Rectennas at optical frequencies: How to analyze the response

Optical rectennas, antenna-coupled diode rectifiers that receive optical-frequency electromagnetic radiation and convert it to DC output, have been proposed for use in harvesting electromagnetic radiation from a blackbody source. The operation of these devices is qualitatively different from that of lower-frequency rectennas, and their design requires a new approach. To that end, we present a method to determine the rectenna response to high frequency illumination. It combines classical circuit analysis with classical and quantum-based photon-assisted tunneling response of a high-speed diode. We demonstrate the method by calculating the rectenna response for low and high frequency monochromatic illumination, and for radiation from a blackbody source. Such a blackbody source can be a hot body generating waste heat, or radiation from the sun

A novel true random number generator based on a stochastic diffusive memristor

The intrinsic variability of switching behavior in memristors has been a major obstacle to their adoption as the next generation universal memory. On the other hand, this natural stochasticity can be valuable for hardware security applications. Here we propose and demonstrate a novel true random number generator (TRNG) utilizing the stochastic delay time of threshold switching in a Ag:SiO2 diffusive memristor, which exhibits evident advantages in scalability, circuit complexity and power consumption. The random bits generated by the diffusive memristor TRNG passed all 15 NIST randomness tests without any post-processing, a first for memristive-switching TRNGs. Based on nanoparticle dynamic simulation and analytical estimates, we attributed the stochasticity in delay time to the probabilistic process by which Ag particles detach from a Ag reservoir. This work paves the way for memristors in hardware security applications for the era of Internet of Things (IoT)

Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing

The accumulation and extrusion of Ca2+ in the pre- and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy minimization, closely resembling synaptic influx and extrusion of Ca2+, respectively. The diffusive memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses and represent a major advancement in hardware implementation of neuromorphic functionalities

Anatomy of Ag/Hafnia‐Based Selectors with 1010 Nonlinearity

Sneak path current is a significant remaining obstacle to the utilization of large crossbar arrays for non-volatile memories and other applications of memristors. A two-terminal selector device with an extremely large current-voltage nonlinearity and low leakage current could solve this problem. We present here a Ag/oxide-based threshold switching (TS) device with attractive features such as high current-voltage nonlinearity (~1010 ), steep turn-on slope (less than 1 mV/dec), low OFF-state leakage current (~10-14 A), fast turn ON/OFF speeds (108 cycles). The feasibility of using this selector with a typical memristor has been demonstrated by physically integrating them into a multilayered 1S1R cell. Structural analysis of the nanoscale crosspoint device suggests that elongation of a Ag nanoparticle under voltage bias followed by spontaneous reformation of a more spherical shape after power off is responsible for the observed threshold switching of the device. Such mechanism has been quantitatively verified by the Ag nanoparticle dynamics simulation based on thermal diffusion assisted by bipolar electrode effect and interfacial energy minimization

Performance limits of optical rectennas

Optical rectennas are antenna-coupled diode rectifiers that receive and convert optical-frequency electromagnetic radiation into DC output. Because classical rectennas working at microwave frequencies can achieve very high rectification efficiencies, rectennas working as solar cells were expected to have efficiencies significantly higher than conventional solar cells. By applying the theory of photon-assisted tunneling (PAT) to optical rectennas at solar intensities, I show that the power conversion efficiency of rectenna solar cells is fundamentally limited to the Trivich-Flinn efficiency limit of 44%. This unexpected result is the same as the Shockley-Queisser ultimate efficiency limit of conventional solar cells. Is it possible to exceed this efficiency limit? I answer this question by showing that there is a correspondence between the quantum and classical operation of a rectenna. Such correspondence allows high frequency rectennas to operate in the same way as classical rectennas, and to potentially exceed the Trivich-Flinn efficiency limit. I propose two ways to achieve classical operation in optical rectennas. Diode design is crucial for achieving high rectification efficiency. High-speed diodes, such as metal-insulator-metal (MIM) diodes, have insufficient asymmetry for harvesting low intensity radiation. I suggest steps to improve the characteristics of double insulator MIM diodes and calculate their power conversion efficiency using PAT theory. A simple figure of merit is provided to quickly assess the usefulness of MIM diodes in optical rectennas. Although ineffective at visible frequencies, MIM diodes have RC time constants sufficient for operation at low terahertz frequencies, useful in applications including detection and high-speed electronics. I develop the steps to design MIM diodes at 1 THz, propose materials that will give the required current-voltage characteristics and RC time constant, perform electrical and optical measurements on fabricated devices, and suggest steps to improve their performance. In contrast to MIM diodes, novel planar devices called geometric diodes have very low RC time constants and are capable of rectifying radiation up to 100 THz. I measure the infrared optical response of graphene-based geometric diodes, and demonstrate one of the best room-temperature detectors working at 28 THz

Fully memristive neural networks for pattern classification with unsupervised learning

Neuromorphic computers comprised of artificial neurons and synapses could provide a more efficient approach to implementing neural network algorithms than traditional hardware. Recently, artificial neurons based on memristors have been developed, but with limited bio-realistic dynamics and no direct interaction with the artificial synapses in an integrated network. Here we show that a diffusive memristor based on silver nanoparticles in a dielectric film can be used to create an artificial neuron with stochastic leaky integrate-and-fire dynamics and tunable integration time, which is determined by silver migration alone or its interaction with circuit capacitance. We integrate these neurons with nonvolatile memristive synapses to build fully memristive artificial neural networks. With these integrated networks, we experimentally demonstrate unsupervised synaptic weight updating and pattern classification