Critical coupling in plasmonic chain for efficient energy trapping

Plasmonic nanoparticles can concentrate electromagnetic energy on the nanometer scale, offering promising applications in diverse fields such as miniaturized photonic circuits or lab-on-chip. An essential prerequisite for these applications is efficient coupling between the nanoparticles and the excitation signal. Plasmonic nanoparticle chains are capable of guiding light on a sub-wavelength scale, and can be excited by being coupled to a dielectric waveguide. Here, a team from C2N proposes a …

A new AI memory capable of learning and deciding on-chip

A French team led by CEA-Leti, with participation from C2N and several other laboratories*, has developed a hybrid memory technology that allows artificial neural networks to learn and make decisions directly on-chip. The new system combines ferroelectric capacitors and memristors in a single CMOS-compatible stack. The memristors are suited for inference, while the FeCAPs enable precise updates for learning. The hybrid device switches between these modes, allowing efficient …