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  1. Artificial synaptic devices made from natural biomaterials capable of emulating functions of biological synapses, such as synaptic plasticity and memory functions, are desirable for the construction of brain-inspired neuromorphic computing systems. The metal/dielectric/metal device structure is analogous to the pre-synapse/synaptic cleft/post-synapse structure of the biological neuron, while using natural biomaterials promotes ecologically friendly, sustainable, renewable, and low-cost electronic devices. In this work, artificial synaptic devices made from honey mixed with carbon nanotubes, honey-carbon nanotube (CNT) memristors, were investigated. The devices emulated spike-timing-dependent plasticity, with synaptic weight as high as 500%, and demonstrated a paired-pulse facilitation gain of 800%, which is the largest value ever reported. 206-level long-term potentiation (LTP) and long-term depression (LTD) were demonstrated. A conduction model was applied to explain the filament formation and dissolution in the honey-CNT film, and compared to the LTP/LTD mechanism in biological synapses. In addition, the short-term and long-term memory behaviors were clearly demonstrated by an array of 5 × 5 devices. This study shows that the honey-CNT memristor is a promising artificial synaptic device technology for applications in sustainable neuromorphic computing.

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    Free, publicly-accessible full text available December 11, 2024
  2. Free, publicly-accessible full text available August 6, 2024
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  4. Natural organic materials such as protein and carbohydrates are abundant in nature, renewable, and biodegradable, desirable for the construction of artificial synaptic devices for emerging neuromorphic computing systems with energy efficient operation and environmentally friendly disposal. These artificial synaptic devices are based on memristors or transistors with the memristive layer or gate dielectric formed by natural organic materials. The fundamental requirement for these synaptic devices is the ability to mimic the memory and learning behaviors of biological synapses. This paper reviews the synaptic functions emulated by a variety of artificial synaptic devices based on natural organic materials and provides a useful guidance for testing and investigating more of such devices. 
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