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Record W4410267946 · doi:10.1002/advs.202416305

Residual Stresses and Micro‐voids Propel Metal Diffusion for Filament‐Based Memristors

2025· article· en· W4410267946 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Science · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsMaterials scienceProtein filamentResidual stressComposite materialDiffusionMetallurgyMetalThermodynamics

Abstract

fetched live from OpenAlex

Metal filamentation based mechanisms have the advantage of a high switching current ratio, yet typically require high switching voltages to activate the memristive device due to the primary mechanism of atomic vacancy filling and movement. Herein, Introducing non-reactive nitrogen gas during plasma sputtering of silver is shown to prime the overlying metal nitride layer to achieve low threshold switching at applied biases of below 60 millivolts. Residual nitrogen species within the silver under-layer promote the creation of nano-sized void defects within the superjacent dielectric layer, which, coupled with residual stresses in the gigapascal range, enable sub-micron filamentation growth. These memristor devices function similarly to potassium ion channels, displaying current growth and relaxation patterns that align with the Hodgkin-Huxley model, and as such are amenable to the development of artificial neuron structures. Further, a diverse set of neuromorphic behaviors not seen within typical metal filamentation based memristors is observed. This includes multi-peak synaptic weight changes in the device's response to spiked stimuli. Both the switching voltages and neuromorphic properties are linked to the nitrogen-argon pressure during silver deposition. Interestingly, these devices also exhibit lateral growth of silver filamentation across the surface of the metal nitride thin film layer with gaps of more than a hundred micrometers, suggesting that the underlying silver undergoes accumulation and breakthrough. The filling of large micro-voids with Ag generates large nanoparticles that easily propagate, enabling a large diffusion front and faster filamentation time, whereas small micro-voids create a bottleneck in the filamentation process. Additionally, the introduction of residual stresses in conventional diffusion theory indicates greater dendritic interconnectivity and thus electrode to electrode connection. This study demonstrates that the facile incorporation of non-reactive gases during the sputter-deposition of a metal electrode opens a path to unique material mechanisms that facilitate the development of versatile memristors.

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.

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 score0.029
Threshold uncertainty score0.462

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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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