Lignin valorization beyond energy use: has lignin's time finally come?
Bibliographic record
Abstract
Abstract According to an old proverb, ‘you can make anything out of lignin, except money’. The complexity of lignin's structure and many inferior characteristics of lignin, such as its insolubility in organic solvent and poor reactivity related to it large molecular weight, have posed significant challenges to lignin valorization. Driven mainly by the commercial availability of large amounts of kraft lignin and hydrolysis lignin in kraft pulp mills and cellulosic ethanol plants, there is a pressing need to valorize lignin for high‐value chemical and material products for better overall profitability for the plants, and for the emerging bioeconomy. To this end, we have developed, over 10 years and in several publications, an engineering approach to lignin valorization. This perspective paper provides an overview of this process and concretizes the research achieved in support of lignin valorization. In the method presented, lignin is first de‐polymerized into de‐polymerized lignin (DL) at a high yield and with a tunable Mw (weight average molecular weight). The DL is then utilized as a mixture (no separation needed) to substitute directly petroleum‐based phenol (up to 75% substitution), polyols (up to 50% substitution), and bis‐phenol A (100 substitution) in preparation of bio‐based phenolic resins, polyurethane foams, and epoxy resins. The DL products were also used to replace petroleum‐based antioxidants resulting in enhanced thermo‐oxidative and thermal stability of polyethylene in the synthesis of bio‐based resins / plastic composites. This approach has demonstrated both technical and economic feasibility, generating a payback period of approximately 3 years for a commercial capacity of 40 000 t/y. Thus, Lignin valorization beyond energy use can be profitable, and the old proverb may prove wrong. Lignin's time might have finally come! © 2020 Society of Industrial Chemistry and John Wiley & Sons Ltd
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".