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ACS Appl Mater Interfaces. 2018 Feb 14;10(6):5649-5656. doi: 10.1021/acsami.7b18206. Epub 2018 Feb 5.

Solid-State Synapse Based on Magnetoelectrically Coupled Memristor.

Author information

1
Hefei National Laboratory for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China , Hefei 230026, China.
2
Key Laboratory of Polar Materials and Devices, Ministry of Education, Department of Electronic Engineering, East China Normal University , Shanghai 200241, China.
3
Department of Physics and Astronomy, University of Nebraska , Lincoln, Nebraska 68588, United States.
4
Department of Physics, Pennsylvania State University , University Park 16802, United States.
5
Collaborative Innovation Center of Extreme Optics, Shanxi University , Shanxi 030006, China.
6
Collaborative Innovation Center of Advanced Microstructures , Nanjing 210093, China.

Abstract

Brain-inspired computing architectures attempt to emulate the computations performed in the neurons and the synapses in the human brain. Memristors with continuously tunable resistances are ideal building blocks for artificial synapses. Through investigating the memristor behaviors in a La0.7Sr0.3MnO3/BaTiO3/La0.7Sr0.3MnO3 multiferroic tunnel junction, it was found that the ferroelectric domain dynamics characteristics are influenced by the relative magnetization alignment of the electrodes, and the interfacial spin polarization is manipulated continuously by ferroelectric domain reversal, enriching our understanding of the magnetoelectric coupling fundamentally. This creates a functionality that not only the resistance of the memristor but also the synaptic plasticity form can be further manipulated, as demonstrated by the spike-timing-dependent plasticity investigations. Density functional theory calculations are carried out to describe the obtained magnetoelectric coupling, which is probably related to the Mn-Ti intermixing at the interfaces. The multiple and controllable plasticity characteristic in a single artificial synapse, to resemble the synaptic morphological alteration property in a biological synapse, will be conducive to the development of artificial intelligence.

KEYWORDS:

interface; magnetoelectric coupling; memristor; multiferroic tunnel junctions; synaptic plasticity

PMID:
29368507
DOI:
10.1021/acsami.7b18206
[Indexed for MEDLINE]

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