FIGURES-OF-MERIT FOR THE TECHNICAL DEVELOPMENT AND APPLICATION OF ADVANCED OXIDATION TECHNOLOGIES FOR BOTH ELECTRIC- AND SOLAR-DRIVEN SYSTEMS A draft of this paper (without the solar section) was published previously [Journal of Advanced Oxidation Technologies, 1, 13–17 (1996)] for general comments from the scientific and engineering community. Opinions, conclusions, and recommendations expressed are those of the authors and do not necessarily reflect the views of the National Science Foundation. (IUPAC Technical Report)
Bibliographic record
Abstract
Advanced oxidation technologies (AOTs), which involve the in situ generation of highly potent chemical oxidants, such as the hydroxyl radical (áOH), have emerged as an important class of technologies for accelerating the oxidation (and hence removal) of a wide range of organic contaminants in polluted water and air. In this report, standard figures-of-merit are proposed for the comparison and evaluation of these waste treatment technologies. These figures-of-merit are based on electric-energy consumption (for electric-energy-driven systems) or collector area (for solar-energy-driven systems). They fit within two phenomenological kinetic order regimes: 1) for high contaminant concentrations (electric energy per mass, E EM , or collector area per mass, A CM ) and 2) for low concentrations (electric energy per order of magnitude, E EO , or collector area per order of magnitude, A CO ). Furthermore, a simple understanding of the overall kinetic behavior of organic contaminant removal in a waste stream (i.e., whether zero- or first-order) is shown to be necessary for the description of meaningful electric- or solar-energy efficiencies. These standard figures-of-merit provide a direct link to the electric- or solar-energy efficiency (lower values mean higher efficiency) of an advanced oxidation technology, independent of the nature of the system, and therefore allow for direct comparison of widely disparate AOTs. These figures-of-merit are also shown to be inversely proportional to fundamental efficiency factors, such as the lamp efficiency (for electrical systems), the fraction of the emitted light that is absorbed in the aqueous solution, and the quantum yield of generation of active radicals.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.010 |
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".