The influence of modifier cations on the Raman stretching modes of Q <i> <sup>n</sup> </i> species in alkali silicate glasses
Bibliographic record
Abstract
Abstract The Raman spectra of alkali silicate glasses containing 5 to 30 mol % M 2 O (M = Li, Na, K, Rb, and Cs) have been fit successfully with pseudo‐Voigt lineshapes of dominantly Lorentzian character in order to quantify the Q n species distributions. This differs from the more popular Gaussian lineshapes which have been used for the past four decades. There is an increase in asymmetry in the Q 3 band, with increasing M 2 O content which appears to result from the weakened Si‐O force constants of some Q 3 bands due to charge transfer via M‐BO bonds. With charge transfer to the tetrahedra, the negative charge accumulates preferentially on Si atoms thus decreasing Si‐O Coulombic interactions, weakening Si‐O force constants, and shifting the Q n A 1 symmetric stretch vibrational frequencies to lower values (eg, from ∼1100 cm −1 to ∼1050 cm −1 ). The fraction of affected Q 3 species increases with alkali content, as does the Q 3 peak asymmetry. We propose that this extends through to all the Q n species and postulate that there are multiple vibrational modes for each Q n species which are dictated by their proximity to network modifier cations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".