RESUMO
Emerging nanoionic memristive devices are considered as the memory technology of the future and have been winning a great deal of attention due to their ability to perform fast and at the expense of low-power and -space requirements. Their full potential is envisioned that can be fulfilled through their capacity to store multiple memory states per cell, which however has been constrained so far by issues affecting the long-term stability of independent states. Here, we introduce and evaluate a multitude of metal-oxide bi-layers and demonstrate the benefits from increased memory stability via multibit memory operation. We propose a programming methodology that allows for operating metal-oxide memristive devices as multibit memory elements with highly packed yet clearly discernible memory states. These states were found to correlate with the transport properties of the introduced barrier layers. We are demonstrating memory cells with up to 6.5 bits of information storage as well as excellent retention and power consumption performance. This paves the way for neuromorphic and non-volatile memory applications.
RESUMO
Pt/TiO x /Pt resistive switching (RS) devices are considered to be amongst the most promising candidates in memristor family and the technology transfer to flexible substrates could open the way to new opportunities for flexible memory implementations. Hence, an important goal is to achieve a fully flexible RS memory technology. Nonetheless, several fabrication challenges are present and must be solved prior to achieving reliable device fabrication and good electronic performances. Here, we propose a fabrication method for the successful transfer of Pt/TiO x /Pt stack onto flexible Parylene-C substrates. The devices were electrically characterised, exhibiting both digital and analogue memory characteristics, which are obtained by proper adjustment of pulsing schemes during tests. This approach could open new application possibilities of these devices in neuromorphic computing, data processing, implantable sensors and bio-compatible neural interfaces.