Catalysis and Activation of Oxygen and Peroxide Delignification of Chemical Pulps: A Review
Bibliographic record
Abstract
Oxygen and hydrogen peroxide have always been technologically attractive oxidants to the pulp and paper industry. The fact that molecular oxygen has a triplet ground state whose direct interaction with singlet-state organic molecules is a spin-forbidden transition, limits its oxidative selectivity. Industrially, it would be extremely beneficial to fix molecular oxygen within organic or inorganic compounds capable of transferring it selectively to an organic substrate such as lignin. Since a variety of research endeavours have already been made to catalyse oxygen delignification and activate peroxide delignification of chemical pulps, this paper critically reviews them. In addition, this effort covers peracids, which can be considered as organic molecules containing active oxygen. Dioxiranes have also been shown to possess the ability to transfer a single activated oxygen atom onto aromatic and unsaturated substrates. As such, dimethyldioxirane is reviewed for its potential as a novel and selective bleaching agent for the production of fully-bleached totally chlorine-free (TCF) pulp. Finally, our critical review covers the recent scientific and patent literature which contains a number of examples where transition metals have been used as additives in peroxide and oxygen delignification.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".