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Record W4415738710 · doi:10.1103/jxws-jnf7

Linking acoustic emission signals to deformation mechanisms in magnesium

2025· article· en· W4415738710 on OpenAlexfundno aff
Shimon Bettan, Emil Bronstein, Hanuš Seiner, Petr Sedlák, Martin Koller, Doron Shilo, Eilon Faran

Bibliographic record

VenuePhysical Review Materials · 2025
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science FoundationGrantová Agentura České Republiky
KeywordsAcoustic emissionDeformation (meteorology)Slip (aerodynamics)MagnesiumDeformation mechanismCrystal twinningModalSpectroscopy

Abstract

fetched live from OpenAlex

Understanding a material's behavior requires insight into how microscopic deformation mechanisms evolve, but identifying these processes at the level of individual microscopic events is a major challenge. Here, the authors present a physics-guided, data-driven spectral analysis of acoustic emission (AE) signals to classify individual deformation events in a magnesium single crystal. The analysis links AE frequency signatures to twinning and slip mechanisms and validates them through resonance ultrasound spectroscopy and modal calculations. Thus, the study achieves unsupervised classification of deformation events, uncovering the transition from twinning-dominant to slip-dominant behavior. This approach offers a new pathway for mechanism-specific monitoring of damage evolution.

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)0.001
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 score0.011
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.001

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 head0.016
GPT teacher head0.301
Teacher spread0.284 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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