Neuromorphic object localization using resistive memories and ultrasonic transducers.

Real-world sensory-processing applications require compact, low-latency, and low-power computing systems. Enabled by their in-memory event-driven computing abilities, hybrid memristive-Complementary Metal-Oxide Semiconductor neuromorphic architectures provide an ideal hardware substrate for such tasks. To demonstrate the full potential of such systems, we propose and experimentally demonstrate an end-to-end sensory processing solution for a real-world object localization application. Drawing inspiration from the barn owl's neuroanatomy, we developed a bio-inspired, event-driven object localization system that couples state-of-the-art piezoelectric micromachined ultrasound transducer sensors to a neuromorphic resistive memories-based computational map. We present measurement results from the fabricated system comprising resistive memories-based coincidence detectors, delay line circuits, and a full-custom ultrasound sensor. We use these experimental results to calibrate our system-level simulations. These simulations are then used to estimate the angular resolution and energy efficiency of the object localization model. The results reveal the potential of our approach, evaluated in orders of magnitude greater energy efficiency than a microcontroller performing the same task.

Macroscopic and microscopic picture of negative capacitance operation in ferroelectric capacitors.

The negative capacitance (NC) operation of ferroelectric materials has been originally proposed based on a homogeneous Landau theory, leading to a simple NC stabilization condition expressed in terms of macroscopic quantities. A multi-domain theory, however, has pointed out the importance of microscopic parameters, such as the domain wall energy coupling constant, and it helped explain the somewhat contradicting experiments for ferroelectric capacitors with or without a metal interlayer. In this work we use comprehensive numerical simulations and simplified equations to correlate the macroscopic features of the NC operation to the underlying microscopic picture. We show that, while the domain wall coupling constant plays a critical role in a quasi static operation, the transient NC operation is less sensitive to this parameter. In particular, ferroelectric capacitors with a very small coupling constant can still display a robust transient NC behavior, closely tracking the 'S'-shaped polarization versus field curve and with negligible hysteresis. Our results have been developed in the framework of a systematic comparison between simulations and experiments, and they provide both a better understanding of the NC operation and a sound basis for the design of future NC based devices.

Piezoresistive Properties of Suspended Graphene Membranes under Uniaxial and Biaxial Strain in Nanoelectromechanical Pressure Sensors.

Graphene membranes act as highly sensitive transducers in nanoelectromechanical devices due to their ultimate thinness. Previously, the piezoresistive effect has been experimentally verified in graphene using uniaxial strain in graphene. Here, we report experimental and theoretical data on the uni- and biaxial piezoresistive properties of suspended graphene membranes applied to piezoresistive pressure sensors. A detailed model that utilizes a linearized Boltzman transport equation describes accurately the charge-carrier density and mobility in strained graphene and, hence, the gauge factor. The gauge factor is found to be practically independent of the doping concentration and crystallographic orientation of the graphene films. These investigations provide deeper insight into the piezoresistive behavior of graphene membranes.