Biomolecular Neuristors from Functionalized Lipid Membranes

Area of Science:

• Biomolecular Engineering
• Neuro-inspired Computing
• Materials Science

Background:

• Neuristors mimic biological neurons for efficient signal processing but typically require complex circuits.
• Existing neuristor designs face challenges in fabrication, size, power consumption, and cost.

Purpose of the Study:

• To demonstrate a single-device artificial neuristor using a functionalized lipid membrane.
• To explore the potential of biomolecular membranes for transistor-free spiking neural networks.

Main Methods:

• Fabrication of a 5nm-thick lipid membrane functionalized with voltage-activated peptides.
• Characterization of the membrane's electrical properties under DC current stimulation.
• Analysis of voltage oscillations and action potential generation.

Main Results:

• The single-membrane device functions as a two-terminal, ultra-low power (fW-pW) artificial neuristor.
• The biomolecular membrane generates stochastic voltage oscillations (10-150 mV) in response to DC currents (5-40 pA).
• Two distinct types of action potentials (fast ~1-50 ms and slow ~1-2 s) were observed via different physical mechanisms.

Conclusions:

• Engineered biomembranes offer inherent multifunctionality and modularity for neuromorphic hardware.
• This single-device neuristor represents a significant advancement in creating compact, efficient, and low-power artificial neurons.
• The findings contribute to the development of ionic and biomolecular devices for emerging computing architectures.