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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Coating thickness can change what surface roughness means for pitting corrosion because the two variables interact. In a 2026 study of steam-grown boehmite on A6061-T6 aluminum, that modeled interaction changed sign near a film thickness of about 2,200 nm for specimens whose root-mean-square roughness (SQ) was approximately 600–1,080 nm. The result does not establish a universal 2,200 nm limit or show that every thicker coating performs worse.
The finding is specific to the coating, aluminum alloy, roughness range, chloride test and statistical model used. It suggests that roughness associated with developing protective coverage at lower thicknesses may instead mark structural irregularities and transport paths at greater thicknesses, but that explanation remains a hypothesis requiring direct experimental validation.
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What the 2026 aluminum study actually found
A team led by Professor Takahiro Ishizaki at Shibaura Institute of Technology analyzed 90 steam-coated A6061-T6 aluminum specimens. Steam treatment grows a boehmite film, an aluminum oxyhydroxide layer, on the alloy surface. The researchers modeled pitting resistance using four descriptors:
- Film thickness (FT): the thickness of the boehmite layer.
- Surface morphology (SQ): root-mean-square surface height, used as the study’s roughness metric.
- Crystallite size (CS): a structural descriptor of the film.
- Substrate dislocation-density index (FS): an index representing defects in the aluminum beneath the film.
They used random-forest modeling with SHAP (Shapley additive explanations) and accumulated local effects to examine how those descriptors related to pitting potential. The report says the results were published online in npj Materials Degradation on 18 August 2026.
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Pitting resistance in this work means the pitting potential measured in a 5 wt.% sodium chloride solution at room temperature. A higher pitting potential indicates that the specimen resisted pit initiation to a greater potential under those particular test conditions. The numbers below therefore cannot be transferred directly to seawater, another chloride concentration, a different temperature or another coating chemistry.
The interaction reversal
Film thickness and SQ were the leading descriptors in the model. Among specimens with SQ of approximately 600–1,080 nm, the modeled interaction between roughness and thickness changed from positive to negative near FT ≈ 2,200 nm. In the lower-roughness range, the same reversal was not observed.
An interaction is not the same as a stand-alone thickness effect. The result means that the relationship between roughness and the predicted pitting potential depended on how thick the film was. It does not mean that a specimen above 2,200 nm automatically has lower pitting resistance, nor that a specimen below that value is automatically protected.
What the sign change means statistically
Imagine plotting predicted pitting potential against SQ at several fixed thicknesses. If the slope is positive at one thickness, greater SQ is associated with a higher prediction in that slice of the model. If the slope becomes negative at another thickness, greater SQ is associated with a lower prediction there. The point where that modeled relationship changes direction is an interaction transition, not a physical switch built into every boehmite film.
Because the transition was identified in a finite set of 90 specimens, it should be treated as a feature of this dataset and model. The report does not provide a general threshold applicable to other aluminum alloys, other oxide or polymer coatings, or other roughness distributions.
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Why thickness can alter the role of roughness
Early growth: roughness may track protective coverage
One interpretation proposed by the authors is that, while the boehmite film is relatively thin, surface roughness may reflect how the film develops over the underlying aluminum. Features that increase SQ could coincide with more complete or otherwise protective coverage during an earlier growth stage. In that situation, roughness and corrosion resistance could appear positively related within part of the thickness range.
This is a model-supported explanation, not a demonstrated mechanism. The statistical analysis identifies a changing association; it does not show that a particular peak or valley caused a measured improvement in barrier performance.
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At greater thickness, the same roughness could instead be associated with structural irregularities. Peaks, valleys, pores or poorly covered regions can create longer or less uniform routes through which water and chloride ions move. If a defect reaches the aluminum or connects with the metal–film interface, localized electrochemical attack can become easier to sustain. Under that interpretation, increasing SQ at larger FT would be associated with a lower predicted pitting potential.
The study authors explicitly say that this coverage-to-irregularity interpretation needs further experimental testing. It should not be presented as proven causality or as a rule that thick films are intrinsically defective.
How pitting starts in a rough coated surface
Pitting is a localized corrosion process. Instead of dissolving uniformly, a small anodic site on the aluminum becomes chemically and electrochemically different from the surrounding surface. Chloride can stabilize that active site, while the confined pit environment becomes increasingly aggressive.
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A coating can delay pit initiation by blocking electrolyte access, increasing the distance ions must travel, or maintaining a stable interface. Roughness affects each route in several competing ways:
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- High spots may be difficult to cover uniformly, leaving thin spots or pinholes.
- Deep valleys can retain solution and be difficult to rinse or dry.
- Connected surface features can shorten transport paths through the film.
- A controlled profile can improve mechanical interlocking or increase the effective area covered by a barrier.
- Profile shape, not just a single roughness amplitude, can determine whether defects connect to the metal.
That is why the same numerical roughness can have different corrosion consequences in different coating systems. SQ is a useful summary statistic, but it does not describe spacing, skewness, peak sharpness, valley depth or whether defects form a connected network.
What the model says about accuracy and uncertainty
The report states that the descriptor-based model predicted corrosion resistance more accurately than a model using only coating temperature and treatment time. Its reported root-mean-square error was 0.292 V. A Monte Carlo analysis estimated that uncertainty in measuring the descriptors contributed approximately 0.080 V to prediction variability.
Those figures characterize this model and its 90-specimen dataset. They are not a general corrosion error bar, a guaranteed field accuracy or a substitute for electrochemical testing. Measurement uncertainty matters especially near a modeled transition: if FT or SQ is measured with enough error, the apparent location or sharpness of a sign change can move.
