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Record W3038749753 · doi:10.3390/app10134626

Lignin to Materials: A Focused Review on Recent Novel Lignin Applications

2020· review· en· W3038749753 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Sciences · 2020
Typereview
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
FundersKorea Institute of Science and Technology
KeywordsLigninDepolymerizationMaterials sciencePolymerRaw materialNanotechnologyOrganic chemistryChemistryPolymer chemistryComposite material

Abstract

fetched live from OpenAlex

In recent decades, advancements in lignin application include the synthesis of polymers, dyes, adhesives and fertilizers. There has recently been a shift from perceiving lignin as a waste product to viewing lignin as a potential raw material for valuable products. More recently, considerable attention has been placed in sectors, like the medical, electrochemical, and polymer sectors, where lignin can be significantly valorized. Despite some technical challenges in lignin recovery and depolymerization, lignin is viewed as a promising material due to it being biocompatible, cheap, and abundant in nature. In the medical sector, lignins can be used as wound dressings, pharmaceuticals, and drug delivery materials. They can also be used for electrochemical energy materials and 3D printing lignin–plastic composite materials. This review covers the recent research progress in lignin valorization, specifically focusing on medical, electrochemical, and 3D printing applications. The technoeconomic assessment of lignin application is also discussed.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.821
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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.

Opus teacher head0.066
GPT teacher head0.314
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it