Nanostructured Temperature Indicator for Cold Chain Logistics
Bibliographic record
Abstract
Food, chemicals, agricultural products, drugs, and vaccines should be transported and stored within an appropriate low-temperature range, following cold chain logistics. Violations of the required temperature regime are generally reported by time-temperature indicators; however, current sensors do not cover a sufficiently broad low-temperature range and may lack thermal and photostability. Here, we report a nanostructured solvatochromic temperature indicator formed from cellulose nanocrystals decorated with carbon dots (C-dots). The indicator utilizes a strong nonlinear dependence of photoluminescence of C-dots on the composition of water/dimethyl sulfoxide (DMSO) solvent and a composition-dependent variation of the melting temperature of the water/DMSO mixture. Exceeding the temperature of the frozen mixed solvent above a designated threshold value results in solvent melting, flow, and impregnation of the nanostructured film, thus causing an irreversible change in the intensity and wavelength of photoluminescence emission of the film, which is reported both qualitatively and quantitatively. The indicator covers a temperature range from -68 to +19 °C and is cost-efficient, portable and photo- and thermostable.
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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 | 0.000 |
| 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".