Room-temperature developed flexible biomemristor with ultralow switching voltage for array learning

Area of Science:

• Materials Science
• Neuroscience
• Computer Engineering

Background:

• Memristors are promising for neuromorphic computing, potentially overcoming von Neumann architecture limitations.
• Flexible memristor development is hindered by high-temperature processing, high operating voltages, and resistance variability.
• Room-temperature fabrication offers advantages like low cost, reduced thermal dissipation, and compatibility with flexible electronics.

Purpose of the Study:

• To develop a flexible memristor using a room-temperature physical vapor deposition (PVD) process.
• To evaluate the memristor's resistive switching characteristics, including operating voltage, uniformity, retention, multilevel storage, and flexibility.
• To simulate synaptic plasticity and array learning behaviors for neuromorphic applications.

Main Methods:

• Fabrication of memristors using a fully physical vapor deposition (PVD) process at room temperature without heat treatment.
• Characterization of resistive switching properties, including set/reset voltages, endurance, retention, and multilevel storage.
• Simulation of synaptic functions such as excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), long-term potentiation/depression (LTP/LTD), and learning-forgetting curves.
• Demonstration of array learning behavior using trainable biomemristors.

Main Results:

• The fabricated memristors exhibited excellent resistive switching with ultralow set/reset voltages (0.48 V/-0.39 V).
• Devices showed uniform resistance distribution (10%/15%), stable retention, multilevel storage, and reliable flexibility (10 mm radius).
• Simulations successfully replicated key synaptic plasticities and brain-like array learning behaviors.

Conclusions:

• A novel room-temperature PVD process enables the fabrication of high-performance flexible memristors.
• These memristors demonstrate potential for low-cost, wearable neuromorphic computing devices.
• The study advances artificial synapse arrays and opens new avenues for brain-inspired electronics.