Hydrogen induced superhydrophilicity in an amorphous CrFeNi-based multi-principal element alloy thin film
Bibliographic record
Abstract
The compelling nature of the highly adapted functional surface structures found in biological systems accompanied by delicately tuned chemical processes, has inspired the design of materials with varied wetting properties and a vast range of applications. Identifying relations between surface structure, chemistry and wettability, is pivotal towards the mechanistic understanding of wetting phenomena. Here we demonstrate how electrochemically driven hydrogen adsorption/absorption induces, irreversibly, a superhydrophilic state in an amorphous CrFeNi-based multi-principal element alloy thin film with close to equimolar composition, i.e., in the class of medium/high entropy alloys. By employing films with sub-nanometer roughness to exclude the influence of geometry on wetting, we show that both the extent of wetting and its dynamics are governed by the rate of the underlying electrochemical reactions. The absorption of hydrogen into the matrix of the amorphous films as proved by thermal desorption spectroscopy, is proposed to partially protonate the electrochemically resilient Ta and Cr surface oxides through a hydrogen spillover phenomenon initiated by the adsorption of hydrogen on the electrochemically reduced Fe sites. Furthermore, atom probe tomography measurements reveal Cr segregation at the outermost surface layers of the film following cathodic treatment. The above processes strongly influence surface energetics resulting in the transition from a mildly hydrophilic state to an ultra-high substrate surface energy regime. Our work establishes a previously unknown physicochemical link between multi-principal element-alloys – hydrogen interactions and surface wettability, that is of significance in frontline research areas spanning electrochemical energy conversion/storage and catalysis to materials degradation and liquids actuation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 teacher head, 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".