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Record W7077459644 · doi:10.1016/j.jmst.2025.08.008

Influence of galvannealed zinc coating on refining microstructure and enhancing mechanical performance of laser brazed DP600 and DP980 steels

2025· article· en· W7077459644 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Material Science and Technology · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBrazingMicrostructureGalvannealedCoatingUltimate tensile strengthJoint (building)Refining (metallurgy)

Abstract

fetched live from OpenAlex

• Reveal the role of galvannealed coatings on braze microstructure and mechanical properties. • Coating thickness affects joint surface and wetting, and composition affects thermal profiles. • Lower Fe accelerates DP980 brazing cooling, refining interfacial and braze microstructure. • TEM and micro-indentation relate microstructure/precipitates to braze deformation mechanism. • DP980 braze exhibits superior strength (highest fracture load, local yield/true stresses). Laser brazing is a critical process for class-A automotive joints, with coating properties significantly affecting joint quality. However, the direct relationship between coating variations and the resulting microstructure and mechanical performance in laser-brazed advanced high-strength steels (AHSS) remains largely unexplored. This study systematically investigates how galvannealed (GA) coating thickness and Fe content within the coating influence laser brazing of DP600 and DP980 steels, including similar and dissimilar configurations. It reveals that variations in coating, rather than bulk steel chemistry, govern joint behavior. Thicker Zn coatings enhanced wetting but introduced surface imperfections, while a lower Fe content increased the cooling rate during DP980 brazing directly refining both the Cu braze microstructure and Fe(Si) interfacial reaction layer. The DP980 joint achieved the highest fracture load (4.4 kN for a 15-mm-wide strip), attributed to its refined braze grains and improved interfacial integrity. The dissimilar DP980-DP600 joint exhibited a refined microstructure compared to the DP600 braze, though the DP600/Cu boundary limited its joint strength due to incomplete wetting. Micro-indentation tests confirmed enhanced yield and tensile strengths in the DP980 braze. This study opens pathways for investigating tailored coating chemistries and thicknesses as design parameters for optimizing braze microstructure and mechanical integrity in AHSS assemblies.

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.

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 score0.005
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.004
GPT teacher head0.217
Teacher spread0.213 · 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