Dynamical nonlinear memory capacitance in biomimetic membranes
Abstract
Two-terminal memory elements, or memelements, capable of co-locating signal processing and memory via history-dependent reconfigurability at the nanoscale are vital for next-generation computing materials striving to match the brain’s efficiency and flexible cognitive capabilities. While memory resistors, or memristors, have been widely reported, other types of memelements remain underexplored or undiscovered. Here we report the first example of a volatile, voltage-controlled memcapacitor in which capacitive memory arises from reversible and hysteretic geometrical changes in a lipid bilayer that mimics the composition and structure of biomembranes. We demonstrate that the nonlinear dynamics and memory are governed by two implicitly-coupled, voltage-dependent state variables—membrane radius and thickness. Further, our system is capable of tuneable signal processing and learning via synapse-like, short-term capacitive plasticity. These findings will accelerate the development of low-energy, biomolecular neuromorphic memelements, which, in turn, could also serve as models to study capacitive memory and signal processing in neuronal membranes.
- Authors:
-
[1];
[3];
[4];
- Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Univ. of Tennessee, Knoxville, TN (United States
- Texas A & M Univ., College Station, TX (United States)
- Univ. of Tennessee, Knoxville, TN (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE; National Science Foundation (NSF)
- OSTI Identifier:
- 1546523
- Grant/Contract Number:
- AC05-00OR22725; NSF ECCS-1631472
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nature Communications
- Additional Journal Information:
- Journal Volume: 10; Journal Issue: 1; Journal ID: ISSN 2041-1723
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Najem, Joseph S., Hasan, Md Sakib, Williams, R. Stanley, Weiss, Ryan J., Rose, Garrett S., Taylor, Graham J., Sarles, Stephen A., and Collier, C. Patrick. Dynamical nonlinear memory capacitance in biomimetic membranes. United States: N. p., 2019.
Web. doi:10.1038/s41467-019-11223-8.
Najem, Joseph S., Hasan, Md Sakib, Williams, R. Stanley, Weiss, Ryan J., Rose, Garrett S., Taylor, Graham J., Sarles, Stephen A., & Collier, C. Patrick. Dynamical nonlinear memory capacitance in biomimetic membranes. United States. https://doi.org/10.1038/s41467-019-11223-8
Najem, Joseph S., Hasan, Md Sakib, Williams, R. Stanley, Weiss, Ryan J., Rose, Garrett S., Taylor, Graham J., Sarles, Stephen A., and Collier, C. Patrick. Fri .
"Dynamical nonlinear memory capacitance in biomimetic membranes". United States. https://doi.org/10.1038/s41467-019-11223-8. https://www.osti.gov/servlets/purl/1546523.
@article{osti_1546523,
title = {Dynamical nonlinear memory capacitance in biomimetic membranes},
author = {Najem, Joseph S. and Hasan, Md Sakib and Williams, R. Stanley and Weiss, Ryan J. and Rose, Garrett S. and Taylor, Graham J. and Sarles, Stephen A. and Collier, C. Patrick},
abstractNote = {Two-terminal memory elements, or memelements, capable of co-locating signal processing and memory via history-dependent reconfigurability at the nanoscale are vital for next-generation computing materials striving to match the brain’s efficiency and flexible cognitive capabilities. While memory resistors, or memristors, have been widely reported, other types of memelements remain underexplored or undiscovered. Here we report the first example of a volatile, voltage-controlled memcapacitor in which capacitive memory arises from reversible and hysteretic geometrical changes in a lipid bilayer that mimics the composition and structure of biomembranes. We demonstrate that the nonlinear dynamics and memory are governed by two implicitly-coupled, voltage-dependent state variables—membrane radius and thickness. Further, our system is capable of tuneable signal processing and learning via synapse-like, short-term capacitive plasticity. These findings will accelerate the development of low-energy, biomolecular neuromorphic memelements, which, in turn, could also serve as models to study capacitive memory and signal processing in neuronal membranes.},
doi = {10.1038/s41467-019-11223-8},
journal = {Nature Communications},
number = 1,
volume = 10,
place = {United States},
year = {Fri Jul 19 00:00:00 EDT 2019},
month = {Fri Jul 19 00:00:00 EDT 2019}
}
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Works referencing / citing this record:
Memristive plasticity in artificial electrical synapses via geometrically reconfigurable, gramicidin-doped biomembranes
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