The missing applications found: Robust design techniques and novel uses of memristors

Resistive memory, also known as memristor, is an emerging potential successor to traditional CMOS charge based memories. Memristors have also recently been proposed as a promising candidate for several additional applications such as logic design, sensing, non-volatile storage, neuromorphic computing, Physically Unclonable Functions (PUFs), Content­addressable memory (CAM) and reconfigurable computing. In this paper, we explore three unique applications of memris­tor technology based implementations, specifically from the perspective of sensing, logic, in-memory computing and their solutions. We review solar cell health monitoring and diagnosis, describe the proposed solutions, and provide directions in memristive gas sensing and in-memory computing. For the gas sensor application, in order to determine the number of memristors to ensure a certain level of accuracy in sen­sitivity, a technique to optimize the sensor array based on an acceptable sensitivity variation and minimum sensitivity margin is presented. These "out-of-the-box" emerging ideas for applications of memristive devices in enhancing robustness and, at the same time, how the requirements of robust design are enabling unconventional use of the devices. To this end, the papers considers some examples of this mutual interaction

Microscopy Conference 2017 (MC 2017) - Proceedings

Das Dokument enthält die Kurzfassungen der Beiträge aller Teilnehmer an der Mikroskopiekonferenz "MC 2017", die vom 21. bis 25.08.2017, in Lausanne stattfand

Fault detection and repair of DSC arrays through memristor sensing

Fault tolerant Photovoltaic array used for green energy systems is emerging as an important area of study because of growing emphasis on reliable design. Among various photovoltaic cells Dye Solar Cell (DSC) is a promising low-cost photovoltaic (PV) technology and high energy-conversion efficiency. Recently it has been shown that it has memristive behavior as well. To efficiently support this claim, in this paper we use experimental data to characterize DSC cell and show that it exhibits memristor state behavior and developed a SPICE model. We use memristive DSC cells as sensing devices. This enables us to identify faulty cells in regular DSC. First, we present the model from the experimental data. A search algorithm is defined to identify the faulty components of the DSC array that fulfill the first requirement of a fault tolerant design. The proposed diagnosis method utilizes recently proposed fault detection solution for efficient testing of PV cells in the presence of faults. We divide the array into segments such that any faults is detectable thereby achieving high diagnosis accuracy. The proposed diagnosis method has been validated through SPICE simulation. Spare cells are to repair the faulty array