RRAM can be used for energy storage as well as memory says CEA-Leti

CEA-Leti has come up with a way to allow RRAM devices to operate as energy-storage elements as well as memory, depending on the applied bias. 

In-memory energy is a supplemental feature to in-memory computing which can reduce energy use because RRAM-based batteries are scalable and dynamically allocable, and can be placed next to memory blocks, which are near the processor.

Locating the energy supply close to the processor is especially helpful when the processor requires peak power, which typically comes from an external source.

This reduces power use over transmission lines, while improving power-delivery network (PDN) efficiency. The hybrid, dual-behavior device is compatible with CMOS fabrication processes.

The high energy-and-power densities are due to the fact that the RRAM devices in the study rely on faradaic processes to store information inside an active volume, enabling the extracted values (power-and-energy densities) to far exceed that of electrostatic capacitors, and which are comparable to micro-

In addition, the technology is more scalable: a cell size exhibits an area as low as 10mm2 without loss of energy-storage capability, whereas state-of-the-art supercapacitors are around 10-3mm2. That means the proposed devices are 10⁴ times more scalable than the smallest-footprint micro-supercapicitors.

The high energy scalability is allowed by the small physical scale of RRAM devices, which involve a sub-nanometer- thick partial filament to store the energy: typical device areas are in the range of [0.1-1]10-7mm2and are expected to scale down in the near future.

Projected applications for these energy-use-cutting, dual-behavior devices include energy-to-memory (NAND and NOR Flash), energy-to-logic (IoT processors) and neuromorphic uses (synaptic technology).