Terminology, Relative Photonic Efficiencies and Quantum Yields in Heterogeneous Photocatalysis. Part II: Experimental Determination of Quantum YieldsA draft version of this paper was published previously in part in [J. Photochem. Photobiol. A:Chem., J. Adv. Oxid. Technol.; IAPS Newsletter and EPA Newsletter] to solicit comments and critiques from the scientific and engineering community. Moreover, during the preparation the draft proposal was submitted to a number of distinguished photochemists and photocatalycists to get their views.
Bibliographic record
Abstract
In the preceding article [Pure Appl. Chem. 71, 303–320 (1999)] we examined two principal features of heterogeneous photocatalysis that demanded scrutiny: (i) description of photocatalysis and (ii) description of process efficiencies. For the latter we proposed a protocol relative photonic efficiency which could subsequently be converted to quantum yields. A difficulty in expressing a quantum yield in heterogeneous photochemistry is the very nature of the system, either solid/liquid or solid/gas, which places severe restrictions on measurement of the photon flow absorbed by the light harvesting component, herein the photocatalyst TiO2, owing to non-negligible scattering by the particulates. It was imperative therefore to examine the extent of this problem. Extinction and absorption spectra of TiO2 dispersions were determined at low titania loadings by normal absorption spectroscopy and by an integrated sphere method, respectively, to assess the extent of light scattering. The method is compared to the one reported by Grela et al. [J. Phys. Chem. 100, 16940 (1996)] who used a polynomial extrapolation of the light scattered in the visible region into the UV region where TiO2 absorbs significantly. This extrapolation underestimates the scattering component present in the extinction spectra, and will no doubt affect the accuracy of the quantum yield data. Further, we report additional details in assessing limiting photonic efficiencies and quantum yields in heterogeneous photocatalysis.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".