Simulation-based design of a bipolar membranes electrodialysis unit for chemicals productionfrom brines
Bibliographic record
Abstract
Nowadays environmental concerns are modifying the production and consumption patterns used so far. An important objective to improve our society is the use of sustainable processes that can reduce industrial waste streams. Bipolar membranes electrodialysis (EDBM) is an emerging environmentally friendly process that could be easily integrated into a circular economy approach to valorize waste brines. It is an electro-membrane process that allows the production of chemicals using only water, electrical energy and a salty solution. When electric current is applied to the electrodes of the EDBM stack, water dissociation takes place in the bipolar membranes. Therefore, the ions from water are combined with those coming from the salt generating acid and base. The increasing interest in the EDBM process requires appropriate design procedures. This study proposed a simulation-based design of a EDBM unit for the production of hydrochloric acid and sodium hydroxide from sodium chloride solution. The design was performed in terms of configuration and operational conditions. A model, realized by Culcasi et al. [1], was used to describe the EDBM process’s behaviour. This model was validated with experimental data so that a high quality design could be achieved. This procedure was used to design a EDBM unit that will be part of the demo-plant of the Horizon 2020 Water-Mining project.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".