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Record W4390064866 · doi:10.1016/j.jmrt.2023.12.184

Correlation between microstructure and mechanical properties in additively manufactured Inconel 718 superalloys with low and high electron beam currents

2023· article· en· W4390064866 on OpenAlexaff
Dohoon Lee, Sangwoo Park, Chanhee Lee, Hyun-Uk Hong, Jongyeong Oh, Tae-Yeong So, Woosung Kim, D. Seo, Jeongho Han, Se‐Hyun Ko, Byoung-Soo Lee

Bibliographic record

VenueJournal of Materials Research and Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsNational Research Council Canada
FundersNational Research Foundation of KoreaKorea Institute of Industrial TechnologyMinistry of Science, ICT and Future Planning
KeywordsInconelSuperalloyMaterials scienceMicrostructureCathode rayMetallurgyElectronComposite materialAlloyNuclear physics

Abstract

fetched live from OpenAlex

This study explored the correlation between microstructure and mechanical properties in additively manufactured Inconel 718 superalloys with low and high electron beam (EB) currents. The relative densities of the as-built Inconel 718 superalloys with low EB currents ranged from 99.45 to 99.79 %, while the alloys with high EB currents demonstrated relatively high relative densities ranging from 99.82 to 99.96 %. The microstructures of the alloys with low EB currents had columnar grain microstructures with a strong <0 0 1> texture parallel to the built direction (BD). The high-angle grain boundary density of the alloys with low EB currents was lower than with high EB currents. In addition, the alloys contained fine γ″ precipitates with an average size of 32 nm. Although the fracture-initiating sites for the alloys consisted of defects, such as micro-cracks and gas-entrapped pores, the alloys with low EB currents demonstrated excellent tensile strength and good uniform elongation due to the single-crystal-like microstructures and fine γ″ precipitates. The γ″ precipitates easily grew in deep and narrow melt pools due to sufficient thermal transfer with increasing penetration depth. However, the growth of γ″ precipitates was limited in the shallow and wide melt pools, and the shallow and wide melt pools resulted in single-crystal-like microstructures and strong <0 0 1> textures parallel to the BD. Therefore, the morphology of the melt pool, determined by the EB current, played an important role in the single-crystalline microstructure and growth of the γ” precipitates.

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)0.000
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 score0.031
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.017
GPT teacher head0.254
Teacher spread0.237 · 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

Citations13
Published2023
Admission routes1
Has abstractyes

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