Silicon-Compatible Ferroelectric Tunnel Junctions with a SiO 2 /Hf 0.5 Zr 0.5 O 2 Composite Barrier as Low-Voltage and Ultra-High-Speed Memristors.
He WangZeyu GuanJiachen LiZhen LuoXinzhe DuZijian WangHaoyu ZhaoShengchun ShenYue Wei YinXiaoguang LiPublished in: Advanced materials (Deerfield Beach, Fla.) (2024)
The 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 SiO 2 /Hf 0.5 Zr 0.5 O 2 composite 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 × 10 4 A cm -2 , 8 discrete states, good retention > 10 5 s at 85 °C, and endurance > 10 7 . 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 HfO 2 -based FTJs are promising for high-performance nonvolatile memories and electrical synapses.
Keyphrases
- big data
- high speed
- single molecule
- neural network
- machine learning
- artificial intelligence
- atomic force microscopy
- skeletal muscle
- healthcare
- dengue virus
- convolutional neural network
- high resolution
- deep learning
- health information
- molecular dynamics
- mass spectrometry
- heart failure
- ionic liquid
- resistance training
- zika virus
- monte carlo
- atrial fibrillation
- carbon nanotubes