MétaCan
Menu
Back to cohort
Record W4312186431 · doi:10.4028/p-6kpo4z

Interfacial Properties of Additively Manufactured M789 Steel on Wrought N709 Alloy

2022· article· en· W4312186431 on OpenAlexaff
Kudakwashe Nyamuchiwa, Yuan Tian, Kanwal Chadha, You Liang He, Clodualdo Aranas

Bibliographic record

VenueDefect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forum · 2022
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMaterials scienceAlloyUltimate tensile strengthNanoindentationHardening (computing)Precipitation hardeningMetallurgyComposite materialIndentation hardnessMicrostructureFusionLayer (electronics)

Abstract

fetched live from OpenAlex

An additively manufactured M789 steel was deposited on wrought precipitation-hardening N709 steel to form a hybrid alloy using the laser powder bed fusion (LPBF) process. After tensile testing, failure in the as-printed (AP) state was detected in the M789 section with a peak strength of 1019 MPa, consistent with the nanoindentation measurement across the M789-N709 interface. The application of heat treatment of the hybrid alloy shifted the failure zone to the N709 alloy with a peak strength of 1600 MPa. The high strength of M789 after heat treatment was due to the formation of the η-phase during aging. A robust metallurgical bond was successfully formed between the two alloys since the fracture did not occur in the interface for both the AP and heat treated (HT) states during tensile testing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.029
GPT teacher head0.244
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDefect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forumSame topicAdditive Manufacturing Materials and ProcessesFrench-language works237,207