How to interpret the 2,200 nm figure correctly
The reported value is best read with all of its conditions attached:
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| Element | Qualification |
|---|---|
| Material | A6061-T6 aluminum with a steam-grown boehmite film |
| Specimens | 90 samples analyzed in the 2026 Shibaura Institute of Technology study |
| Roughness metric | SQ, root-mean-square surface height |
| Roughness range showing the reversal | Approximately 600–1,080 nm SQ |
| Thickness near the modeled sign change | Approximately 2,200 nm FT |
| Corrosion measurement | Pitting potential in 5 wt.% sodium chloride at room temperature |
| Meaning of the value | A modeled change in the roughness–thickness interaction, not a universal critical thickness |
For a new coating, the appropriate question is not “Is its thickness above 2,200 nm?” The useful question is whether its own thickness, profile and chemistry produce a similar interaction under a comparable corrosion test.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why roughness alone cannot predict coating protection
Transport through the coating
A review of surface-profile effects describes one attack route as transport through the coating itself. Water, oxygen and aggressive ions can move through pores, cracks, thin regions or other defects. A rough profile may increase the number of locations that need complete coverage, but the outcome depends on how the coating conforms to that profile.
Lateral attack at the interface
A second route begins when a defect exposes the metal. Corrosion can then spread laterally along the metal–coating interface. A coating that appears intact from above may still fail if adhesion is weak or if an interconnected defect network allows underfilm corrosion.
Profile shape and cleaning
Greater roughness can improve mechanical interlocking for some polymer barriers, yet very rough surfaces may be difficult to clean. Residue in valleys, sharp peaks and inaccessible recesses can prevent uniform coverage. The review therefore cautions that roughness effects are not straightforward.
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A 2019 study of machined, epoxy-coated steel found that roughness magnitude alone did not explain coating stability; profile shape and mechanical interlocking also mattered. Those results apply to that steel-and-epoxy system, not to steam-coated aluminum.
A separate 2026 study of CrAlN-coated H13 steel found that reducing substrate roughness improved corrosion indicators under its test conditions while reducing measured coating critical load. That trade-off illustrates why adhesion and corrosion can respond differently to the same surface preparation. It is not direct evidence for boehmite films.
A practical workflow for evaluating a new coating
Engineers comparing thickness and roughness should keep the variables and measurements aligned rather than borrowing a threshold from another material.
- Define the system. Record the substrate alloy, heat treatment, coating chemistry, deposition or conversion process and any sealing or post-treatment.
- Measure thickness at multiple locations. Report the method, calibration and distribution, not only a nominal average. A mean thickness can conceal thin spots that control pit initiation.
- Measure roughness with a defined metric. State whether the value is RMS height, arithmetic average roughness or another parameter. For the aluminum study, the relevant metric is SQ.
- Describe the profile. Add peak and valley information, spacing, skewness or images where possible. Two surfaces with the same SQ can have very different defect connectivity.
- Test in the intended environment. Specify chloride concentration, temperature, exposure time, aeration and electrochemical procedure. Pitting potential in room-temperature 5 wt.% sodium chloride is not interchangeable with a service environment.
- Separate association from mechanism. Use modeling to identify interactions, then test proposed causes with cross-sectional microscopy, surface mapping, permeability or localized electrochemical measurements.
- Validate outside the training data. Hold out specimens or use a separate production batch. A transition found only in one dataset may reflect sampling, measurement noise or an unmeasured process variable.
Common mistakes when applying the finding
- Turning 2,200 nm into a universal limit: the value belongs to one boehmite-on-A6061-T6 dataset and one model.
- Reading the interaction as an overall thickness trend: a sign change in the roughness effect does not prove that all thicker specimens have lower pitting potentials.
- Dropping the SQ definition: RMS surface height is not interchangeable with every roughness parameter.
- Ignoring the roughness range: the reported reversal occurred in approximately 600–1,080 nm SQ specimens and was not observed in the lower-roughness range.
- Claiming causation from feature importance: SHAP and accumulated-local-effects analyses explain model behavior; they do not by themselves establish ion transport through a specific defect.
- Comparing unlike systems: polymer-coated steel, hard nitride coatings and steam-grown boehmite have different chemistry, adhesion and defect structures.
- Overlooking measurement uncertainty: the reported approximately 0.080 V contribution from descriptor-measurement uncertainty can matter when predicted differences are small.
What remains unanswered
The study establishes a useful conditional pattern but leaves several engineering questions open. Direct experiments are needed to determine whether changing film thickness while holding the same surface profile causes the interaction reversal, or whether thickness also changes crystallite structure, porosity and interface quality. It is also necessary to test whether the pattern persists under cyclic wetting, different chloride concentrations, elevated temperatures and longer exposures.
Additional work should examine the region-dependent interaction reported between roughness and crystallite size. That interaction may help distinguish a purely geometric effect from a coupled change in film structure. Cross-sectional electron microscopy, confocal laser scanning microscopy and X-ray diffraction can characterize such changes, but the report does not identify any particular instrument as a recommended product.
Bottom line for design decisions
Thickness does not assign a fixed good-or-bad value to surface roughness. In steam-grown boehmite on A6061-T6 aluminum, the modeled influence of SQ changed with FT, with a sign reversal near 2,200 nm only in the approximately 600–1,080 nm roughness range. Treat that number as a study-specific interaction marker. For any other coating, measure the complete surface profile, test pitting under the relevant environment and validate the proposed mechanism instead of importing the threshold.
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