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Approaching the Zero-Power Operating Limit in a Self-Coordinated Organic Protonic Synapse.
Shuzhi Liu1,2, Zhilong He1, Bin Zhang3
1School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|October 23, 2023
Summary
Researchers developed an organic protonic memristor using TPPS molecules for brain-inspired computing. This artificial synapse achieves nonvolatile memory and ultra-low power consumption, overcoming key challenges in neuromorphic engineering.
Area of Science:
- Materials Science
- Neuroscience
- Electrical Engineering
Background:
- Developing artificial synapses is crucial for brain-inspired computing (neuromorphic engineering).
- Achieving both nonvolatile memory and ultra-low power consumption simultaneously in artificial synapses remains a significant challenge due to the energy barrier paradox.
- Existing artificial synapse technologies struggle to meet the stringent requirements for energy efficiency and stable memory modulation.
Purpose of the Study:
- To synthesize a novel organic molecule and fabricate protonic memristors for high-performance artificial synapses.
- To demonstrate effective and nonvolatile modulation of device conductance with minimal power consumption.
- To validate the artificial synapse's functionality by showcasing neuromorphic learning rules like SRDP and STDP.
Main Methods:
- Synthesis of a proton-reservoir type molecule: 4,4',4″,4'''-(Porphine-5,10,15,20-tetrayl) tetrakis (benzenesulfonic acid) (TPPS).
- Fabrication of organic protonic memristors with device widths ranging from 10 µm to 100 nm.
- Characterization of device conductance modulation, retention, power consumption, and synaptic plasticity (SRDP, STDP).
Main Results:
- The TPPS-based memristor exhibited nonvolatile conductance modulation over 64 states with retention exceeding 30 minutes.
- Achieved ultra-low power consumption for modulation (16.25 pW to 2.06 nW) and reading (6.5 fW to 0.83 pW), approaching zero-power limits.
- Successfully demonstrated artificial synapse behavior, including spiking-rate-dependent plasticity (SRDP) and spiking-timing-dependent plasticity (STDP) with power consumption as low as 0.66-0.82 pW, and 100 LTD/LTP cycles.
Conclusions:
- The synthesized TPPS molecule and fabricated organic protonic memristors offer a promising solution for high-performance artificial synapses.
- The device effectively addresses the energy barrier paradox, enabling nonvolatile memory and ultra-low power operation.
- This work paves the way for energy-efficient neuromorphic computing systems and brain-inspired artificial intelligence.
Keywords:
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