Authors: He Wang, Zeyu Guan, Jiachen Li, Zhen Luo, Xinzhe Du, Zijian Wang, Haoyu Zhao, Shengchun Shen, Yuewei Yin, Xiaoguang Li
Published: 2024-01-31
Source: Full article
AbstractThe big data era requires ultrafast, low‐power, and silicon‐compatible materials and devices for information storage and processing. Here, ferroelectric tunnel junctions (FTJs) based on SiO2/Hf0.5Zr0.5O2composite barrier and both conducting electrodes are designed and fabricated on Si substrates. The FTJ achieves the fastest write speed of 500 ps under 5 V (2 orders of magnitude faster than reported silicon‐compatible FTJs) or 10 ns speed at a low voltage of 1.5 V (the lowest voltage among FTJs at similar speeds), low write current density of 1.3 × 104A cm−2, 8 discrete states, good retention > 105s at 85 °C, and endurance > 107. In addition, it provides a large read current (88 A cm−2) at 0.1 V, 2 orders of magnitude larger than reported FTJs. Interestingly, in FTJ‐based synapses, gradually tunable conductance states (128 states) with high linearity (<1) are obtained by 10 ns pulses of <1.2 V, and a high accuracy of 91.8% in recognizing fashion product images is achieved by online neural network simulations. These results highlight that silicon‐compatible HfO2‐based FTJs are promising for high‐performance nonvolatile memories and electrical synapses.