Related Experiment Video
Updated: Sep 10, 2025
Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Reconfigurable Counterion Gradient around Charged Metal Nanoparticles Enables Self-Rectifying and Volatile Artificial
Jingyu Wang1,2, Lin Liu1,2, Xing Zhao1
1CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China.
None:
Developing a device that faithfully replicates the characteristics of biological synapses is a prerequisite for the hardware implementation of neuromorphic computing. An electronic device fabricated with metallic materials, instead of traditional semiconductors, is "genetically" impossible since the field applied to the metal is screened, leading to insensitive modulation in material conductance. Herein, these two independent or uncorrelated "challenges" can be addressed by using metal nanoparticles decorated with charged molecules. Specifically, we have developed a self-rectifying and volatile metal nanoparticle artificial synapse whose conductance can be continuously modulated. Theoretical calculations indicate that the current rectification is due to the reconfigurable asymmetric counterion gradients within the nanoparticle channel with asymmetric electrode areas. The synaptic functions based on nanoparticle devices are subsequently emulated. Finally, we demonstrate that our synapse array can accurately classify handwritten digits with a newly developed computational structure that combines CNN and reservoir computing.
Related Concept Videos
01:21Electrochemical Gradient and Channel Proteins: An Overview
The electrical gradient: The electrical gradient across cell membranes refers to the difference in electric charge between the inside and outside of a cell. This difference drives the movement of ions towards or away from the cells. For instance, if the inside of the cell is more negatively charged relative to...
01:19The Role of Ion Channels in Neuronal Computation
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
01:26Chemical Synapses
Because chemical synapses depend on the release of neurotransmitter molecules from synaptic vesicles to pass on their signal, there is an approximately one millisecond delay between when the axon potential reaches the presynaptic terminal and when the neurotransmitter leads to opening of postsynaptic ion channels. Additionally, this signaling is...
01:30Ligand-Gated Ion Channel Receptor: Gating Mechanism
01:28Electrical Synapses
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...
01:26What is an Electrochemical Gradient?
The chemical gradient relies on differences in the abundance of a substance on the outside versus the inside of a cell and flows from areas of high to low ion concentration. In contrast, the electrical gradient revolves around an...