Simple Self-Powered Sensor for the Detection of D<sub>2</sub>O and Other Isotopologues of Liquid Water
Bibliographic record
Abstract
Distinguishing between heavy water and regular water has been a continuing challenge since these isotopologues of water have very similar physical and chemical properties. We report the development and evaluation of a simple, inexpensive sensor capable of detecting liquid D 2 O and other isotopologues of liquid water through the measurement of electrical signals generated from a nanoporous alumina film. This electrical output, consisting of a sharp voltage pulse followed by a separate broad voltage pulse, is present during the application of microliter volumes of liquid. The amplitude and temporal characteristics of these pulses have been combined to enable four diagnostic parameters for sensing D 2 O and H 2 18 O. The sensing mechanism is based on different modification effects on the alumina surface by H 2 O and D 2 O, spatially localized variations in the surface potential of alumina induced by isotopically substituted water molecules, combined with the effect of isotopic composition on charge transfer. As a proof-of-concept demonstration, a sensing system has been developed that provides real-time detection of liquid D 2 O in a stand-alone system.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".