Scaled, Ferroelectric Memristive Synapse for Back‐End‐of‐Line Integration with Neuromorphic Hardware. (8th March 2022)
- Record Type:
- Journal Article
- Title:
- Scaled, Ferroelectric Memristive Synapse for Back‐End‐of‐Line Integration with Neuromorphic Hardware. (8th March 2022)
- Main Title:
- Scaled, Ferroelectric Memristive Synapse for Back‐End‐of‐Line Integration with Neuromorphic Hardware
- Authors:
- Bégon‐Lours, Laura
Halter, Mattia
Puglisi, Francesco Maria
Benatti, Lorenzo
Falcone, Donato Francesco
Popoff, Youri
Dávila Pineda, Diana
Sousa, Marilyne
Offrein, Bert Jan - Abstract:
- Abstract: Ohmic, memristive synaptic weights are fabricated with a back‐end‐of‐line compatible process, based on a 3.5 nm HfZrO4 thin film crystallized in the ferroelectric phase at only 400 °C. The current density is increased by three orders of magnitude compared to the state‐of‐the‐art. The use of a metallic oxide interlayer, WO x, allows excellent retention (only 6% decay after 10 6 s) and endurance (10 10 full switching cycles). The On/Off of 7 and the small device‐to‐device variability (<5%) make them promising candidates for neural networks inference. The synaptic functionality for online learning is also demonstrated: using pulses of increasing (resp. constant) amplitude and constant (resp. increasing) duration, emulating spike‐timing (resp. spike‐rate) dependent plasticity. Writing with 20 ns pulses only dissipate femtojoules. The cycle‐to‐cycle variation is below 2%. The training accuracy (MNIST) of a neural network is estimated to reach 92% after 36 epochs. Temperature‐dependent experiments reveal the presence of allowed states for charge carriers within the bandgap of hafnium zirconate. Upon polarization switching, the screening of the polarization by mobile charges (that can be associated with oxygen vacancies and/or ions) within the ferroelectric layer modifies the energy profile of the conduction band and the bulk transport properties. Abstract : A back‐end‐of‐line, ferroelectric synapse shows excellent cycle‐to‐cycle and device‐to‐device variation (2%),Abstract: Ohmic, memristive synaptic weights are fabricated with a back‐end‐of‐line compatible process, based on a 3.5 nm HfZrO4 thin film crystallized in the ferroelectric phase at only 400 °C. The current density is increased by three orders of magnitude compared to the state‐of‐the‐art. The use of a metallic oxide interlayer, WO x, allows excellent retention (only 6% decay after 10 6 s) and endurance (10 10 full switching cycles). The On/Off of 7 and the small device‐to‐device variability (<5%) make them promising candidates for neural networks inference. The synaptic functionality for online learning is also demonstrated: using pulses of increasing (resp. constant) amplitude and constant (resp. increasing) duration, emulating spike‐timing (resp. spike‐rate) dependent plasticity. Writing with 20 ns pulses only dissipate femtojoules. The cycle‐to‐cycle variation is below 2%. The training accuracy (MNIST) of a neural network is estimated to reach 92% after 36 epochs. Temperature‐dependent experiments reveal the presence of allowed states for charge carriers within the bandgap of hafnium zirconate. Upon polarization switching, the screening of the polarization by mobile charges (that can be associated with oxygen vacancies and/or ions) within the ferroelectric layer modifies the energy profile of the conduction band and the bulk transport properties. Abstract : A back‐end‐of‐line, ferroelectric synapse shows excellent cycle‐to‐cycle and device‐to‐device variation (2%), retention and endurance (10 10 cycles). A 10% error is measured in a 3 × 3 crossbar (92% accuracy predicted on the MNIST data set). Ohmic conduction at low bias is ideal for multiply and accumulate operation. Temperature measurements reveal the analog resistive switching mechanisms in semiconducting and ferroelectric HfZrO4 . … (more)
- Is Part Of:
- Advanced Electronic Materials. Volume 8:Number 6(2022)
- Journal:
- Advanced Electronic Materials
- Issue:
- Volume 8:Number 6(2022)
- Issue Display:
- Volume 8, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 8
- Issue:
- 6
- Issue Sort Value:
- 2022-0008-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-03-08
- Subjects:
- back‐end‐of‐line -- ferroelectrics -- resistive switching -- synaptic weight -- transport
Materials -- Electric properties -- Periodicals
Materials science -- Periodicals
Magnetic materials -- Periodicals
Electronic apparatus and appliances -- Periodicals
537 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2199-160X ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/aelm.202101395 ↗
- Languages:
- English
- ISSNs:
- 2199-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.848400
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21809.xml