Nanoscale Visualization and Contact Angle Analysis of Water Droplets on Ferroelectric Materials
Bibliographic record
Abstract
Understanding wetting phenomena at the nanoscale is essential for evaluating interfacial properties of functional materials. However, conventional contact angle measurements lack the resolution required to capture nanoscopic features, while existing nanoscale approaches remain technically complex or indirect. Here, we present a direct visualization method using noncontact atomic force microscopy (AFM) combined with temperature-controlled condensation and pixel-wise contact angle mapping. By inducing the spontaneous formation of stable water droplets on hydrophilic surfaces through controlled stage cooling, we achieve high-resolution imaging and quantitative analysis of contact angles. Applying this method to ferroelectric lithium tantalate (LiTaO 3 ), we reveal a polarization-dependent contact angle difference at the nanoscale, undetectable by conventional macroscopic sessile methods. We further demonstrate the broader applicability of this approach by visualizing nanoscale water droplets on individual submicron nickel–iron layered double hydroxide (NiFeLDH) catalyst particles. This methodology enhances the precision and generalizability of nanoscale wetting characterization and opens further possibilities for interfacial analysis across a wide range of functional materials.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".