elements based on coupled VO2 oscillators via tunable thermal triggering.

Li Guanmin G Wang Zhong Z Chen Yuliang Y Jeon Jae-Chun JC Parkin Stuart S P SSP

Nature communications 20240711 1

Computational technologies based on coupled oscillators are of great interest for energy efficient computing. A key to developing such technologies is the tunable control of the interaction among oscillators which today is accomplished by additional electronic components. Here we show that the synchronization of closely spaced vanadium dioxide (VO2) oscillators can be controlled via a simple thermal triggering element that itself is formed from VO2. The net energy consumed ...[more]

PMID: 38987537

Similar Datasets

Project description:Oscillatory Neural Networks (ONNs) are currently arousing interest in the research community for their potential to implement very fast, ultra-low-power computing tasks by exploiting specific emerging technologies. From the architectural point of view, ONNs are based on the synchronization of oscillatory neurons in cognitive processing, as occurs in the human brain. As emerging technologies, VO2 and memristive devices show promising potential for the efficient implementation of ONNs. Abundant literature is now becoming available pertaining to the study and building of ONNs based on VO2 devices and resistive coupling, such as memristors. One drawback of direct resistive coupling is that physical resistances cannot be negative, but from the architectural and computational perspective this would be a powerful advantage when interconnecting weights in ONNs. Here we solve the problem by proposing a hardware implementation technique based on differential oscillatory neurons for ONNs (DONNs) with VO2-based oscillators and memristor-bridge circuits. Each differential oscillatory neuron is made of a pair of VO2 oscillators operating in anti-phase. This way, the neurons provide a pair of differential output signals in opposite phase. The memristor-bridge circuit is used as an adjustable coupling function that is compatible with differential structures and capable of providing both positive and negative weights. By combining differential oscillatory neurons and memristor-bridge circuits, we propose the hardware implementation of a fully connected differential ONN (DONN) and use it as an associative memory. The standard Hebbian rule is used for training, and the weights are then mapped to the memristor-bridge circuit through a proposed mapping rule. The paper also introduces some functional and hardware specifications to evaluate the design. Evaluation is performed by circuit-level electrical simulations and shows that the retrieval accuracy of the proposed design is comparable to that of classic Hopfield Neural Networks.

Project description:This study presents an investigation of pacemaker mechanisms underlying lymphatic vasomotion. We tested the hypothesis that active inositol 1,4,5-trisphosphate receptor (IP(3)R)-operated Ca(2+) stores interact as coupled oscillators to produce near-synchronous Ca(2+) release events and associated pacemaker potentials, this driving action potentials and constrictions of lymphatic smooth muscle. Application of endothelin 1 (ET-1), an agonist known to enhance synthesis of IP(3), to quiescent lymphatic smooth muscle syncytia first enhanced spontaneous Ca(2+) transients and/or intracellular Ca(2+) waves. Larger near-synchronous Ca(2+) transients then occurred leading to global synchronous Ca(2+) transients associated with action potentials and resultant vasomotion. In contrast, blockade of L-type Ca(2+) channels with nifedipine prevented ET-1 from inducing near-synchronous Ca(2+) transients and resultant action potentials, leaving only asynchronous Ca(2+) transients and local Ca(2+) waves. These data were well simulated by a model of lymphatic smooth muscle with: 1), oscillatory Ca(2+) release from IP(3)R-operated Ca(2+) stores, which causes depolarization; 2), L-type Ca(2+) channels; and 3), gap junctions between cells. Stimulation of the stores caused global pacemaker activity through coupled oscillator-based entrainment of the stores. Membrane potential changes and positive feedback by L-type Ca(2+) channels to produce more store activity were fundamental to this process providing long-range electrochemical coupling between the Ca(2+) store oscillators. We conclude that lymphatic pacemaking is mediated by coupled oscillator-based interactions between active Ca(2+) stores. These are weakly coupled by inter- and intracellular diffusion of store activators and strongly coupled by membrane potential. Ca(2+) store-based pacemaking is predicted for cellular systems where: 1), oscillatory Ca(2+) release induces depolarization; 2), membrane depolarization provides positive feedback to induce further store Ca(2+) release; and 3), cells are interconnected. These conditions are met in a surprisingly large number of cellular systems including gastrointestinal, lymphatic, urethral, and vascular tissues, and in heart pacemaker cells.

Dataset Information

Computational elements based on coupled VO₂ oscillators via tunable thermal triggering.

Publications

Computational elements based on coupled VO<sub>2</sub> oscillators via tunable thermal triggering.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets