Revealing Silica's pH-Dependent Second Harmonic Generation Response with Overcharging
Bibliographic record
Abstract
Isolating the contribution of the silica in second harmonic generation (SHG) studies at the silica/water interface remains a challenge. Herein, we compare SHG intensities with previously measured zeta potentials and vibrational sum frequency generation (vSFG) intensities to deconvolute the silica contribution in the SHG measurements. Under conditions that promote overcharging, the zeta potential and the vSFG measurements follow a similar trend, however, SHG yields the opposite behaviour. The results can only be rationalized by considering a significant pH dependent increase in the silica contribution. Using a simplistic, yet physically motivated model, we demonstrate that silica can interfere either constructively or destructively with water. By computing the hyperpolarizabilities of neutral and deprotonated silica clusters with density functional theory (CAM-B3LYP/6-31+G(d,p)), we reveal that one potential source of this pH-dependent response of silica is a change in the hyperpolarizability upon the deprotonation of surface sites suggesting SHG is directly sensitive to surface charging of mineral oxides.
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 | 0.001 |
| 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".