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Record W4285398947 · doi:10.1149/ma2022-01251217mtgabs

A Study on Electrochemical Polishing of Additively Manufactured Ti6Al4V Complex Parts and Its Influence on Corrosion Behavior

2022· article· en· W4285398947 on OpenAlexaff
Shamim Pourrahimi, Lucas A. Hof

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsPolishingMaterials scienceAbrasiveTitanium alloyRaw materialFabricationCorrosionMetallurgySurface roughnessSurface finishComposite materialAlloy

Abstract

fetched live from OpenAlex

Nowadays, metal additive manufacturing (AM) has become popular for creating complex geometries that are impossible to create with conventional manufacturing methods. However, the surface quality of as-built AM parts is typically not (uniformly) smooth. Among different imperfections leading to irregular surface morphology, we can mention the staircase effect due to the layer-by-layer nature of the deposition techniques, partially fused feedstock material, balling effects, spatter, and inadequate fusion, where each impact on surface finish depends on the deployed AM process method. Typically, the surface quality of an as-built part is not satisfactory for functional biomedical applications. To address this issue, many research studies are focusing on optimizing part production variables, such as feed stock material, design of the part, AM process parameters and condition of fusion deposition and binding. However, in most cases, to meet the final part requirements, post-processing after AM production is necessary. Different post-processing methods such as abrasive polishing, laser polishing, chemical etching, and electrochemical polishing are established over the years. Among others, electrochemical polishing (ECP) is a suitable post-processing method for metal additive manufactured parts, particularly those with complicated geometry and inaccessible surfaces such as lattice structures. Titanium and its alloys are commonly used in biomedical applications because of their fracture toughness, corrosion resistance, and biocompatible properties, as well as their fatigue strength. Therefore, Ti-6Al-4V is selected as AM feedstock material for lattice structure fabrication in this work. The principal objectives of this study are 1) to characterize the surface of the lattice structure’s struts to observe the influence of post-processing on the core of the lattice and ensure achieving a uniform lattice structure; and 2) to study the influence of electrochemical polishing (ECP) on corrosion behavior of AM lattice structures as well as on AM flat surfaces. In a first step (Figure 1a), the best ECP condition, based on a Taguchi method design of experiment (DOE), on a flat additively manufactured titanium surface is established. The applied potential, electrochemical polishing time, and the electrode distance (the distance between working and counter electrode) are considered as the ECP parameters in the DOE, and for each parameter two levels are considered. Therefore, four experiments are designed, and two samples are polished for each experiment. In order to observe the effect of each experiment, a Confocal characterization is performed (Figure 1b), and based on the results, the experiment with the highest improvement in roughness is selected to polish a part with lattice-like structure (Figure 1C). In a second step, it is necessary to characterize the internal struts of the lattice structures to observe the influence of post-processing on the core of the lattice and ensure achieving a uniform lattice structure after ECP. This can be accomplished by cutting the part followed by profilometry or confocal microscopy, which are destructive methods. As a non-destructive method, X-ray computed tomography (XCT) can be used to asses the internal parts of a lattice structure. However, in most literature, it is used as a qualitative tool to evaluate the uniformity of lattice structure after post-processing. In this study, the XCT output are analyzed using a novel method, which could quantitatively measure the surface roughness of internal struts and assess its improvement by ECP, in a non-destructive manner. In spite of the fact that corrosion resistance of lattice structure AM parts is important for many practical applications, few studies specifically report corrosion rates before and after post-processing of AM lattice parts. In this paper the influence of ECP on corrosion behavior of AM lattice structures and AM plane surfaces are studied. To evaluate the impact of ECP on the corrosion behavior of AM parts, linear polarization is conducted to measure both the corrosion potential and corrosion rate (Figure 1d). According to the obtained results, the highest improvement of in surface roughness is obtained in the second experiment (sample P03, P04), which contains the higher level in each parameter (20 min polishing time and 20V applied voltage). By ECP of the Ti-6Al-4V AM surface, we have proven that we can decrease the arithmetic mean surface roughness value - S a – by 70%. Using the ECP process, we reduced the initial roughness of 12.3 μm to a polished surface of 3.5 μm. Further experiments are being conducted on the ECP of lattice structures and the evaluation of their corrosion behavior. Figure 1

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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 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 score0.171
Threshold uncertainty score0.926

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 head0.023
GPT teacher head0.249
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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