Evidence map›Paper›PMID 34099691›Full record

ArticleNature communications2021

Self-sustained green neuromorphic interfaces.

Tianda Fu, Xiaomeng Liu, Shuai Fu, Trevor Woodard, Hongyan Gao, Derek R Lovley, Jun Yao

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
6.3field-weighted citation impact, top 3% of its field
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

19 citing papers in PubMed, 82 citations in OpenAlex.

  1. Article
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  8. Sodium-Controlled Interfacial Resistive Switching in Thin Film Niobium Oxide for Neuromorphic Applications.Chemistry of materials : a publication of the American Chemical Society · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Emerging memristive neurons for neuromorphic computing and sensing.Science and technology of advanced materials · 2023
    Review
  14. Article
  15. Article
  16. Article
  17. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Tianda FuDepartment of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA.ORCID 0000-0002-7425-3305
Xiaomeng LiuDepartment of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA.ORCID 0000-0003-1463-9916
Shuai FuDepartment of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA.
Trevor WoodardDepartment of Microbiology, University of Massachusetts, Amherst, MA, USA.
Hongyan GaoDepartment of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA.
Derek R LovleyDepartment of Microbiology, University of Massachusetts, Amherst, MA, USA.ORCID 0000-0001-7158-3555
Jun YaoDepartment of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA. juny@umass.edu.ORCID 0000-0002-5269-3190
University of Massachusetts Amherst · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incorporating neuromorphic electronics in bioelectronic interfaces can provide intelligent responsiveness to environments. However, the signal mismatch between the environmental stimuli and driving amplitude in neuromorphic devices has limited the functional versatility and energy sustainability. Here we demonstrate multifunctional, self-sustained neuromorphic interfaces by achieving signal matching at the biological level. The advances rely on the unique properties of microbially produced protein nanowires, which enable both bio-amplitude (e.g., <100 mV) signal processing and energy harvesting from ambient humidity. Integrating protein nanowire-based sensors, energy devices and memristors of bio-amplitude functions yields flexible, self-powered neuromorphic interfaces that can intelligently interpret biologically relevant stimuli for smart responses. These features, coupled with the fact that protein nanowires are a green biomaterial of potential diverse functionalities, take the interfaces a step closer to biological integration.

Indexed as

NanowiresBiocompatible MaterialsElectronicsNanotechnologyNeural Networks, ComputerProteinsSynapsesBiocompatible MaterialsProteins

Identifiers

PMID34099691
PMCPMC8184933
OpenAlexW3168828086

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.