Journal
IEEE TRANSACTIONS ON ELECTRON DEVICES
Volume 67, Issue 10, Pages 4201-4207Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TED.2020.3017463
Keywords
Training; Synapses; Electrodes; Capacitors; Tin; Field effect transistors; Modulation; Ferroelectric memories; hafnium; neural networks
Funding
- Ministry of Science and Technology (MOST) [109-2218-E-003-003, 108-2622-8-002-016]
- Taiwan Semiconductor Research Institute (TSRI), Taiwan
Ask authors/readers for more resources
Atomic layer deposition (ALD)-based TiN electrode on ferroelectric HfZrO2 metal/ferroelectric/metal (MFM) capacitor and ferroelectric field-effect transistor (FeFET) is demonstrated experimentally with weight transfer, that is, Delta P, per pulse analysis through consecutive alternating potentiation/depression (Pot./Dep.) training pulses. The weight training pulse schemes are studied to have symmetric and linear synapse weight transfer to increase the accuracy and accelerate the deep neural network (DNN) training. With ALD TiN inserted, alpha(p)/alpha(d) = -0.63/-0.84, asymmetry vertical bar alpha(p) - alpha(d)vertical bar = 0.21, and polarization modulation ratio (Pot./Dep.) = 97%/98% are achieved for MFM capacitor, and alpha(p)/alpha(d) = -1.32/-1.88, asymmetry vertical bar alpha(p) - alpha(d)vertical bar = 0.56, and G(max)/G(min) > 10x are delivered for FeFET.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available