Single Molecule Tracking Studies of Flow-Aligned Mesoporous Silica Monoliths: Aging-Time Dependence of Pore Order
Bibliographic record
Abstract
Single molecule tracking (SMT) methods are employed to characterize the in-plane alignment and order of cylindrical mesopores in flow-aligned surfactant-templated silica monoliths prepared within glass microfluidic channels. The majority of dye molecules observed in wide-field fluorescence videos of these samples exhibit one-dimensional (1D) diffusive motions. Orthogonal regression analysis of these motions provides a measure of the mesopore orientation distribution function, which in turn is used to quantify the mesopore order via a two-dimensional orientational order parameter, . Mesopore organization is explored as a function of aging time between sol preparation and filling of the microfluidic channels. Channels filled well before gelation of the sol are shown to incorporate large monodomains having average pore alignment within a few degrees of the flow direction. These monodomains extend over several millimeters and yield aging-time-independent values larger than ~0.80. In contrast, channels filled near the time of sol gelation yield monoliths with misaligned pores that are also more disordered, having ≈ 0.35. The SMT results are compared to those from small-angle X-ray scattering anisotropy experiments; these data are consistent across the range of samples investigated. A model describing the aging-time dependence of sol organization is presented. These studies demonstrate that well-aligned mesoporous silica monoliths can be obtained by simple flow alignment procedures but that short sol aging times are required in order to achieve optimum pore organization.
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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) | 0.000 | 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".