@article{Li2025, 
author = {Jiayi Li and Yuxi Guo and Xin Ju and Diing Shenp Ang},
title = {Hyperpolarizing photoreceptor inspired biomimetic energy-saving sensor for dynamic machine vision},
year = {2025},
journal = {Nano Research},
volume = {18},
number = {1},
pages = {94907057},
keywords = {negative photoconductivity, retinomorphic sensor, optronic neuron, artificial photoreceptor, edge AI},
url = {https://www.sciopen.com/article/10.26599/NR.2025.94907057},
doi = {10.26599/NR.2025.94907057},
abstract = {Vision systems in vertebrates have evolved energy-efficient and adaptable features in hyperpolarizing photoreceptors that machine vision struggles to mimic. Because semiconducting materials always exhibit a photoconductive effect, attempts to mimic hyperpolarizing photoreceptors have proven to be non-trivial. Sophisticated two-dimensional (2D) material based van der Waals heterostructures and other novel structures/materials pose fabrication and integration challenges. This work aims to address the issue by successfully harnessing the defect dynamics in a ubiquitous transition metal oxide (TMO) hafnia to present, for the first time, a photosensor with characteristics closely resembling those of hyperpolarizing photoreceptors, including on-the-fly adaptation to constant and changing illumination, all in just a single ultrathin (5 nm) layer. This work opens a new prospect for accelerating the development of biomimetic vision systems, given the integral role TMOs have already played in mainstream semiconductor technology.}
}