Switching dynamics of nanoscale ferroelectric capacitors with a radius of 35 nm were investigated using piezoresponse force microscopy. Polarization switching starts with only one nucleation event occurring only at the predetermined places. The switching dynamics of nanoscale capacitors did not follow the classical Kolmogorov-Avrami-Ishibashi model. On the basis of the consideration of two separate (nucleation and growth) steps within a nonstatistical finite system, we have proposed a model which is in good agreement with the experimental results.
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http://dx.doi.org/10.1021/nl9038339 | DOI Listing |
J Phys Chem A
January 2025
Department of Chemistry and Chemical Biology, Center for Computational Chemistry, University of New Mexico, Albuquerque, New Mexico 87131, United States.
The kinetics of electronically inelastic quenching of O(Δ) and O(Σ) by collisions with O(P) have been investigated using mixed quantum-classical trajectories governed by adiabatic potential energy surfaces and state couplings generated from a recently developed diabatic potential energy matrix (DPEM) for the 14 lowest-energy A' states of O. Using the coherent switching with decay of mixing (CSDM) method, dynamics calculations were performed both with 14 coupled electronic states and with 8 coupled electronical states, and similar results were obtained. The calculated thermal quenching rate coefficients are generally small, but they increase with temperature.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
University of Strathclyde, Institute of Photonics, SUPA Dept of Physics, Glasgow, United Kingdom.
We report a spiking flip-flop memory mechanism that allows controllably switching between neural-like excitable spike-firing and quiescent dynamics in a resonant tunneling diode (RTD) neuron under low-amplitude (<150 mV pulses) and high-speed (ns rate) inputs pulses. We also show that the timing of the set-reset input pulses is critical to elicit switching responses between spiking and quiescent regimes in the system. The demonstrated flip-flop spiking memory, in which spiking regimes can be controllably excited, stored, and inhibited in RTD neurons via specific low-amplitude, high-speed signals (delivered at proper time instants) offers high promise for RTD-based spiking neural networks, with the potential to be extended further to optoelectronic implementations where RTD neurons and RTD memory elements are deployed alongside for fast and efficient photonic-electronic neuromorphic computing and artificial intelligence hardware.
View Article and Find Full Text PDFEClinicalMedicine
February 2025
Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Background: Reproductive coercion (RC) is a type of abuse where a partner intentionally attempts to interfere with fertility through deception or violence, often by manipulating one's contraceptive use or reproductive decision-making. Cross-sectional studies on the magnitude of RC across sub-Saharan Africa have noted associations with contraceptive use. No studies have longitudinally examined RC experiences as related to future contraceptive dynamics, including discontinuation or forgoing use altogether.
View Article and Find Full Text PDFAnimals survive in dynamic environments changing at arbitrary timescales, but such data distribution shifts are a challenge to neural networks. To adapt to change, neural systems may change a large number of parameters, which is a slow process involving forgetting past information. In contrast, animals leverage distribution changes to segment their stream of experience into tasks and associate them with internal task abstracts.
View Article and Find Full Text PDFUnderstanding how the collective activity of neural populations relates to computation and ultimately behavior is a key goal in neuroscience. To this end, statistical methods which describe high-dimensional neural time series in terms of low-dimensional latent dynamics have played a fundamental role in characterizing neural systems. Yet, what constitutes a successful method involves two opposing criteria: (1) methods should be expressive enough to capture complex nonlinear dynamics, and (2) they should maintain a notion of interpretability often only warranted by simpler linear models.
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