Oil and Water Almost Mix in Novel Neuromorphic Computing Components

Lipid-based devices mimic brain-like processing

Two blue opaque spheres connected in a pool of liquid.
Image courtesy of Oak Ridge National Laboratory
Researchers demonstrated the first example of a lipid-based “memcapacitor,” an energy storage device with memory that advances brain-like, synaptic information processing in neuromorphic computing. The video linked to the graphic illustrates the expansion of the oil-water interface between the drops as voltage is applied.

The Science

Researchers developed a novel memory storage device that uses soft biomaterials. These are artificial materials designed to work like natural biological materials. The memory storage device mimics synapses, the connections between nerve cells. The device consists of two layers of fatty organic compounds called lipids. The lipid layers form at an oil-water interface to create a soft membrane. When scientists apply an electric charge to the membrane, the membrane changes shape in ways that can store energy and filter biological and chemical data.

The Impact

The novel membrane speeds the development of hardware to support neuromorphic computing networks. These are computing systems that draw their design from nervous systems found in nature. Systems designed with bio-circuitry open new pathways for artificial intelligence. They are especially promising for real time sensing applications. They are also promising for distributed “edge” computing, which places computer storage and processing resources close to the location where they are needed to produce flexible, scalable networks with low energy costs.


Neuromorphic computing systems mimic the brain’s synaptic circuitry. The technology offers increased efficiency and interconnectivity. It also offers unique potential for computing nondigital or sensory information using architectures based on biology. Neuromorphic systems are gaining interest for use in wearable or embedded technologies that can compute on the fly, without connection to a cloud, by leveraging the highly specialized sensing and detection capabilities found in biological molecules.

To advance these neuromorphic computers, scientists must develop novel materials and computing elements that differ from the solid-state electronic devices used in traditional digital computers. Neuromorphic computers are based on “memelements,” components that combine both processing and memory in a single location to mimic the way neurons and synapses evaluate, learn, and communicate sensory information. Researchers are developing novel biomaterials to support memelements. They have previously demonstrated a memristor, a component that evaluates information to determine if the signal is strong enough to propagate. This new research goes a step further by demonstrating a memcapacitor, a signal processing device that can also store energy, enabling greater complexity in neuromorphic networks.


Stephen Sarles
Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville

Patrick Collier
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory


The research was supported by the National Science Foundation and performed in collaboration with scientists at the Center for Nanophase Materials Sciences, a Department of Energy Office of Science Nanoscale Science Research Center user facility.


Joseph Najem, et al. “Dynamical nonlinear memory capacitance in biomimetic membranes,” Nature Communications 10, 3232 (2019). [DOI: 10.1038/s41467-019-11223-8]

Related Links

Bio-circuitry mimics synapses and neurons in a step toward sensory computing, Oak Ridge National Laboratory

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