RESUMO
Iontronic fluidic ionic/electronic components are emerging as promising elements for artificial brain-like computation systems. Nanopore ionic rectifiers can be operated as a synapse element, exhibiting conductance modulation in response to a train of voltage impulses, thus producing programmable resistive states. We propose a model that replicates hysteresis, rectification, and time domain response properties, based on conductance modulation between two conducting modes and a relaxation time of the state variable. We show that the kinetic effects observed in hysteresis loops govern the potentiation phenomena related to conductivity modulation. To illustrate the efficacy of the model, we apply it to replicate rectification, hysteresis and conductance modulation of two different experimental systems: a polymer membrane with conical pores, and a blind-hole nanoporous anodic alumina membrane with a barrier oxide layer. We show that the time transient analysis of the model develops the observed potentiation and depression phenomena of the synaptic properties.
RESUMO
With the increasing demands and complexity of the neuromorphic computing schemes utilizing highly efficient analog resistive switching devices, understanding the apparent capacitive and inductive effects in device operation is of paramount importance. Here, we present a systematic array of characterization methods that unravel two distinct voltage-dependent regimes demonstrating the complex interplay between the dynamic capacitive and inductive effects in volatile perovskite-based memristors: (1) a low voltage capacitance-dominant and (2) an inductance-dominant regime evidenced by the highly correlated hysteresis type with nonzero crossing, the impedance responses, and the transient current characteristics. These dynamic capacitance- and inductance-dominant regimes provide fundamental insight into the resistive switching of memristors governing the synaptic depression and potentiation functions, respectively. More importantly, the pulse width-dependent and long-term transient current measurements further demonstrate a dynamic transition from a fast capacitive to a slow inductive response, allowing for the tailored stimulus programming of memristor devices to mimic synaptic functionality.
RESUMO
The kinetics of light emission in halide perovskite light-emitting diodes (LEDs) and solar cells is composed of a radiative recombination of voltage-injected carriers mediated by additional steps such as carrier trapping, redistribution of injected carriers, and photon recycling that affect the observed luminescence decays. These processes are investigated in high-performance halide perovskite LEDs, with external quantum efficiency (EQE) and luminance values higher than 20% and 80 000 Cd m-2 , by measuring the frequency-resolved emitted light with respect to modulated voltage through a new methodology termed light emission voltage modulated spectroscopy (LEVS). The spectra are shown to provide detailed information on at least three different characteristic times. Essentially, new information is obtained with respect to the electrical method of impedance spectroscopy (IS), and overall, LEVS shows promise to capture internal kinetics that are difficult to be discerned by other techniques.
RESUMO
Frequency resolved methods are widely used to determine device properties of perovskite solar cells. However, obtaining the electronic parameters for diffusion and recombination by impedance spectroscopy has been so far elusive, since the measured spectra do not present the diffusion of electrons. Here we show that intensity modulated photocurrent spectroscopy (IMPS) displays a high frequency spiraling feature determined by the diffusion-recombination constants, under conditions of generation of carriers far from the collecting contact. We present models and experiments in two different configurations: the standard sandwich-contacts solar cell device and the quasi-interdigitated back-contact (QIBC) device for lateral long-range diffusion. The results of the measurements produce the hole diffusion coefficient of D p = 0.029 cm2/s and lifetime of τ p = 16 µs for one cell and D p = 0.76 cm2/s and τ p = 1.6 µs for the other. The analysis in the frequency domain is effective to separate the carrier diffusion (at high frequency) from the ionic contact phenomena at a low frequency. This result opens the way for a systematic determination of transport and recombination features in a variety of operando conditions.
RESUMO
Understanding the operation of neurons and synapses is essential to reproducing biological computation. Building artificial neuromorphic networks opens the door to a new generation of faster and low-energy-consuming electronic circuits for computation. The main candidates to imitate the natural biocomputation processes, such as the generation of action potentials and spiking, are memristors. Generally, the study of the performance of material neuromorphic elements is done by the analysis of time transient signals. Here, we present an analysis of neural systems in the frequency domain by small-amplitude ac impedance spectroscopy. We start from the constitutive equations for the conductance and memory effect, and we derive and classify the impedance spectroscopy spectra. We first provide a general analysis of a memristor and demonstrate that this element can be expressed as a combination of simple parts. In particular, we derive a basic equivalent circuit where the memory effect is represented by an RL branch. We show that this ac model is quite general and describes the inductive/negative capacitance response in many systems such as halide perovskites and organic LEDs. Thereafter, we derive the impedance response of the integrate-and-fire exponential adaptative neuron model that introduces a negative differential resistance and a richer set of spectra. On the basis of these insights, we provide an interpretation of the varied spectra that appear in the more general Hodgkin-Huxley neuron model. Our work provides important criteria to determine the properties that must be found in material realizations of neuronal elements. This approach has the great advantage that the analysis of highly complex phenomena can be based purely on the shape of experimental impedance spectra, avoiding the need for specific modeling of rather involved material processes that produce the required response.
Assuntos
Espectroscopia Dielétrica , Redes Neurais de Computação , Eletrônica , Neurônios , SinapsesRESUMO
Small perturbation techniques have proven to be useful tools for the investigation of perovskite solar cells. A correct interpretation of the spectra given by impedance spectroscopy (IS), intensity-modulated photocurrent spectroscopy (IMPS), and intensity-modulated photovoltage spectroscopy (IMVS) is key for the understanding of device operation. The utilization of a correct equivalent circuit to extract real parameters is essential to make this good interpretation. In this work, we present an equivalent circuit, which is able to reproduce the general and the exotic behaviors found in impedance spectra. From the measurements, we demonstrate that the midfrequency features that may appear to depend on the active layer thickness, and we also prove the spectral correlation of the three techniques that has been suggested theoretically.
RESUMO
The analysis of perovskite solar cells by impedance spectroscopy has provided a rich variety of behaviors that demand adequate interpretation. Two main features have been reported: First, different impedance spectral arcs vary in combination; second, inductive loops and negative capacitance characteristics appear as an intrinsic property of the current configuration of perovskite solar cells. Here we adopt a previously developed surface polarization model based on the assumption of large electric and ionic charge accumulation at the external contact interface. Just from the equations of the model, the impedance spectroscopy response is calculated and explains the mentioned general features. The inductance element in the equivalent circuit is the result of the delay of the surface voltage and depends on the kinetic relaxation time. The model is therefore able to quantitatively describe exotic features of the perovskite solar cell and provides insight into the operation mechanisms of the device.