CMOS‐Compatible LiNbO <sub>3</sub> Domain‐Wall Entropy Engine for Ultrafast True Random Number Generation

H Haiyue Tang (College of Integrated Circuits and Micro/Nano Electronics Innovation, Fudan University , Shanghai 200433,) Z Zilong Wang X Xinglong Wang X Xianyu Hu (State Key Laboratory of Integrated Chips and Systems, College of Integrated Circuits and Micro‐Nano Electronics Fudan University Shanghai China) D Di Hu (Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina) Q Qianwei Huang (Institute of Energy Materials Science) W Wendi Zhang A Anquan Jiang (College of Integrated Circuits and Micro‐Nano Electronics Innovation Fudan University Shanghai 200433 China)

Abstract

Abstract Random ferroelectric domain nucleation and growth lead to the generation of numerous unpredictable microscopic states that collectively form a natural high‐entropy system. Conventional electrical methods can directly measure reversible domain switching currents, offering a viable platform for true random number generation (TRNG). However, TRNG based on random ferroelectric switching events is limited by the noise amplitudes in electrical signals. In this study, TRNG is realized via the stochastic formation of conductive domain walls in single‐crystal LiNbO 3 thin films bonded to SiO 2 /Si wafers. This approach achieves a noise amplitude and cycling endurance &gt;500 nA and &gt;10 10 , respectively. The interfacial‐layer‐based device exhibits self‐reinitialized stochastic sub‐10‐ns domain switching operations, enabling ultrafast generation of bit outputs and flexible device scaling. The generated random bitstreams, validated via National Institute of Standards and Technology (NIST)tests, exhibit robust resistance against machine‐learning‐based predictive attacks. This pioneering study establishes ferroelectric conductive domain walls as groundbreaking platforms for CMOS‐compatible entropy source extraction, effectively addressing the long‐standing challenges in amplifying entropy signals with operational robustness.

Article Details

Volume / Issue Vol. 38, Issue 4
Published January 01, 2026
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (8)

H

Haiyue Tang

College of Integrated Circuits and Micro/Nano Electronics Innovation, Fudan University , Shanghai 200433,

Z

Zilong Wang

X

Xinglong Wang

X

Xianyu Hu

State Key Laboratory of Integrated Chips and Systems, College of Integrated Circuits and Micro‐Nano Electronics Fudan University Shanghai China

D

Di Hu

Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina

Q

Qianwei Huang

Institute of Energy Materials Science

W

Wendi Zhang

A

Anquan Jiang

College of Integrated Circuits and Micro‐Nano Electronics Innovation Fudan University Shanghai 200433 China