Dendritic Computing with Multigate Ferroelectric Field-Effect Transistors

Islam, A. N. M. Nafiul; Niu, Xuezhong; Duan, Jiahui; Kumar, Shubham; Ni, Kai; Sengupta, Abhronil

doi:10.1021/acs.nanolett.5c03241

Dendritic Computing with Multigate Ferroelectric Field-Effect Transistors

Journal Article · Mon Oct 27 00:00:00 EDT 2025 · Nano Letters

DOI:https://doi.org/10.1021/acs.nanolett.5c03241· OSTI ID:3000228

Islam, A. N. M. Nafiul ^[1]; Niu, Xuezhong ^[2]; Duan, Jiahui ^[2]; Kumar, Shubham ^[2]; Ni, Kai ^[2]; ^[1]

Pennsylvania State Univ., University Park, PA (United States)
University of Notre Dame, IN (United States)

Although inspired by neuronal systems in the brain, artificial neural networks generally employ point-neurons, which offer computational complexity far less than that of their biological counterparts. Neurons have dendritic arbors that connect to different sets of synapses and offer local nonlinear accumulation – playing a pivotal role in processing and learning. Inspired by this, we propose a novel neuron design based on a multigate ferroelectric field-effect transistor that mimics dendrites. It leverages ferroelectric nonlinearity for local computations within dendritic branches while utilizing the transistor action to generate the neuronal output. The branched architecture enables smaller crossbar arrays in hardware integration, improving efficiency. Using an experimentally calibrated device-circuit-algorithm cosimulation framework, we demonstrate that networks incorporating our dendritic neurons achieve superior performance compared to much larger networks without dendrites (∼ 17× fewer trainable weight parameters). These findings suggest that dendritic hardware can significantly improve computational efficiency and learning capacity of neuromorphic systems optimized for edge applications.

View Accepted Manuscript (DOE)

Research Organization:: Pennsylvania State Univ., University Park, PA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: SC0021118

OSTI ID:: 3000228

Journal Information:: Nano Letters, Journal Name: Nano Letters; ISSN 1530-6992; ISSN 1530-6984

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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