(Invited) In-Situ Liquid Phase TEM Studies of Corrosion Initiation in Aluminium Alloys
Bibliographic record
Abstract
Aluminium alloy 2024-T3 (AA2024-T3), widely applied in aerospace industries, may suffer from severe localized corrosion as a result of its relatively complex and heterogeneous microstructure. The corrosion initiation in such a critical alloy is governed by dynamic processes that take place at the nanoscale. A thorough understanding of the sequential stages of corrosion initiation is of pivotal importance to developing efficient inhibition strategies and demands high resolution techniques along with the ability of real-time recording of nanoscopic events. However, to date, it has not yet been possible to unambiguously show the morphological and electrochemical characteristics during local corrosion of AA2024-T3. In particular, local corrosion initiation linked to nano-/microstructural heterogeneities, intermetallic particles (IMPs), take place relatively fast and at the nanoscopic scale, rendering the study of the early stages of corrosion experimentally virtually impossible until now. Herein, we show, for the first time, the dynamic evolution of site-specific local corrosion of AAs from early surface initiation to depth propagation at the nanoscale using a dedicated in-situ liquid phase-transmission electron microscopy (LP-TEM) experimental facility. Transmission electron microscopy (TEM), capable of revealing microstructural and compositional variations in alloys at atomic and nanoscopic scale, has been applied widely in corrosion studies but mostly ex-situ and quasi in-situ. These approaches are not straightforward as artefacts and contaminations might be introduced into the system during the ex-situ and quasi in-situ experiments, including dehydration of surfaces and therefore may not fully represent the real conditions. With recent technological advances, thanks to the development of dedicated microelectronic mechanical systems (MEMS), it is now possible to fabricate components like nanoreactors (NRs) to study complicated corroding systems at the nanoscale in-situ. In fact, NRs employed in TEM studies enable to monitor morphological and compositional evolutions in materials in-situ as a result of interaction with aggressive environments like a gas or liquid. In this study, we put efforts into providing direct evidence for the nanoscopic role of intermetallics in AA2024-T3 localized corrosion through quasi in-situ TEM and in-situ LP-TEM approaches. Quasi in-situ studies were implemented by intermittently exposing the Argon ion-milled thin samples to 0.01 M NaCl solution. For in-situ LP-TEM, the real TEM specimens (lamellae) were first fabricated out of regions of interest with a FEI Helios focused ion beam. Then, the lamellae were transferred successfully to home-made NRs using an easy-lift technique. The NRs, equipped with an electrochemical set-up, were specially designed for corrosion studies. A Cs-corrected FEI Titan TEM was employed to perform real-time studies in scanning TEM (STEM) mode. Although a good resolution is still a major challenge for in-situ LP-TEM, the results revealed that intermetallic phases regardless of their types are active and prone sites to localized corrosion attack themselves and the observations finally show and elucidate initial stages of IMP-induced pitting corrosion and copper redistribution mechanisms in AA2024-T3.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".