Mechanisms of rhyolitic glass hydration below the glass transition
Bibliographic record
Abstract
Although a great deal is known about the interaction between water and rhyolitic glasses and melts at temperatures above the glass transition, the nature of this interaction at lower temperatures is much more obscure. Comparisons between high- and low-temperature diffusion studies suggest that several factors play important roles under lower-temperature conditions that are not significant at higher temperatures. Water concentrations in rhyolitic glasses hydrated at low temperatures are significantly greater than in those hydrated at high temperatures and low pressures. Surface concentrations, which equilibrate quickly with the surrounding environment at high temperature, change far more slowly as temperature decreases, and may not equilibrate at room temperature for hundreds or thousands of years. Temperature extrapolations of high- and low-temperature diffusion data are not consistent, suggesting that a change in mechanism occurs. These differences may be due to the inability of “self-stress,” caused by the in-diffusing species, to relax at lower temperature. Preliminary calculations suggest that the level of stress caused by glass-water interaction may be greater than the tensile strength of the glass. On a microstuctural scale, extrapolations of high-temperature Fourier transform infrared spectroscopy (FTIR) data to lower temperatures suggests that there should be little or no hydroxyl present in glasses hydrated at low temperature. Comparisons of low-temperature hydration results among SiO 2 , obsidian, and albite compositions show distinct differences, and features are present in the spectra that do not occur at high temperature. Analysis of H 2 O and D 2 O diffusion also suggest that mechanistic differences occur between low- and high-temperature diffusive processes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".