A Review of Membrane Technology for Integrated Forest Biorefinery
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
More recently, the concept of integrated forest biorefinery (IFBR) has received much attention as a promising solution for the struggling forest industry in North America and Europe to overcome its difficult financial period and competes globally. This new business paradigm offers a broad range of potentially attractive products, from bioenergy to value-added green organic chemicals in addition to traditional pulp and paper products. However, it also implies adoption of different types of appropriate separation technologies. Recent advancements in membrane technologies and their valuable applications have resulted in numerous breakthroughs in IFBR. The review of the implementation of membrane technologies for the separation of the value-added chemicals in the integrated forest biorefinery could contribute to the knowledge required for the large-scale adoption of membrane technologies in the forest industry. This paper aims to present a state-of-the-art review on the applications and the recent advancements of membrane technologies in IFBR, and their capacities to produce value-added chemicals and bioenergy. The emphasis is given to the focus areas of IFBR, particularly: the recovery of value-added chemicals, black liquor concentration, product recovery from Kraft evaporator condensates, tall oil recovery, inorganic and inorganic compounds recovery, fermentation inhibitors removal, enzyme recovery, biobutanol and bioethanol production and recovery. The paper also discusses the challenges and opportunities of this new business paradigm of forest industries.
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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it