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In several recent studies, the probabilistic nature of magnetic tunnel junction (MTJ) switching has been utilized rather than suppressed for proposals and demonstrations of specific or novel scenarios or applications, such as true random number generation, neural spike generation, stochastic computing (SC), and probabilistic spin logic. Among all schemes of operations for generating tunable random signals, dual-biasing is very simple but also robust against device variations. When an MTJ is connected to a voltage source with polarity encouraging parallel (P)-to-antiparallel (AP) switching by spin-transfer torque (STT), and under a static bias field that favors P-state, the MTJ can switch back and forth between two states randomly, due to the state-dependent modulation of current by the tunneling magnetoresistance (TMR) of the MTJ. In this work, we demonstrate bipolar random signal generation by connecting two MTJs in series with a voltage source. [ABSTRACT FROM AUTHOR]

New technologies are continuously investigated to overcome the physical limitations of the downscaling process of microelectronic industry in order to perpetuate the miniaturization of devices as well as to enhance their capabilities. Memories are important components of almost any modern system. Applications, such as portable devices for which magnetic storage is not viable, prompt the search for universal memories that combine writing and retention capabilities. In this context, materials and structures that exhibit resistive switching are of utmost importance for the development of nonvolatile memories. In this context, graphene oxide has emerged as a promising resistive medium in metal-insulator–metal memory structures, because of the low cost and easy processing. Despite the controversy on the switching mechanism, graphene oxide-based memristors have also been proposed as self-selective memory elements. Nonlinearity is a fundamental characteristic of any memristor. In this work, we explore the occurrence of switching in graphene oxide, even when weak nonlinearities are observed. Metal-graphene oxide-metal structures were subjected to voltage cycling by applying triangular inputs and measuring the current. The nonlinearities were quantified by harmonic analysis, using total harmonic distortion as a figure of merit. An increasing nonlinear behavior is observed as the condition for switching is built up for increasing input amplitudes. This parameter allows an earlier identification of the set process. The harmonic analysis helps to discriminate the nonlinear perturbation to the linear response and allowing modeling of the current-voltage curve. [ABSTRACT FROM AUTHOR]