Influence of thermochemical activation of wood on the physicochemical properties of lignin
Bibliographic record
Abstract
The wood matrix is a lignin–carbohydrate nanobiocomposite, thermodynamically quasi-equilibrium heterogeneous system of biopolymers. Changing its thermodynamic equilibrium due to directed chemical and (or) physical impacts opens up new approaches to the study of plant objects. Thermochemical activation, including treatments in sub- (steam explosion) and supercritical conditions (supercritical fluid extraction) having similar mechanisms of action, is one such method. The effect of steam explosion is determined by two components — chemical (the catalytic effect of formed acetic and formic acid) and physical (a sharp adiabatic expansion). The main components of supercritical treatment are increased temperature and pressure in the CO2 medium with cosolvents. The chemical component of this treatment is due to the addition of chemical reagents. Such treatments lead to a change in the thermodynamic state and capillary-porous structure of the lignin–carbohydrate matrix, an increase in its heterogeneity, and the yield of extracted lignin preparations. Lignin is the most reactive component of the wood matrix, and these processes result in changes in its functional nature and reaction properties. Thus, the lignin sample extracted after steam explosion had the greatest increase in the content of phenolic hydroxyl (by 39 rel.%) and carboxyl (by 57 rel.%) groups. Change in the functional composition of lignin leads to a change in its redox state, characterized by the oxidative potential and free energy of oxidation. It was shown that lignin after steam explosion had the highest oxidative potential and the lowest value of the oxidation energy, which indicated the greatest change in its reactivity in redox interactions.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".