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HZO-based FerroNEMS MAC for In-Memory Computing

Applied Physics 2022-11-23 v1 Hardware Architecture

Abstract

This paper demonstrates a hafnium zirconium oxide (HZO)-based ferroelectric NEMS unimorph as the fundamental building block for very low-energy capacitive readout in-memory computing. The reported device consists of a 250 μ\mum ×\times 30 μ\mum unimorph cantilever with 20 nm thick ferroelectric HZO on 1 μ\mum SiO2SiO_2.Partial ferroelectric switching in HZO achieves analog programmable control of the piezoelectric coefficient (d31d_{31}) which serves as the computational weight for multiply-accumulate (MAC) operations. The displacement of the piezoelectric unimorph was recorded by actuating the device with different input voltages VinV_{in}. The resulting displacement was measured as a function of the ferroelectric programming/poling voltage VpV_p. The slopes of central beam displacement (δmax\delta_{max}) vs VinV_{in} were measured to be between 182.9nm/V (for -8 VpV_p) and -90.5nm/V (for 8 VpV_p), demonstrating that VpV_p can be used to change the direction of motion of the beam. The resultant (δmax\delta_{max}) from AC actuation is in the range of -18 to 36 nm and is a scaled product of the input voltage and programmed d31d_{31} (governed by the VpV_p). The multiplication function serves as the fundamental unit for MAC operations with the ferroelectric NEMS unimorph. The displacement from many such beams can be added by summing the capacitance changes, providing a pathway to implement a multi-input and multi-weight neuron. A scaling and fabrication analysis suggests that this device can be CMOS compatible, achieving high in-memory computational throughput.

Keywords

Cite

@article{arxiv.2208.06499,
  title  = {HZO-based FerroNEMS MAC for In-Memory Computing},
  author = {Shubham Jadhav and Ved Gund and Benyamin Davaji and Debdeep Jena and Huili and Xing and Amit Lal},
  journal= {arXiv preprint arXiv:2208.06499},
  year   = {2022}
}
R2 v1 2026-06-25T01:40:39.138Z