Open AccessA FeFET with a novel MFMFIS gate stack: towards energy-efficient and ultrafast NVMs for neuromorphic computing
Author(s) -
Tarek Ali,
Konstantin Mertens,
Kati Kühnel,
Matthias Rudolph,
Sebastian Oehler,
David Lehninger,
Franz Müller,
Ricardo Revello,
Raik Hoffmann,
Katrin Zimmermann,
Thomas Kämpfe,
M. Czernohorsky,
Konrad Seidel,
J. Van Houdt,
Lukas M. Eng
Publication year - 2021
Publication title -
nanotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.926
H-Index - 203
eISSN - 1361-6528
pISSN - 0957-4484
DOI - 10.1088/1361-6528/ac146c
Subject(s) - ferroelectricity , materials science , optoelectronics , neuromorphic engineering , non volatile memory , stack (abstract data type) , transistor , field effect transistor , voltage , electrical engineering , computer science , machine learning , artificial neural network , dielectric , programming language , engineering
The discovery of ferroelectricity in the fluorite structure based hafnium oxide (HfO 2 ) material sparked major efforts for reviving the ferroelectric field effect transistor (FeFET) memory concept. A Novel metal-ferroelectric-metal-ferroelectric-insulator-semiconductor (MFMFIS) FeFET memory is reported based on dual ferroelectric integration as an MFM and MFIS in a single gate stack using Si-doped Hafnium oxide (HSO) ferroelectric (FE) material. The MFMFIS top and bottom electrode contacts, dual HSO based ferroelectric layers, and tailored MFM to MFIS area ratio (AR-TB) provide a flexible stack structure tuning for improving the FeFET performance. The AR-TB tuning shows a tradeoff between the MFM voltage increase and the weaker FET Si channel inversion, particularly notable in the drain saturation current I D (sat) when the AR-TB ratio decreases. Dual HSO ferroelectric layer integration enables a maximized memory window (MW) and dynamic control of its size by tuning the MFM to MFIS switching contribution through the AR-TB change. The stack structure control via the AR-TB tuning shows further merits in terms of a low voltage switching for a saturated MW size, an extremely linear at wide dynamic range of the current update, as well as high symmetry in the long term synaptic potentiation and depression. The MFMFIS stack reliability is reported in terms of the switching variability, temperature dependence, endurance, and retention. The MFMFIS concept is thoroughly discussed revealing profound insights on the optimal MFMFIS stack structure control for enhancing the FeFET memory performance.