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Record W4388485348 · doi:10.1002/smll.202304988

Pseudocapacitance‐Induced Synaptic Plasticity of Tribo‐Phototronic Effect Between Ionic Liquid and 2D MoS<sub>2</sub>

2023· article· en· W4388485348 on OpenAlexafffund
Ribwar Ahmadi, Amin Abnavi, Amirhossein Hasani, Hamidreza Ghanbari, Mohammad Reza Mohammadzadeh, Mirette Fawzy, Fahmid Kabir, Michael M. Adachi

Bibliographic record

VenueSmall · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsSimon Fraser University
FundersWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceTriboelectric effectIonic liquidSynaptic plasticityContact electrificationNanotechnologyOptoelectronicsComposite materialChemistry

Abstract

fetched live from OpenAlex

Abstract Contact‐induced electrification, commonly referred to as triboelectrification, is the subject of extensive investigation at liquid–solid interfaces due to its wide range of applications in electrochemistry, energy harvesting, and sensors. This study examines the triboelectric between an ionic liquid and 2D MoS 2 under light illumination. Notably, when a liquid droplet slides across the MoS 2 surface, an increase in the generated current and voltage is observed in the forward direction, while a decrease is observed in the reverse direction. This suggests a memory‐like tribo‐phototronic effect between ionic liquid and 2D MoS 2 . The underlying mechanism behind this tribo‐phototronic synaptic plasticity is proposed to be ion adsorption/desorption processes resulting from pseudocapacitive deionization/ionization at the liquid–MoS 2 interface. This explanation is supported by the equivalent electrical circuit modeling, contact angle measurements, and electronic band diagrams. Furthermore, the influence of various factors such as velocity, step size, light wavelength and intensity, ion concentration, and bias voltage is thoroughly investigated. The artificial synaptic plasticity arising from this phenomenon exhibits significant synaptic features, including potentiation/inhibition, paired‐pulse facilitation/depression, and short‐term memory (STM) to long‐term memory (LTM) transition. This research opens up promising avenues for the development of synaptic memory systems and intelligent sensing applications based on liquid–solid interfaces.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.218
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2023
Admission routes2
Has abstractyes

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