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Record W4410799319 · doi:10.1016/j.rineng.2025.105532

Effect of particle size distribution on the sidewall surface roughness of AlSi10Mg parts manufactured by laser powder bed fusion

2025· article· en· W4410799319 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

VenueResults in Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceFusionParticle-size distributionSurface roughnessParticle sizeSurface finishSurface (topology)Particle (ecology)LaserComposite materialOpticsGeometryGeologyMathematicsPhysics

Abstract

fetched live from OpenAlex

The sidewall surface roughness is believed to be caused by unmelted or partially melted powders adhering to the meltpool, and thus can be linked to the particle size distribution (PSD) and apparent density of the feedstock. This study reports the effect of PSD, apparent density and sidewall coordination number on sidewall surface roughness from metal Laser Powder Bed Fusion (LPBF) processing. A series of thin walls were fabricated using four different AlSi10Mg alloy powders to investigate this correlation. The results indicate that a large powder size (D 10 , D 50 , D 90 of 74, 82, and 104 µm, respectively) combined with a narrow PSD (S w of 4.28) reduces the number of contacts with the sidewall, thereby decreasing the number of particles attached to the surface, resulting in the reduction of the surface roughness parameters, S a, and S q , by up to 43.4 % and 24.8 % respectively. This work advances the understanding of the factors driving surface roughness in LPBF and demonstrates that the usage of a proper PSD can significantly improve surface quality in metal AM processes.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.207
Teacher spread0.204 · 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