TY - JOUR
T1 - Antiferroelectric polarization enabling physical activation in CuBiP2Se6 for medical image processing
AU - Lin, Yinan
AU - Yang, Dongliang
AU - Wang, Zhongyi
AU - Zhen, Weili
AU - Yu, Tianze
AU - Xue, Fei
AU - Wei, Hongtao
AU - Sun, Linfeng
N1 - Publisher Copyright:
© 2026. The Author(s).
PY - 2026/4/3
Y1 - 2026/4/3
N2 - Antiferroelectric materials, featuring field controllable antipolar ordering and reversible polarization switching, offer a promising platform for hardware efficient neuromorphic computing. The tunable polarization dynamics and layered van der Waals structure enable the multifunctional integration of sensing, learning, and computation within a single device architecture. Here, we demonstrate an antiferroelectric polarization driven diode exhibiting an extended linear operating region, which simultaneously enables physical activation and computing-in-memory. Building on the device capability, we construct an in-sensor computing system that achieves over 95% accuracy in medical image classification. We further integrate the devices to demonstrate a hardware-based activation function, attaining accuracy and training loss comparable to an ideal activation function. To enhance adaptability, we further propose a tunable activation circuit that enables linear modulation of the reverse bias slope via gain control. Overall, this work establishes a dual-functional antiferroelectric heterojunction, highlighting its strong potential for constructing optically triggered, compact, and low-power perception-computation-integrated neuromorphic systems for medical image processing.
AB - Antiferroelectric materials, featuring field controllable antipolar ordering and reversible polarization switching, offer a promising platform for hardware efficient neuromorphic computing. The tunable polarization dynamics and layered van der Waals structure enable the multifunctional integration of sensing, learning, and computation within a single device architecture. Here, we demonstrate an antiferroelectric polarization driven diode exhibiting an extended linear operating region, which simultaneously enables physical activation and computing-in-memory. Building on the device capability, we construct an in-sensor computing system that achieves over 95% accuracy in medical image classification. We further integrate the devices to demonstrate a hardware-based activation function, attaining accuracy and training loss comparable to an ideal activation function. To enhance adaptability, we further propose a tunable activation circuit that enables linear modulation of the reverse bias slope via gain control. Overall, this work establishes a dual-functional antiferroelectric heterojunction, highlighting its strong potential for constructing optically triggered, compact, and low-power perception-computation-integrated neuromorphic systems for medical image processing.
UR - https://www.scopus.com/pages/publications/105040729139
U2 - 10.1038/s41467-026-70594-x
DO - 10.1038/s41467-026-70594-x
M3 - Article
C2 - 41927531
AN - SCOPUS:105040729139
SN - 2041-1723
VL - 17
JO - Nature Communications
JF - Nature Communications
IS - 1
ER -