Production and separation of acetic acid from pyrolysis oil of lignocellulosic biomass: a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Bio‐oil from lignocellulosic biomass pyrolysis is a promising feedstock as a precursor for the production of transportation fuels and value‐added chemicals. The presence of significant concentrations of oxygen, water, and acids makes it difficult to use bio‐oil directly as a transportation fuel without costly upgrading. The acidity of pyrolysis liquids is mainly derived from volatile acids, such as acetic acid, causing chemical instability and corrosion. The extraction of acids from bio‐oil can therefore offer strategies for improved applications and economic value. Moreover, acetic acid is a valuable reagent and the building block for several commercially important chemicals. This review presents the results of important research related to the production of bio‐oil‐derived acetic acid. The discussion is intended to summarize the effect of biomass type and pretreatment method, pyrolysis processing conditions, and separation techniques on acetic acid production via pyrolysis. On this basis, acetic acid characterization techniques are also presented along with an overview of acetic acid applications and economic considerations. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it