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Enhancing passivity and corrosion resistance of laser-powder bed fused maraging stainless steel CX through TiC-induced microstructure tailoring

2025· article· en· W4409166495 on OpenAlexafffund
Khashayar Morshed-Behbahani, Nika Zakerin, Elham Afshari, D.P. Bishop, Kevin P. Plucknett, Ali Nasiri

Bibliographic record

VenueColloids and Surfaces A Physicochemical and Engineering Aspects · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsDalhousie University
FundersDalhousie UniversityNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsOcean Frontier InstituteCanada Foundation for Innovation
KeywordsMicrostructurePassivityMaterials scienceMaraging steelMetallurgyCorrosionWear resistanceLaser

Abstract

fetched live from OpenAlex

Maraging stainless steel Corrax® (also known as SS CX) can be successfully processed using the laser powder bed fusion (L-PBF) technology. However, the fabricated alloy exhibits anisotropic properties due to the formation of columnar grains along the build direction. While heat treatment can partially address this issue, it cannot fully eliminate it and adds an additional post-processing step to the manufacturing cycle. This research explores the strategic addition of TiC particles as an effective inoculant to refine the microstructure of L-PBF SS CX and investigates the influence of these microstructural changes on its corrosion performance—an area yet to be explored in existing literature. TiC particles were incorporated into the initial SS CX powder feedstock at 1 wt% and 2 wt% concentrations, and the results were compared to those of the non-inoculated alloy. The addition of TiC inoculants effectively refined the grain structure and promoted the formation of a duplex microstructure comprising martensite and austenite in the inoculated alloys. Specifically, the proportion of the smallest grains ( ≤ 2 μm) increased significantly, rising from 24.6 % in the SS CX sample with 1 wt% TiC to 29.3 % in the SS CX sample with 2 wt% TiC. This grain refinement significantly reduced corrosion susceptibility and enhanced the overall corrosion resistance of the alloy. In this context, the charge transfer resistance of 2.8 × 10 6 Ω·cm 2 observed for L-PBF SS CX increased by 18 % and 71 % in samples containing 1 wt% and 2 wt% TiC, respectively. Similarly, the corrosion current densities of the L-PBF SS CX samples with 1 wt% and 2 wt% TiC were one and two orders of magnitude lower, respectively, than those of the non-inoculated counterpart. Moreover, the refined microstructure facilitated the formation of a more uniform and defect-free passive film, further improving the corrosion resistance of TiC-inoculated L-PBF SS CX.

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 categoriesMeta-epidemiology (narrow)
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 score0.003
Threshold uncertainty score1.000

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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.

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

Citations6
Published2025
Admission routes2
Has abstractyes

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