During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data‐processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain‐like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon‐based circuits. However, so far, a single‐component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two‐terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow‐gap Mott insulators subject to electric pulsing.

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Progress of silicon-based technology is nearing its physical limit, as the minimum feature size of components is reaching a mere 10 nm. The resistive switching behavior of transition metal oxides and the associated memristor device is emerging as a competitive technology for next-generation electronics. Significant progress has already been made in the past decade, and devices are beginning to hit the market; however, this progress has mainly been the result of empirical trial and error. Hence, gaining theoretical insight is of the essence. In the present work, we report the striking result of a connection between the resistive switching and shock-wave formation, a classic topic of nonlinear dynamics. We argue that the profile of oxygen vacancies that migrate during the commutation forms a shock wave that propagates through a highly resistive region of the device. We validate the scenario by means of model simulations and experiments in a manganese-oxide-based memristor device, and we extend our theory to the case of binary oxides. The shock-wave scenario brings unprecedented physical insight and enables us to rationalize the process of oxygen-vacancy-driven resistive change with direct implications for a key technological aspect-the commutation speed. DOI: 10.1103/PhysRevX.6.011028 Subject Areas: Condensed Matter Physics, Materials Science, Nonlinear DynamicsThe information age we live in is made possible by a physical underlayer of electronic hardware, which originates in condensed-matter physics research. Despite the great progress made in recent decades, the demand for faster and power-efficient devices continues to grow. Thus, there is urgent need to identify novel materials and physical mechanisms for future electronic-device applications. In this context, transition metal oxides (TMOs) are attracting much attention for nonvolatile memory applications [1]. In particular, TMO are associated with the phenomenon of resistive switching (RS) [2] and the memristor device [3], which is emerging as a competitive technology for nextgeneration electronics [1,[4][5][6][7][8][9][10]. The RS effect is a large, rapid, nonvolatile, reversible change of the resistance, which may be used to encode logic information. In the simplest case, one may associate high and low resistance values to binary states, but multibit memory cells are also possible [11,12].Typical systems where RS is observed are two-terminal capacitor-like devices, where the dielectric might be a TMO and the electrodes are ordinary metals. The phenomenon occurs in a strikingly large variety of systemsranging from simple binary compounds, such as NiO, TiO 2 , ZnO, Ta 2 O 5 , HfO 2 , and CuO, to more complex perovskite structures, such as superconducting cuprates and colossal magnetoresistive manganites [2,4,6,9,13].From a conceptual point of view, the main challenges for a nonvolatile memory are as follows: (i) to change its resistance within nano seconds (required for modern electronics applications), (ii) to be able to retain the state for years (i.e., n...

Bipolar resistive switching in low cost n-Si/La2/3Ca1/3MnO3/M (M = Ti + Cu) devices was investigated. For low SET compliance currents (CC), an interfacial-related resistive switching mechanism, associated to the migration of oxygen vacancies close to the manganite/metal interface, is operative. Simulations using the voltage enhanced oxygen vacancies drift model validate our experimental results. When further increasing the CC, we have observed the onset of a second, filamentary, resistive switching regime with a concomitant collapse of the ON/OFF ratio. We finally demonstrate that it is possible to delay the onset of the filamentary regime by controlling the film thickness.

We consider the phenomenon of electric Mott transition (EMT), which is an electric induced insulator to metal transition. Experimentally, it is observed that depending on the magnitude of the electric excitation the final state may show a short lived or a long lived resistance change. We extend a previous model for the EMT to include the effect of local structural distortions through an elastic energy term. We find that by strong electric pulsing the induced metastable phase may become further stabilized by the electro-elastic effect. We present a systematic study of the model by numerical simulations and compare the results to new experiments in Mott insulators of the AM4Q8 family. Our work significantly extends the scope of our recently introduced leaky-integrateand-fire Mott-neuron [P. Stoliar Adv Mat 2017] to bring new insight on the physical mechanism of its relaxation. This is a key feature for future neuromorphic circuit implementations. arXiv:1711.05206v1 [cond-mat.mtrl-sci]