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Weebit Nano and Leti File Two Patents

Optimizing ReRAM performance

Weebit Nano, Ltd. seeking to develop and commercialise the next gen of memory technology, and its development partner Leti, the French research institute recognised as a global leader in the field of micro-electron, have filed two patents for the company’s Silicon Oxide (SiOx) ReRAM technology.

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These patents relate to methods for optimising the performance of ReRAM memory cells by adjusting the manufacturability based on electrical measurements. One patent outlines a general methodology used to achieve the highest electrical performance of ReRAM cells while the other is the specification of that methodology. Identifying the unique SiOx device specification and manufacturing method enhances the commercial viability of the firm’s technology, and therefore reduces manufacturing costs and allows for more flexible manufacturing capability.

Coby Hanoch, CEO, Weebit Nano, said: “As we move closer to productisation, we are constantly looking for ways to optimise our SiOx ReRAM technology. Our close collaboration with Leti has enabled us to make significant progress and technological breakthroughs, such as the ones covered by these two patents. The precise specification of the optimisation process allows us to push the boundaries of ReRAM technology even further and places us at the forefront of the ReRAM industry.

While we continue to work on optimising parameters of Weebit’s ReRAM technology and responding to feedback from potential customers, the latest advancement enhances our manufacturing process and capability ahead of the move to a production fab.

Read also:
Weebit Nano Achieves Results at Forefront of ReRAM Market
Tests conducted by French research institute Leti
May 10, 2019 | Press Release
Weebit Nano 3FQ19 Activities Update
Achieves technical parameters, moves closer to production fab transfer, builds commercial and research partnerships.
May 7, 2019 | Press Release
Weebit Nano and Leti Build Neuromorphic Demonstrator Using SiOx ReRAM Technology
System will be based on Spiking Neural Network (SNN) test vehicle for implementing synapses, which will showcase capabilities of technology by performing precise object recognition tasks in energy-efficient manner.
March 8, 2019 | Press Release

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