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Ping Feng

Publications and source records attributed to Ping Feng.

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Revisiting neutron-skin thickness and dipole polarizability constraints on the symmetry energy in Antisymmetrized Molecular Dynamics

The neutron-skin thickness and electric dipole polarizability are among the most sensitive probes of the symmetry energy at subsaturation densities. Motivated by the tension raised by recent analyses of PREX-II and CREX data within density-functional-based approaches, we perform a unified study of static and dynamical isovector observables within the antisymmetrized molecular dynamics (AMD) framework. Using thirty interaction parameter sets that span different values of the symmetry-energy coefficient $S_0$, slope parameter $L$, and neutron-proton effective-mass splitting $\Delta m_{np}^*$, we systematically analyze the neutron-skin thicknesses of nuclei from $^{40}$Ca to $^{238}$U together with the electric dipole polarizability $\alpha_D$ of $^{208}$Pb. A combined $\chi^2$ analysis of neutron-skin thicknesses and the electric dipole polarizability yields preferred values of $L$ that increase with $S_0$, reflecting the joint constraint from the static and dynamical observables. Furthermore, we identify the density region mainly probed by these observables as 0.019 $\le \rho/\rho_0\le $0.60, where the relative narrowing strength function varies by less than 10% compared to its maximum narrowing strength. The maximum reduction of the uncertainty of $S(\rho)$ occurs at 0.28 $\rho_0$, where the symmetry energy within 1$\sigma_{post}$ uncertainty is constrained to be $S(0.28\rho_0) = 13.84\pm 1.31$ MeV. These results demonstrate that a unified AMD analysis of neutron-skin systematics and dipole polarizability provides a complementary constraint on the symmetry energy below saturation density.

nucl-th

Flexible Metal Oxide/Graphene Oxide Hybrid Neuromorphic Devices on Flexible Conducting Graphene Substrates

Flexible metal oxide/graphene oxide hybrid multi-gate neuron transistors were fabricated on flexible graphene substrates. Dendritic integrations in both spatial and temporal modes were successfully emulated, and spatiotemporal correlated logics were obtained. A proof-of-principle visual system model for emulating lobula giant motion detector neuron was investigated. Our results are of great interest for flexible neuromorphic cognitive systems.

q-bio.NC

Proton Conducting Graphene Oxide Coupled Neuron Transistors for Brain-Inspired Cognitive Systems

Neuron is the most important building block in our brain, and information processing in individual neuron involves the transformation of input synaptic spike trains into an appropriate output spike train. Hardware implementation of neuron by individual ionic/electronic hybrid device is of great significance for enhancing our understanding of the brain and solving sensory processing and complex recognition tasks. Here, we provide a proof-of-principle artificial neuron based on a proton conducting graphene oxide (GO) coupled oxide-based electric-double-layer (EDL) transistor with multiple driving inputs and one modulatory input terminal. Paired-pulse facilitation, dendritic integration and orientation tuning were successfully emulated. Additionally, neuronal gain control (arithmetic) in the scheme of rate coding is also experimentally demonstrated. Our results provide a new-concept approach for building brain-inspired cognitive systems.

q-bio.NC

Dendritic Integration Regulation and Neuronal Arithmetic Implemented in a Proton-Coupled Neuron Transistor

Neuron is the most important building block in our brain, and information processing in individual neuron involves the transformation of input synaptic spike trains into an appropriate output spike train. Hardware implementation of neuron by individual ionic/electronic coupled device is of great importance for enhancing our understanding of the brain and solving sensory processing and complex recognition tasks. Here, we provide a proof-of-principle artificial neuron with multiple presynaptic inputs and one modulatory terminal based on a proton-coupled oxide-based electric-double-layer transistor. Regulation of dendritic integration was realized by tuning the voltage applied on the modulatory terminal. Additionally, neuronal gain control (arithmetic) in the scheme of temporal-correlated coding and rate coding are also mimicked. Our results provide a new-concept approach for building brain-inspired neuromorphic systems.

q-bio.NC

Flexible Sensory Platform Based on an Electrolyte-Gated Oxide Neuron Transistor

Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuron transistors gated by solid-state electrolyte films are fabricated on flexible plastic substrates for biochemical sensing applications. When a quasi-static dual-gate laterally synergic sensing mode is adopted, the neuron transistor sensor shows a high pH sensitivity of ~105 mV/pH, which is higher than the Nernst limit. Our results demonstrate that single-spike dynamic mode can remarkably improve the pH sensitivity, reduce response/recover time and power consumption. We also find that appropriate depression applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuron transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.

cond-mat.mtrl-sci

On a Lower Bound for the Time Constant of First-Passage Percolation

We consider the Bernoulli first-passage percolation on $\mathbb Z^d (d\ge 2)$. That is, the edge passage time is taken independently to be 1 with probability $1-p$ and 0 otherwise. Let ${μ(p)}$ be the time constant. We prove in this paper that \[ μ(p_1)-μ({p_2})\ge \frac{μ(p_2)}{1-p_2}(p_2-p_1)\] for all $ 0\leq p_1<p_2< 1$ by using Russo's formula.

math.PR