Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function.

There is an increasing need to implement neuromorphic systems that are both energetically and computationally efficient. There is also great interest in using electric elements with memory, memelements, that can implement complex neuronal functions intrinsically. A feature not widely incorporated in neuromorphic systems is history-dependent action potential time adaptation which is widely seen in real cells. Previous theoretical work shows that power-law history dependent spike time adaptation, seen in several brain areas and species, can be modeled with fractional order differential equations. Here, we show that fractional order spiking neurons can be implemented using super-capacitors. The super-capacitors have fractional order derivative and memcapacitive properties. We implemented two circuits, a leaky integrate and fire and a Hodgkin-Huxley. Both circuits show power-law spiking time adaptation and optimal coding properties. The spiking dynamics reproduced previously published computer simulations. However, the fractional order Hodgkin-Huxley circuit showed novel dynamics consistent with criticality. We compared the responses of this circuit to recordings from neurons in the weakly-electric fish that have previously been shown to perform fractional order differentiation of their sensory input. The criticality seen in the circuit was confirmed in spontaneous recordings in the live fish. Furthermore, the circuit also predicted long-lasting stimulation that was also corroborated experimentally. Our work shows that fractional order memcapacitors provide intrinsic memory dependence that could allow implementation of computationally efficient neuromorphic devices. Memcapacitors are static elements that consume less energy than the most widely studied memristors, thus allowing the realization of energetically efficient neuromorphic devices.

Fast Sub-Hz potentiostatic/galvanostatic bio-impedance measurements using chaotic oscillators.

The measurement of bio-impedance spectra at ultra low frequencies (sub-Hz) is known to require a considerably long time with the classical frequency-sweep method or other narrow-band periodic excitation signals. In this work, an impedance measurement technique based on using wide-band chaotic signals is proposed and experimentally validated over the frequency range [Formula: see text]. The technique was tested in both potentiostatic and galvanostatic modes, first using commercial components and then using an enhanced Howland current pump designed and fabricated in a 65nm CMOS technology. The accuracy of the proposed technique was assessed on fruit samples compared to measurements conducted using a research-grade Biologic VSP-300 electro-chemical station.

Plant Tissue Modelling Using Power-Law Filters.

Impedance spectroscopy has became an essential non-invasive tool for quality assessment measurements of the biochemical and biophysical changes in plant tissues. The electrical behaviour of biological tissues can be captured by fitting its bio-impedance data to a suitable circuit model. This paper investigates the use of power-law filters in circuit modelling of bio-impedance. The proposed models are fitted to experimental data obtained from eight different fruit types using a meta-heuristic optimization method (the Water Cycle Algorithm (WCA)). Impedance measurements are obtained using a Biologic SP150 electrochemical station, and the percentage error between the actual impedance and the fitted models' impedance are reported. It is found that a circuit model consisting of a combination of two second-order power-law low-pass filters shows the least fitting error.

Possibility of information encoding/decoding using the memory effect in fractional-order capacitive devices.

In this study, we show that the discharge voltage pattern of a supercapacitor exhibiting fractional-order behavior from the same initial steady-state voltage into a constant resistor is dependent on the past charging voltage profile. The charging voltage was designed to follow a power-law function, i.e. [Formula: see text], in which [Formula: see text] (charging time duration between zero voltage to the terminal voltage [Formula: see text]) and p ([Formula: see text]) act as two variable parameters. We used this history-dependence of the dynamic behavior of the device to uniquely retrieve information pre-coded in the charging waveform pattern. Furthermore, we provide an analytical model based on fractional calculus that explains phenomenologically the information storage mechanism. The use of this intrinsic material memory effect may lead to new types of methods for information storage and retrieval.

Extending the double-dispersion Cole-Cole, Cole-Davidson and Havriliak-Negami electrochemical impedance spectroscopy models.

Double-dispersion impedance models are important for the accurate fitting of spectral impedance measurements in Electrical Impedance Spectroscopy (EIS). While the Cole-Cole model is the most widely known, it is possible to define double-dispersion Cole-Davidson and Havriliak-Negami models as well. In this work, we show that more freedom can be exercised when these three models are combined together and that this combination can be done in various forms. Experimental results using a two-stage optimization algorithm applied on the suggested models are provided.

Atmospheric pressure air microplasma current time series for true random bit generation.

