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Record W4412723971 · doi:10.1016/j.msea.2025.148880

Elucidating the effect of sintering time on the process-structure-property relationship of Inconel 625 produced by metal extrusion additive manufacturing

2025· article· en· W4412723971 on OpenAlexafffund
Y.N. Aditya, Sahil Rohila, Sajad Hosseinimehr, David Ester, Michael J. Benoit

Bibliographic record

VenueMaterials Science and Engineering A · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsVancouver Biotech (Canada)University of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Waterloo
FundersMitacsInnovate BC
KeywordsExtrusionMetallurgySinteringInconelMaterials scienceInconel 625MetalMicrostructure

Abstract

fetched live from OpenAlex

Inconel 625 (IN625), a Ni-based superalloy valued for its strength and corrosion resistance, is known to suffer from microcracking during fusion-based additive manufacturing. Metal Extrusion Additive Manufacturing (MEAM) offers a solid-state alternative that eliminates solidification, thereby reducing the risk of microcracking. However, there is currently a lack of understanding between the interrelationship of process conditions, microstructure, and mechanical properties for IN625 produced by MEAM. This study investigates the influence of sintering time, 5 min (short time) versus 4 h (long time) at 1290 °C, on the densification, microstructure, and mechanical performance of MEAM-processed IN 625. The 4 h sintered sample achieved a higher relative density (99.5 %) compared to the 5 min sample (98.5 %), and both developed (Nb + Mo) rich carbides with distinct morphologies and volume fractions. Extended sintering reduced residual porosity, resulting in improved tensile strength and elongation. Fractographic analysis confirmed ductile failure via microvoid coalescence in both cases. These findings underscore the critical role of sintering duration in optimising density; despite developing microstructure characteristics that should degrade mechanical properties at longer sintering times, the mechanical properties of the 4 h sample were superior to those of the 5 min sample, revealing reduction of porosity to be the critical mechanism for maximising mechanical properties for this alloy and process.

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)0.001
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 score0.003
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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 routes2
Has abstractyes

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