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SYBT: Symposium Beyond Transistors: Material-Based Edge Computing Paradigms

SYBT 1: Beyond Transistors: Material-Based Edge Computing Paradigms

SYBT 1.2: Hauptvortrag

Mittwoch, 11. März 2026, 10:00–10:30, HSZ/AUDI

Accelerating Neural Networks Computation with Ferroelectric Oxides — •Laura Bégon-Lours, Nikhil Garg, Alexandre Baigol, Anwesha Panda, Nathan Savoia, and Alexander Flasby — Integrated Systems Laboratory, D-ITET, ETH Zürich

On conventional computers, the performance of AI models is limited by the data transfer between the memory and the processor. Compute-in-Memory architectures offer a new paradigm: Vector-Matrix Multiplications may be performed by a voltage drop through a matrix of programmable resistances, the *synaptic weights*. Ferroelectric materials are excellent candidates for their realization: the conductance is programmed by controlling the configuration of the ferroelectric domains. The mechanisms governing the resistive switching in WOx / HZO-SL (5 nm) bilayers are discussed. The effect of the programming pulse duration and amplitude on the polarization switching are investigated, from milliseconds to nanoseconds timescales. Devices of different sizes and shapes are measured down to 500 nm in dimension. For an device size of 1 micrometer square, an On/Off ratio as high as 4 is obtained for 20 ns pulses, a 4-fold improvement compared to 40 um devices. The relatively low crystallization temperature of polycrystalline hafnium oxide / zirconium oxide superlattices (HZO-SL) is compatible with the Back-End-Of-Line (BEOL) of CMOS transistors. These results not only demonstrate the functionalization of the BEOL with synaptic weights, but also pave the way for the integration of ferroelectric field-effect transistors with Beyond CMOS semiconductors.

Keywords: Ferroelectric Hafnium Oxide; Artificial Synapses; Nanofabrication; Integrated Circuits; Oxide thin-films