Xu Bingqian, Cai Yao, Wang Zekai, Xu Qinwen, Ren Yuqi, Chen Xiang, Hu Chenxi, Li Xiaohui, Shi Jianping, Sun Chengliang, Guo Shishang
Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, 430072, China.
The Institute of Technological Sciences, Hubei Key Laboratory of Electronic Manufacturing and Packaging Integration, Wuhan University, Wuhan, 430072, China.
Small Methods. 2025 Jun 19:e2500842. doi: 10.1002/smtd.202500842.
ScAlN is an emerging nitride ferroelectric material that exhibits exceptional remnant polarization (P) at ultrathin scales (<50 nm), stable single-phase ferroelectricity, and CMOS compatibility, making it highly promising for next-generation low-power, high-density memory and neuromorphic devices. However, ScAlN films deposited by conventional physical vapor deposition (PVD) faces challenges such as Sc precipitation and crystal orientation degradation at high Sc concentrations (>20%) and reduced thicknesses, leading to deteriorated ferroelectricity and increased leakage. In this work, it is demonstrated that an optimized substrate structure enables PVD-grown ScAlN films to achieve significantly enhanced ferroelectric properties compared to conventional substrates, retaining high P even at 20 nm thickness. This improvement is further validated with ScAlN and ScAlN films across varying thicknesses. Additionally, a ScAlN-based FeFET fabricated on this substrate exhibits a 17 V memory window, >10 switching ratio, >10 s retention, and >10 cycle endurance. When configured as an artificial synapse, the device achieves 98.7% recognition accuracy in neural network training under encoded pulse voltages, highlighting its potential for energy-efficient computing.