Применение циклической вольтамперометрии при моделировании долговременной эксплуатации системы «Металл полимерное покрытие»
Bibliographic record
Abstract
Despite being an old process from the end of the 19<sup>th</sup> century, electrosorption has attracted renewed attention in recent years because of its unique properties and advantages compared to other separation technologies and due to the concomitant development of new porous electrode materials. Electrosorption offer the advantage to separate the pollutants from wastewater with the possibility of selectively adsorbing and desorbing the targeted compounds. A comprehensive review of electrosorption is provided with particular attention given to the electrosorption of organic compounds, unlike existing capacitive deionization review papers that only focus on inorganic salts. The background and principle of electrosorption are first presented, while the influence of the main parameters (e.g., electrode materials, electrode potential, physico-chemistry of the electrolyte solutions, type of compounds, co-sorption effect, reactor design, etc.) is then detailed and the modeling and engineering aspects are discussed. Finally, the main output and future prospects about recovery studies and combination between electro-sorption/desorption and degradation processes are given. This review particularly highlights that carbon-based materials have been mostly employed (85% of studies) as porous electrode in organics electrosorption, while existing studies lack of electrode stability and durability tests in real conditions. These electrodes have been implemented in a fixed-bed reactor design most of the time (43% of studies) due to enhanced mass transport. Moreover, the electrode potential is a major criterion: it should be applied in the non-faradaic domain otherwise unwanted reactions can easily occur, especially the corrosion of carbon from 0.21 V/standard hydrogen electrode or the water oxidation/reduction. Furthermore, there is lack of studies performed with actual effluents and without addition of supporting electrolyte, which is crucial for testing the real efficiency of the process. The associated predictive model will be required by considering the matrix effect along with transport phenomena and physico-chemical characteristics of targeted organic compounds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".