Generating true random bits of high quality at high data rates is usually viewed as a challenging task. To do so, physical sources of entropy with wide bandwidth are required which are able to provide truly random bits and not pseudorandom bits, as it is the case with deterministic algorithms and chaotic systems. In this work we demonstrate a reliable high-speed true random bit generator (TRBG) device based on the unpredictable electrical current time series of atmospheric pressure air microplasma (APAMP). After binarization of the sampled current time series, no further post-processing was needed in order for the bitstreams to pass all 15 tests of the NIST SP 800-22 statistical test suite. Several configurations of the system have been successfully tested at different sampling rates up to 100 MS/s, and with different inter-electrode distances giving visible/non-visible optical emissions. The cost-effectiveness, simplicity and ease of implementation of the proposed APAMP system compared to others makes it a very promising solution for portable TRBGs.

Extraction of bioimpedance phase information from its magnitude using a non-uniform Kramers-Kronig transform.

A novel non-uniform Kramers-Kronig Transform algorithm for bioimpedance phase extraction is proposed and tested in this work. The algorithm error is studied and compared with a previously proposed phase extraction technique, also based on the Kramers-Kronig transform. Results using simulated datasets and experimental datasets confirm the excellent performance of the algorithm.

Corrigendum: Reevaluation of Performance of Electric Double-layer Capacitors from Constant-current Charge/Discharge and Cyclic Voltammetry.

This corrects the article DOI: 10.1038/srep38568.

Reevaluation of Performance of Electric Double-layer Capacitors from Constant-current Charge/Discharge and Cyclic Voltammetry.

The electric characteristics of electric-double layer capacitors (EDLCs) are determined by their capacitance which is usually measured in the time domain from constant-current charging/discharging and cyclic voltammetry tests, and from the frequency domain using nonlinear least-squares fitting of spectral impedance. The time-voltage and current-voltage profiles from the first two techniques are commonly treated by assuming ideal RsC behavior in spite of the nonlinear response of the device, which in turn provides inaccurate values for its characteristic metrics [corrected]. In this paper we revisit the calculation of capacitance, power and energy of EDLCs from the time domain constant-current step response and linear voltage waveform, under the assumption that the device behaves as an equivalent fractional-order circuit consisting of a resistance Rs in series with a constant phase element (CPE(Q, α), with Q being a pseudocapacitance and α a dispersion coefficient). In particular, we show with the derived (Rs, Q, α)-based expressions, that the corresponding nonlinear effects in voltage-time and current-voltage can be encompassed through nonlinear terms function of the coefficient α, which is not possible with the classical RsC model. We validate our formulae with the experimental measurements of different EDLCs.

Reduced Graphene Oxide Thin Film on Conductive Substrates by Bipolar Electrochemistry.

Recent years have shown an increased interest in developing manufacturing processes for graphene and its derivatives that consider the environmental impact and large scale cost-effectiveness. However, today's most commonly used synthesis routes still suffer from their excessive use of harsh chemicals and/or the complexity and financial cost of the process. Furthermore, the subsequent transfer of the material onto a substrate makes the overall process even more intricate and time-consuming. Here we describe a single-step, single-cell preparation procedure of metal-supported reduced graphene oxide (rGO) using the principle of bipolar electrochemistry of graphite in deionized water. Under the effect of an electric field between two stainless steel feeder electrodes, grapheme layers at the anodic pole of the wireless graphite were oxidized into colloidal dispersion of GO, which migrated electrophoretically towards the anodic side of the cell, and deposited in the form of rGO (d(002) = 0.395 nm) by van der Waals forces. For substrates chemically more susceptible to the high anodic voltage, we show that the electrochemical setup can be adapted by placing the latter between the wireless graphite and the stainless steel feeder anode. This method is straightforward, inexpensive, environmentally-friendly, and could be easily scaled up for high yield and large area production of rGO thin films.

Extracting the parameters of the double-dispersion Cole bioimpedance model from magnitude response measurements.

In the field of bioimpedance measurements, the Cole impedance model is widely used for characterizing biological tissues and biochemical materials. In this work, a nonlinear least squares fitting is applied to extract the double-dispersion Cole impedance parameters from simulated magnitude response datasets without requiring the direct impedance data or phase information. The technique is applied to extract the impedance parameters from MATLAB simulated noisy magnitude datasets showing less than 1.2 % relative error when 60 dB SNR Gaussian white noise is present. This extraction is verified experimentally using apples as the Cole impedances showing less than 3 % relative error between simulated responses (using the extracted impedance parameters) and the experimental results over the entire dataset.