ArticleNature communications2018
A molecular neuromorphic network device consisting of single-walled carbon nanotubes complexed with polyoxometalate.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 146 citations in OpenAlex.
- Polyoxometalates (POMs) Memristors/Neuromorphic Devices: From Structure Engineering to Material and Function Integration.Nanomaterials (Basel, Switzerland) · 2026Review
- Utilizing Cooperative Proton-Electron Mixed Conduction Induced via Chemical Dedoping of Self-Doped Poly(3,4-ethylenedioxythiophene) Nanofilms for In-Material Physical Reservoirs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Very-large-scale mimetic optogenetic synapses for physical reservoir computing.Nature communications · 2026Article
- Genomic and Functional Characterization of Bacillus siamensis B01 with Antimicrobial Activity Against Vibrio spp.Current microbiology · 2025Article
- Cooperative and selective redox doping switches single-molecule magnetism.Science advances · 2025Article
- Self-organizing neuromorphic nanowire networks as stochastic dynamical systems.Nature communications · 2025Article
- Highly-integrable analogue reservoir circuits based on a simple cycle architecture.Scientific reports · 2024Article
- Few- and single-molecule reservoir computing experimentally demonstrated with surface-enhanced Raman scattering and ion gating.Science advances · 2024Article
- Electron-Sponge Nature of Polyoxometalates for Next-Generation Electrocatalytic Water Splitting and Nonvolatile Neuromorphic Devices.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Theoretical Study on the Open-Shell Electronic Structure and Electron Conductivity of [18]Annulene as a Molecular Parallel Circuit Model.Nanomaterials (Basel, Switzerland) · 2023Article
- Artificial-intelligence-assisted mass fabrication of nanocantilevers from randomly positioned single carbon nanotubes.Microsystems & nanoengineering · 2023Article
- Stochastic Resonance in Organic Electronic Devices.Polymers · 2022Review
- Physical Implementation of Reservoir Computing through Electrochemical Reaction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks.Nature materials · 2022Article
- Information dynamics in neuromorphic nanowire networks.Scientific reports · 2021Article
- The rise of intelligent matter.Nature · 2021Review
- A protecting group strategy to access stable lacunary polyoxomolybdates for introducing multinuclear metal clusters.Chemical science · 2021Article
- Nanoscale Patterning of Carbon Nanotubes: Techniques, Applications, and Future.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020Review
- Polyoxometalates as components of supramolecular assemblies.Chemical science · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
In contrast to AI hardware, neuromorphic hardware is based on neuroscience, wherein constructing both spiking neurons and their dense and complex networks is essential to obtain intelligent abilities. However, the integration density of present neuromorphic devices is much less than that of human brains. In this report, we present molecular neuromorphic devices, composed of a dynamic and extremely dense network of single-walled carbon nanotubes (SWNTs) complexed with polyoxometalate (POM). We show experimentally that the SWNT/POM network generates spontaneous spikes and noise. We propose electron-cascading models of the network consisting of heterogeneous molecular junctions that yields results in good agreement with the experimental results. Rudimentary learning ability of the network is illustrated by introducing reservoir computing, which utilises spiking dynamics and a certain degree of network complexity. These results indicate the possibility that complex functional networks can be constructed using molecular devices, and contribute to the development of neuromorphic devices.
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What OpenQuestion holds
Registered trials
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.