Evaluation of ultrafiltration, precipitation and adsorption processes for the purification of galactoglucomannan from steam pretreated softwood
Bibliographic record
Abstract
Galactoglucomannan (GGM) has been identified as a valuable resource and can be used in fields such as oxygen barrier films, food coatings or hydrogels. This hemicellulose can be extracted from softwood using steam explosion (STEX) under mild conditions. However, the GGM-solution also contains impurities such as lignin, lignin-carbohydrate complexes, organic acids, and salts, which require further purification before use.In this study, two different STEX-conditions were evaluated: (1) STEX pre-treatment at 190˚C for 5 minutes and (2) 200˚C for 2 minutes. The results showed only minor differences between the two conditions. However, the option using 200˚C for 2 minutes was slightly better with a mannan yield of 17.6% and a purity of 27.1%. For the purification, four different ultrafiltration polymericflat-sheet membranes were investigated in a recirculating batch setup. The best membrane was the GR90PP (Alfa Laval, 5kDa MWCO) which gave a flux of 11 L/m2h at a transmembrane pressure of 3 bar and a GGM retention of 96%. This membrane was used to concentrate the GGM solution to a volume concentration factor of 2. After this, three different purification processes for the ultrafiltration retentate were evaluated: (1) diafiltration with 4 feed volumes of water using the GR90PP membrane, (2) precipitation of hemicellulose with anti-solvents and (3) adsorption of lignin. Diafiltration showed promising ability to remove low-molecular-weight impurities and thereby increasing the mannan purity to 38% (corresponding to a GGM purity of 71%). The precipitation process step was not able to separate lignin compounds from the GGM in an efficient way independent from type and concentration of solvent. The adsorption process using granulated activated carbon demonstrated somewhat promising results regarding the separation of GGM and lignin, but require further investigation.The purified GGM could be cast into films and demonstrated good oxygen transfer rates (0.4-4.9 ml/m2/24h) at 50% relative humidity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".