Thermodynamic functions of water and ice confined to 2nm radius pores
Bibliographic record
Abstract
The heat capacity C(p) of the liquid state of water confined to 2 nm radius pores in Vycor glass was measured by temperature modulation calorimetry in the temperature range of 253-360 K, with an accuracy of 0.5%. On nanoconfinement, C(p) of water increases, and the broad minimum in the C(p) against T plot shifts to higher temperature. The increase in the C(p) of water is attributed to an increase in the phonon and configurational contributions. The apparent heat capacity of the liquid and partially frozen state of confined water was measured by temperature scanning calorimetry in the range of 240-280 K with an accuracy of 2%, both on cooling or heating at 6 K h(-1) rate. The enthalpy, entropy, and free energy of nanoconfined liquid water have been determined. The apparent heat capacity remains higher than that of bulk ice at 240 K and it is concluded that freezing is incomplete at 240 K. This is attributed to the intergranular-water-ice equilibrium in the pores. The nanoconfined sample melts over a 240-268 K range. For 9.6 wt % nanoconfined water concentration ( approximately 50% of the maximum filling) at 280 K, the enthalpy of water is 81.6% of the bulk water value and the entropy is 88.5%. For 21.1 wt % (100% filling) the corresponding values are 90.7% and 95.0%. The enthalpy decrease on nanoconfinement is a reflection of the change in the H-bonded structure of water. The use of the Gibbs-Thomson equation for analyzing the data has been discussed and it is found that a distribution of pore size does not entirely explain our results.
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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 | 0.000 | 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".