Electrochemical Acidification of Kraft Black Liquor: Effect of Fouling and Chemical Cleaning on Ion Exchange Membrane Integrity
Bibliographic record
Abstract
In the essence of the green biorefinery concept an interest in further implementations of wood compounds has gained a lot of attention. Therefore, it is crucial to identify and develop efficient and eco-friendly extraction processes. In particular in a lignin biorefinery plant, electrochemical acidification of Kraft black liquor via electrodialysis with bipolar membrane is considered as a sustainable avenue to acidify the Kraft black liquor and subsequently extract lignin. Even though the application of this acidification technique results in less chemical consumption than the acid precipitation method, the colloidal fouling of the ion exchange (bipolar and cation exchange) membranes, adversely affects its performance. This study was performed to determine the influence of the colloidal fouling and chemical cleaning process on the integrity of the membranes. Four commercially available cation exchange membranes and one bipolar membrane were examined. Membrane analyses, such as thickness, contact angle, ion exchange capacity and electrical resistance measurements, as well as scanning electron microscopy with energy dispersive X-ray analysis, were carried out. It was found that changing the type of the cation-exchange membrane cannot eliminate the fouling phenomenon and a chemical cleaning cycle is required. Caustic soda and fresh diluted black liquor were tested as the cleaning solutions. The initial properties of the bipolar membrane and two cation-exchange membranes (CMB and Nafion 324) were reestablished after the chemical cleaning step. Furthermore, in terms of sustainability concept, the utilization of in situ and free of charge fresh diluted black liquor, as the cleaning agent, can be an interesting eco-efficient approach.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".