RESUMO
One of the main, long-term objectives of artificial intelligence is the creation of thinking machines. To that end, substantial effort has been placed into designing cognitive systems; i.e. systems that can manipulate semantic-level information. A substantial part of that effort is oriented towards designing the mathematical machinery underlying cognition in a way that is very efficiently implementable in hardware. In this work, we propose a 'semi-holographic' representation system that can be implemented in hardware using only multiplexing and addition operations, thus avoiding the need for expensive multiplication. The resulting architecture can be readily constructed by recycling standard microprocessor elements and is capable of performing two key mathematical operations frequently used in cognition, superposition and binding, within a budget of below 6 pJ for 64-bit operands. Our proposed 'cognitive processing unit' is intended as just one (albeit crucial) part of much larger cognitive systems where artificial neural networks of all kinds and associative memories work in concord to give rise to intelligence. This article is part of the theme issue 'Harmonizing energy-autonomous computing and intelligence'.
RESUMO
Resistive random access memory (RRAM) is considered an attractive candidate for next generation memory devices due to its competitive scalability, low-power operation and high switching speed. The technology however, still faces several challenges that overall prohibit its industrial translation, such as low yields, large switching variability and ultimately hard breakdown due to long-term operation or high-voltage biasing. The latter issue is of particular interest, because it ultimately leads to device failure. In this work, we have investigated the physicochemical changes that occur within RRAM devices as a consequence of soft and hard breakdown by combining full-field transmission x-ray microscopy with soft x-ray spectroscopic analysis performed on lamella samples. The high lateral resolution of this technique (down to 25 nm) allows the investigation of localized nanometric areas underneath permanent damage of the metal top electrode. Results show that devices after hard breakdown present discontinuity in the active layer, Pt inclusions and the formation of crystalline phases such as rutile, which indicates that the temperature increased locally up to 1000 K.
RESUMO
Reduction in metal-oxide thin films has been suggested as the key mechanism responsible for forming conductive phases within solid-state memory devices, enabling their resistive switching capacity. The quantitative spatial identification of such conductive regions is a daunting task, particularly for metal-oxides capable of exhibiting multiple phases as in the case of TiOx. Here, we spatially resolve and chemically characterize distinct TiOx phases in localized regions of a TiOx-based memristive device by combining full-field transmission X-ray microscopy with soft X-ray spectroscopic analysis that is performed on lamella samples. We particularly show that electrically pre-switched devices in low-resistive states comprise reduced disordered phases with O/Ti ratios around 1.37 that aggregate in a ~100 nm highly localized region electrically conducting the top and bottom electrodes of the devices. We have also identified crystalline rutile and orthorhombic-like TiO2 phases in the region adjacent to the main reduced area, suggesting that the temperature increases locally up to 1000 K, validating the role of Joule heating in resistive switching. Contrary to previous studies, our approach enables to simultaneously investigate morphological and chemical changes in a quantitative manner without incurring difficulties imposed by interpretation of electron diffraction patterns acquired via conventional electron microscopy techniques.
