Influence of carbonisation on selected engineering properties of carbon resin electrodes for electrochemical treatment of wastewater
Bibliographic record
Abstract
Abstract In this study, effects of selected factors on selected properties of carbon resin electrodes (CRE) have been investigated. CRE were developed from used dry cells and resin using non‐heat‐treatment process. Selected properties (density, electrical resistance, microstructure, hygroscopy, stability moisture content, compressive and flexural strength) of the electrodes were monitored and effects of carbonisation temperature, carbon particle size, and compaction pressure on these properties were studied. The study revealed that the density of CRE was in the range of 1.33 to 1.59 g/cm3, compressive strength ranged from 36.56 to 43.81 MN/m2, flexural strength, moisture content, and swelling were in the range of 6.76 to 8.10 MN/m2, 0.84–0.93%, and 6.04–9.30%, respectively. In all cases electrical resistance and density of CRE decreased with increasing carbonisation temperature at various operational factors (particle size, compacting pressure, and percentage of the resin used). Also, it was revealed that carbonisation of CRE from 30 to 220°C reduced specific electrical resistance and density from 1.85 to 1.29 × 10−1 Ω/cm and from 1.35 to 1.24 g/cm3, respectively, but carbonisation temperature had no significant effect on wetness, compressive and flexural strength, stability, and moisture content of the electrodes. Estimated costs revealed that cost of producing CRE was cheaper ($13.25/m) than that of heat‐treated electrodes ($33.33/m). It was concluded that carbonisation temperature, particle size, compacting pressure, and percentage of the resin used are important factors in the development of CRE with lower specific electrical resistance.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".