Evidence map›Paper›PMID 31324794›Full record

ArticleNature communications2019

Dynamical nonlinear memory capacitance in biomimetic membranes.

Joseph S Najem, Md Sakib Hasan, R Stanley Williams, Ryan J Weiss, Garrett S Rose, Graham J Taylor, Stephen A Sarles, C Patrick Collier

Erratum issuedAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
  2. Ion transport through reconfigurable nanoparticle-surfactant stabilized droplet interface bilayers.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Electromechanically induced membrane restructuring enables learning and memory.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Physical insights into biological memory using phospholipid membranes.The European physical journal. E, Soft matter · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Evidence for long-term potentiation in phospholipid membranes.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Joseph S NajemDepartment of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN, 37916, USA.ORCID http://orcid.org/0000-0001-9687-886X
Md Sakib HasanDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, 37916, USA.
R Stanley WilliamsDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77840, USA.ORCID http://orcid.org/0000-0003-0213-4259
Ryan J WeissDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, 37916, USA.
Garrett S RoseDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, 37916, USA.
Graham J TaylorDepartment of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN, 37916, USA.ORCID http://orcid.org/0000-0001-8833-7705
Stephen A SarlesDepartment of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN, 37916, USA. ssarles@utk.edu.
C Patrick CollierCenter for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA. colliercp@ornl.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Electric CapacitanceLipid BilayersNonlinear DynamicsAlgorithmsBiomimeticsCell MembraneElectrical SynapsesLearningMemoryModels, TheoreticalNeuronal PlasticityNeuronsLipid Bilayers

Identifiers

PMID31324794
PMCPMC6642212

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.