Physics inspired compact modelling of $$\hbox {BiFeO}_3$$ based memristors

Abstract

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$$\mathrm{O}_{3}$$ O 3 (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.

Ferroelectric enhanced Ga2O3/BFMO-based deep ultraviolet photovoltaic detectors with dual electric fields for photogenerated carrier separation

“…Here, A** values of Ga 2 O 3 and BFMO were taken as 33.7 and 120.2 A cm À2 K À2 , respectively, following the literature. 30,31 For the single BFMO device, the fitted values of the parameters F B1 (n 1 ) and F B2 (n 2 ) were 0.80 eV (1.17) and 0.81 eV (1.13), respectively. F B1 was lower than F B2 in the single BFMO device, making the photogenerated electrons (holes) transfer from the FTO (Au) side to the Au (FTO) side [see Fig.…”

Enhancing memristor fundamentals through instrumental characterization and understanding reliability issues

“…Memristors typically exhibit undesirable variations in resistance values and SET and RESET voltages from one device to device (also called D2D or spatial variation) and from one cycle to cycle (also called C2C or temporal variation). 165,166 From the perspective of physical mechanism, the cycle-to-cycle variation originates from the stochastic formation and rupture of conductive filaments. 43 The device-to-device variation stems from the limitations of fabrication techniques, which produce nonideal film morphology and homogeneity, resulting in the different electrical characteristics between memristors.…”