MétaCan
Menu
Back to cohort

The Effect of Strain Reversal during High Pressure Torsion on the Evolution of Microstructure and Hardness in Al-2.5wt% Mg alloy

2020· dataset· en· W3135046835 on OpenAlexaff
Kanwal Chadha, P.P. Bhattacharjee

Bibliographic record

VenueAuthorea · 2020
Typedataset
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsUniversity of FrederictonUniversity of New Brunswick
Fundersnot available
KeywordsMicrostructureEquiaxed crystalsMaterials scienceMetallurgyAlloyTorsion (gastropod)Indentation hardnessGrain sizeAluminium

Abstract

fetched live from OpenAlex

The present work aims to investigate the effect of strain reversal during High Pressure Torsion (HPT) on the evolution of microstructure and hardness properties of Aluminium-Magnesium (Al-2.5%Mg) alloy. For this purpose, Al-2.5%Mg alloy was subjected to monotonically (CW) and strain reversal (CW-CCW) deformation by High Pressure Torsion (HPT). The samples were subjected to a series of rotations in monotonically and strain reversal deformation with same equivalent strains of 1, 4, 12, 24 and 60 under an applied load of 6 GPa and with 1 rpm under quasi-constrained conditions. It was observed that Al-2.5%Mg when subjected to different routes, follows same trend in the evolution of the ultrafine structure, i.e. initial recrystallized microstructure with large grain size throughout the disk, at low strain level sub grains with prominent LAGBs network inside the grains and ultimately at the higher strains ultrafine microstructure throughout the disk characterized by equiaxed grains separated by HAGBs. The only exception to this was observed in case of Al-2.5%Mg during high strains at the centre regions where the fraction of HAGBs was found strikingly less as compared to its counterpart during strain reversal deformation. Hardness homogeneity was not observed for Al-2.5%Mg where the hardness at the centre regions was observed to be lesser than the edge regions with exceptionally less hardness at centre for strain reversal specimens at higher strains.

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: none
Teacher disagreement score0.590
Threshold uncertainty score0.524

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 science0.0010.000
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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAuthoreaSame topicMicrostructure and mechanical propertiesFrench-language works237,207