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Liquid-based memory and artificial synapse
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DOI：10.1039/c9nr02767j.png)
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Abstract
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The brain is considered as the most efficient computational system, and broadly consists of neurons and synapses. Synapses are spaces between neurons; neurotransmitters move from pre-synaptic neurons to post-synaptic neurons to transfer signals. Active research has been carried out to mimic the functions of the human nervous system using solid materials. However, mimicking the exact functions of human synaptic behaviors using solid-state materials is limited because the movement of neurotransmitters in liquid (real synapses) and solid (artificial synapses) environments is very different. Here, we demonstrate synaptic properties including long-term memory, paired-pulse facilitation, and excitatory post-synaptic current, resembling the properties of neurons in biological systems in a liquid-based resistive-switching memory (LRSM) device with a two-terminal structure designed to function based on silver nitrate (AgNO3) solution. The LRSM device can be utilized in very versatile forms and be fabricated in any shapes since its main component is liquid.
Keywords:
LONG-TERM POTENTIATION
PLASTICITY
NETWORK
MODEL
DENSITY
DEVICES
STATE
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