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Record W4400933113 · doi:10.1108/rpj-04-2024-0163

Sintering parameter investigation for bimetallic stainless steel 316L/inconel 718 composite printed by dual-nozzle fused deposition modeling

2024· article· en· W4400933113 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.

Bibliographic record

VenueRapid Prototyping Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Waterloo
FundersNational Science and Technology CouncilNational Taipei University of TechnologyMinistry of Education, India
KeywordsMaterials scienceInconelSinteringComposite materialComposite numberThermoplasticInconel 625PorosityBimetallic stripAlloyMetallurgyMetal

Abstract

fetched live from OpenAlex

Purpose Fused deposition modeling (FDM) nowadays offers promising future applications for fabricating not only thermoplastic-based polymers but also composite PLA/Metal alloy materials, this capability bridges the need for metallic components in complex manufacturing processes. The research is to explore the manufacturability of multi-metal parts by printing green bodies of PLA/multi-metal objects, carrying these objects to the debinding process and varying the sintering parameters. Design/methodology/approach Three different sample types of SS316L part, Inconel 718 part and bimetallic composite of SS316L/IN718 were effectively printed. After the debinding process, the printed parts (green bodies), were isothermally sintered in non-vacuum chamber to investigate the fusion behavior at four different temperatures in the range of 1270 °C−1530 °C for 12 h and slowly cooled in the furnace. All samples was assessed including geometrical assessment to measure the shrinkage, characterization (XRD) to identify the crystallinity of the compound and microstructural evolution (Optical microscopy and SEM) to explore the porosity and morphology on the surface. The hardness of each sample types was measured and compared. The sintering parameter was optimized according to the microstructural evaluation on the interface of SS316L/IN718 composite. Findings The investigation indicated that the de-binding of all the samples was effectively succeeded through less weight until 16% when the PLA of green bodies was successfully evaporated. The morphology result shows evidence of an effective sintering process to have the grain boundaries in all samples, while multi-metal parts clearly displayed the interface. Furthermore, the result of XRD shows the tendency of lower crystallinity in SS316L parts, whilst IN718 has a high crystallinity. The optimal sintering temperature for SS316L/IN718 parts is 1500 °C. The hardness test concludes that the higher sintering temperature gives a higher hardness result. Originality/value This study highlights the successful sintering of a bimetallic stainless steel 316 L/Inconel 718 composite, fabricated via dual-nozzle fused deposition modeling, in a non-vacuum environment at 1500 °C. The resulting material displayed maximum hardness values of 872 HV for SS316L and 755.5 HV for IN718, with both materials exhibiting excellent fusion without any cracks.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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