Polarization-controlled volatile ferroelectric and capacitive switching in Sn2P2S6. Issue 1 (1st March 2023)
- Record Type:
- Journal Article
- Title:
- Polarization-controlled volatile ferroelectric and capacitive switching in Sn2P2S6. Issue 1 (1st March 2023)
- Main Title:
- Polarization-controlled volatile ferroelectric and capacitive switching in Sn2P2S6
- Authors:
- Neumayer, Sabine M
Ievlev, Anton V
Tselev, Alexander
Basun, Sergey A
Conner, Benjamin S
Susner, Michael A
Maksymovych, Petro - Abstract:
- Abstract: Smart electronic circuits that support neuromorphic computing on the hardware level necessitate materials with memristive, memcapacitive, and neuromorphic- like functional properties; in short, the electronic response must depend on the voltage history, thus enabling learning algorithms. Here we demonstrate volatile ferroelectric switching of Sn2 P2 S6 at room temperature and see that initial polarization orientation strongly determines the properties of polarization switching. In particular, polarization switching hysteresis is strongly imprinted by the original polarization state, shifting the regions of non-linearity toward zero-bias. As a corollary, polarization switching also enables effective capacitive switching, approaching the sought-after regime of memcapacitance. Landau–Ginzburg–Devonshire simulations demonstrate that one mechanism by which polarization can control the shape of the hysteresis loop is the existence of charged domain walls (DWs) decorating the periphery of the repolarization nucleus. These walls oppose the growth of the switched domain and favor back-switching, thus creating a scenario of controlled volatile ferroelectric switching. Although the measurements were carried out with single crystals, prospectively volatile polarization switching can be tuned by tailoring sample thickness, DW mobility and electric fields, paving way to non-linear dielectric properties for smart electronic circuits.
- Is Part Of:
- Neuromorphic computing and engineering. Volume 3:Issue 1(2023)
- Journal:
- Neuromorphic computing and engineering
- Issue:
- Volume 3:Issue 1(2023)
- Issue Display:
- Volume 3, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 3
- Issue:
- 1
- Issue Sort Value:
- 2023-0003-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-03-01
- Subjects:
- domain walls -- neuromorphic -- tunable -- ferroelectric -- scanning microwave impedance microscopy
Neural networks (Computer science) -- Periodicals
Neural computers -- Periodicals
Neuromorphics -- Periodicals
006.3 - Journal URLs:
- http://www.iop.org/ ↗
https://iopscience.iop.org/journal/2634-4386 ↗ - DOI:
- 10.1088/2634-4386/acb37e ↗
- Languages:
- English
- ISSNs:
- 2634-4386
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25693.xml