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Record W4412441565 · doi:10.1016/j.jmapro.2025.07.022

Dissimilar ultrasonic spot welding of AA6016 alloy-to-DP800 steel: The role of a novel AlSi(Fe) PVD coating

2025· article· en· W4412441565 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 Manufacturing Processes · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsUniversity of AlbertaToronto Metropolitan University
FundersJoining and Welding Research Institute, Osaka UniversityNatural Resources CanadaAlberta InnovatesOsaka UniversityNatural Sciences and Engineering Research Council of CanadaBundesministerium für Wirtschaft und Klimaschutz
KeywordsMaterials scienceCoatingUltrasonic sensorMetallurgyAlloySpot weldingWeldingUltrasonic weldingComposite materialAcoustics

Abstract

fetched live from OpenAlex

Lightweighting in the automotive industry often involves joining dissimilar materials, while ensuring the safety and durability of load-bearing components. However, the joining of dissimilar materials presents significant challenges due to differences in their physical and chemical properties. In this study, a novel AlSi(Fe) physical vapor deposition (PVD) coating was applied on DP800 steel to enhance its compatibility with AA6016 aluminum alloy during solid-state ultrasonic spot welding (USW). The AA6016-to-coated DP800 steel joints, fabricated at welding energies around 1250 J, surpassed the tensile lap shear load requirements specified in the AWS D17.2 standard. The presence of the PVD coating not only enhanced the tensile lap shear strength by 23 % (i.e., from 69 MPa to 85 MPa), but also reduced the welding energy required to achieve optimal joint performance by 37.5 % (i.e., from 2000 J to 1250 J). This reduction in energy consumption further contributed to improved welding efficiency. The AA6016-to-uncoated DP800 steel joints at a welding energy of 2000 J exhibited button pullout failure under tensile loading and high-stress cyclic loading, largely due to excessive thinning of the AA6016 alloy. In contrast, the AA6016-to-coated DP800 steel joints welded at 500 J showed adhesive failure caused by defects at the weld interface. However, at a welding energy of 1250 J, these joints demonstrated superior intermixing between the Al sub-layer of PVD coating and the AA6016 alloy, resulting in a combination of cohesive and adhesive failure modes. The findings reveal the effectiveness of the AlSi(Fe) PVD coating in improving the mechanical properties of the joints while enhancing the energy efficiency of the welding process. • A novel AlSi(Fe) PVD coating with nearly pure Al enables AA6016-to-DP800 welding. • The outer Al sub-layer enhances thermophysical similarity between Al and steel. • Joints made at ∼1250 J without intermetallic formation exceed AWS D17.2 standards. • Optimal joints show mixed failure modes and superior coating-AA6016 intermixing. • Effect of PVD coating on the transition of failure mechanisms is explicated.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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