Direct Writing Unclonable Watermarks with an Electrochemical Jet
Bibliographic record
Abstract
Abstract Counterfeit parts result in significant losses per annum and are often dangerous, therefore they represent a serious concern for manufacturers and end users alike. Easily written but unclonable watermarks undermine the proposition of the counterfeiter. Here, a rapid electrochemical jet engraving routine is presented to encode robust materials with self‐organized dendritic structures at length scales that can be imaged with a smartphone. Surface defects act as stochastically distributed seeds from which discrete pitting events can be propagated by translating the electrochemical field. While the vascular pathways can be directly written at the macro scale, the formation and propagation of microscale dendritic arms is chaotic, caused by the implicit randomness of the defect seeds and the supply of ions to the surface. The latter is confounded by random perturbations in the flow condition. Each engraved dendrite is unique, stable at high temperature (>500 °C) and can be subjected to rapid image recognition to allow individual mark identification at any point during part production and delivery, or through part lifetime.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".