Exploring the Reconfigurable Memory Effect in Electroforming-Free YMnO3-Based Resistive Switches: Towards a Tunable Frequency Response.

Memristors, since their inception, have demonstrated remarkable characteristics, notably the exceptional reconfigurability of their memory. This study delves into electroforming-free YMnO3 (YMO)-based resistive switches, emphasizing the reconfigurable memory effect in multiferroic YMO thin films with metallically conducting electrodes and their pivotal role in achieving adaptable frequency responses in impedance circuits consisting of reconfigurable YMO-based resistive switches and no reconfigurable passive elements, e.g., inductors and capacitors. The multiferroic YMO possesses a network of charged domain walls which can be reconfigured by a time-dependent voltage applied between the metallically conducting electrodes. Through experimental demonstrations, this study scrutinizes the impedance response not only for individual switch devices but also for impedance circuitry based on YMO resistive switches in both low- and high-resistance states, interfacing with capacitors and inductors in parallel and series configurations. Scrutinized Nyquist plots visually capture the intricate dynamics of impedance circuitry, revealing the potential of electroforming-free YMO resistive switches in finely tuning frequency responses within impedance circuits. This adaptability, rooted in the unique properties of YMO, signifies a paradigm shift heralding the advent of advanced and flexible electronic technologies.

Review on Resistive Switching Devices Based on Multiferroic BiFeO3.

This review provides a comprehensive examination of the state-of-the-art research on resistive switching (RS) in BiFeO3 (BFO)-based memristive devices. By exploring possible fabrication techniques for preparing the functional BFO layers in memristive devices, the constructed lattice systems and corresponding crystal types responsible for RS behaviors in BFO-based memristive devices are analyzed. The physical mechanisms underlying RS in BFO-based memristive devices, i.e., ferroelectricity and valence change memory, are thoroughly reviewed, and the impact of various effects such as the doping effect, especially in the BFO layer, is evaluated. Finally, this review provides the applications of BFO devices and discusses the valid criteria for evaluating the energy consumption in RS and potential optimization techniques for memristive devices.

Physics inspired compact modelling of [Formula: see text] based memristors.

With the advent of the Internet of Things, nanoelectronic devices or memristors have been the subject of significant interest for use as new hardware security primitives. Among the several available memristors, BiFe[Formula: see text] (BFO)-based electroforming-free memristors have attracted considerable attention due to their excellent properties, such as long retention time, self-rectification, intrinsic stochasticity, and fast switching. They have been actively investigated for use in physical unclonable function (PUF) key storage modules, artificial synapses in neural networks, nonvolatile resistive switches, and reconfigurable logic applications. In this work, we present a physics-inspired 1D compact model of a BFO memristor to understand its implementation for such applications (mainly PUFs) and perform circuit simulations. The resistive switching based on electric field-driven vacancy migration and intrinsic stochastic behaviour of the BFO memristor are modelled using the cloud-in-a-cell scheme. The experimental current-voltage characteristics of the BFO memristor are successfully reproduced. The response of the BFO memristor to changes in electrical properties, environmental properties (such as temperature) and stress are analyzed and consistant with experimental results.

Synaptic Plasticity in Memristive Artificial Synapses and Their Robustness Against Noisy Inputs.

Emerging brain-inspired neuromorphic computing paradigms require devices that can emulate the complete functionality of biological synapses upon different neuronal activities in order to process big data flows in an efficient and cognitive manner while being robust against any noisy input. The memristive device has been proposed as a promising candidate for emulating artificial synapses due to their complex multilevel and dynamical plastic behaviors. In this work, we exploit ultrastable analog BiFeO3 (BFO)-based memristive devices for experimentally demonstrating that BFO artificial synapses support various long-term plastic functions, i.e., spike timing-dependent plasticity (STDP), cycle number-dependent plasticity (CNDP), and spiking rate-dependent plasticity (SRDP). The study on the impact of electrical stimuli in terms of pulse width and amplitude on STDP behaviors shows that their learning windows possess a wide range of timescale configurability, which can be a function of applied waveform. Moreover, beyond SRDP, the systematical and comparative study on generalized frequency-dependent plasticity (FDP) is carried out, which reveals for the first time that the ratio modulation between pulse width and pulse interval time within one spike cycle can result in both synaptic potentiation and depression effect within the same firing frequency. The impact of intrinsic neuronal noise on the STDP function of a single BFO artificial synapse can be neglected because thermal noise is two orders of magnitude smaller than the writing voltage and because the cycle-to-cycle variation of the current-voltage characteristics of a single BFO artificial synapses is small. However, extrinsic voltage fluctuations, e.g., in neural networks, cause a noisy input into the artificial synapses of the neural network. Here, the impact of extrinsic neuronal noise on the STDP function of a single BFO artificial synapse is analyzed in order to understand the robustness of plastic behavior in memristive artificial synapses against extrinsic noisy input.

Detecting Bacterial Cell Viability in Few µL Solutions from Impedance Measurements on Silicon-Based Biochips.

Using two different types of impedance biochips (PS5 and BS5) with ring top electrodes, a distinct change of measured impedance has been detected after adding 1-5 µL (with dead or live Gram-positive Lysinibacillus sphaericus JG-A12 cells to 20 µL DI water inside the ring top electrode. We relate observed change of measured impedance to change of membrane potential of L. sphaericus JG-A12 cells. In contrast to impedance measurements, optical density (OD) measurements cannot be used to distinguish between dead and live cells. Dead L. sphaericus JG-A12 cells have been obtained by adding 0.02 mg/mL of the antibiotics tetracycline and 0.1 mg/mL chloramphenicol to a batch with OD0.5 and by incubation for 24 h, 30 °C, 120 rpm in the dark. For impedance measurements, we have used batches with a cell density of 25.5 × 108 cells/mL (OD8.5) and 270.0 × 108 cells/mL (OD90.0). The impedance biochip PS5 can be used to detect the more resistive and less capacitive live L. sphaericus JG-A12 cells. Also, the impedance biochip BS5 can be used to detect the less resistive and more capacitive dead L. sphaericus JG-A12 cells. An outlook on the application of the impedance biochips for high-throughput drug screening, e.g., against multi-drug-resistant Gram-positive bacteria, is given.

Towards Bacteria Counting in DI Water of Several Microliters or Growing Suspension Using Impedance Biochips.

We counted bacterial cells of E. coli strain K12 in several-microliter DI water or in several-microliter PBS in the low optical density (OD) range (OD = 0.05-1.08) in contact with the surface of Si-based impedance biochips with ring electrodes by impedance measurements. The multiparameter fit of the impedance data allowed calibration of the impedance data with the concentration cb of the E. coli cells in the range of cb = 0.06 to 1.26 × 109 cells/mL. The results showed that for E. coli in DI water and in PBS, the modelled impedance parameters depend linearly on the concentration of cells in the range of cb = 0.06 to 1.26 × 109 cells/mL, whereas the OD, which was independently measured with a spectrophotometer, was only linearly dependent on the concentration of the E. coli cells in the range of cb = 0.06 to 0.50 × 109 cells/mL.