Photocatalytic degradation of malic acid using a thin coated TiO<sub>2</sub>‐film: Insights on the mechanism of photocatalysis
Bibliographic record
Abstract
Decontamination of opaque fluids using photocatalysts and near Ultraviolet (UV) irradiation involves major technical challenges. This study considers a thin TiO 2 layer placed in a new Chemical Reactor Engineering Centre (CREC)‐photoreactor cell. This new photoreactor cell is used for the photocatalytic degradation of malic and malonic acids, typical apple juice components. Conversion of organic species can only proceed through the “dark side” of the TiO 2 layer, which is in direct contact with the fluid. Under the selected operating conditions both external mass‐transfer limitations and photolysis are found to be negligible. Macroscopic radiation balance shows that 92% of near UV radiation is absorbed by the ‘back side” of the TiO 2 ‐film. Photocatalytic degradation experiments with 10, 20, 30, and 40 ppm malic acid initial concentrations, show that malonic acid is a main intermediate. Complete malic acid conversion occurs after 5–8 h of irradiation. Kinetic modeling of malic and malonic acid photodegradation with kinetic parameter estimation is performed using both an “in series” and an “in series‐parallel” reaction networks. The “in series‐parallel” reaction network displays better ability for predicting CO 2 formation, showing maximum quantum yields of 14.2%. Given that in the CREC‐photoreactor cell with a thin TiO 2 ‐film, photocatalysis can only proceed via the transfer of mobile “h + ” sites from the irradiated side to the “dark side', this study demonstrates the significance of this step on the overall photocatalysis mechanism. © 2014 American Institute of Chemical Engineers AIChE J , 60: 3286–3299, 2014
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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".