Measurement of Desorption Rates from Octadecylsilyl Bonded-Phase HPLC Particles and Its Characterization in Terms of Pore, Surface, and Film Diffusion
Bibliographic record
Abstract
An instrument is developed to measure rates of desorption of solutes from particulate HPLC packing materials for processes that are quantitatively complete in a few tenths of a second. The instrument is a modified, pressure-driven, stopped-flow device. The major modifications include positioning a very short (0.6 mm) bed of the particles just upstream of the detector cell, eliminating the mixing chamber, and adding high-speed switching valves in order to allow sequential continuous flow of individual solutions. Instantaneous rate curves are measured for the desorption of 1,2-dimethyl-4-nitrobenzene (DMNB) from 12-microm-diameter porous particles of the bonded-phase packing Luna C-18 employing high linear velocities of the eluting solvent. The same experiment is performed for the nonsorbed compound phloroglucinol (PG) The PG rate curve is used in two ways (i.e., subtraction and deconvolution) in order to correct the observed rate curve of DMNB for experimental artifacts such as bed hold-up volume and instrument band broadening. The cumulative desorption rate curve of DMNB is obtained by integration. It is accurately described (R2 > 0.999) by a theoretical model that invokes both intraparticle diffusion (including both hindered pore diffusion and surface diffusion) and external film diffusion. The surface diffusion coefficient is (3.2 +/- 0.8) x 10(-6) cm(2)/s and the diffusion film thickness is 0.5 microm. The validity, of both the experimental technique and the theoretical model, is demonstrated by excellent agreement between a predicted and an observed chromatographic elution peak for DMNB on a 25-cm-long commercial column of Luna C-18.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".