Wetting in Color: Colorimetric Differentiation of Organic Liquids with High Selectivity
Bibliographic record
Abstract
Colorimetric litmus tests such as pH paper have enjoyed wide commercial success due to their inexpensive production and exceptional ease of use. Expansion of colorimetry to new sensing paradigms is challenging because macroscopic color changes are seldom coupled to arbitrary differences in the physical/chemical properties of a system. Here we present in detail the design of a "Wetting In Color Kit" (WICK), an inexpensive and highly selective colorimetric indicator for organic liquids that exploits chemically encoded inverse-opal photonic crystals to project minute differences in liquids' wettability to macroscopically distinct, easy-to-visualize structural color patterns. We show experimentally and corroborate with theoretical modeling using percolation theory that the highly symmetric structure of our large-area, defect-free SiO(2) inverse-opal films leads to sharply defined threshold wettability for liquid infiltration, occurring at intrinsic contact angles near 20° with an estimated resolution smaller than 5°. The regular structure also produces a bright iridescent color, which disappears when infiltrated with liquid, naturally coupling the optical and fluidic responses. To deterministically design a WICK that differentiates a broad range of liquids, we introduced a nondestructive quality control procedure to regulate the pore structure and developed two new surface modification protocols, both requiring only silanization and selective oxidation. The resulting tunable, built-in horizontal and vertical chemistry gradients let us tailor the wettability threshold to specific liquids across a continuous range. With patterned oxidation as a final step, we control the shape of the liquid-specific patterns displayed, making WICK easier to read. Using these techniques, we demonstrate the applicability of WICKs in several exemplary systems that colorimetrically distinguish (i) ethanol-water mixtures varying by only 2.5% in concentration; (ii) methanol, ethanol, and isopropyl alcohol; (iii) hexane, heptane, octane, nonane, and decane; and (iv) samples of gasoline (regular unleaded) and diesel. As wetting is a generic fluidic phenomenon, we envision that WICK could be suitable for applications in authentication or identification of unknown liquids across a broad range of industries.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".