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Record W4405190134 · doi:10.3390/polym16233438

Is Kraft Pulping the Future of Biorefineries? A Perspective on the Sustainability of Lignocellulosic Product Development

2024· article· en· W4405190134 on OpenAlexaff
Kalavathy Rajan, Paula Bertón, Robin D. Rogers, Julia L. Shamshina

Bibliographic record

VenuePolymers · 2024
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiorefiningBiorefineryLignocellulosic biomassBiomass (ecology)SustainabilityCellulosic ethanolPulp and paper industryBlack liquorKraft paperPulp (tooth)Waste managementEnvironmental scienceBusinessLigninBiofuelEngineeringChemistryCellulose

Abstract

fetched live from OpenAlex

By reflecting on the history and environmental impact of conventional biorefining, such as kraft pulping, we aim to explore important questions about how natural polymers can be more sustainably sourced to develop bio-products and reduce reliance on plastics. Since the Industrial Revolution, chemical pulping processes have enabled the mass production of cellulosic products from woody biomass. Kraft pulping, which dominates within modern pulp and paper mills, has significantly contributed to environmental pollution and carbon emissions due to sulfurous byproducts and its high water and energy consumption. While chemical pulping technologies have advanced over time, with improvements aimed at enhancing sustainability and economic feasibility, conventional biorefineries still face challenges related to biomass conversion efficiency and environmental impact. For example, efforts to fully utilize wood resources, such as isolating lignin from black liquor, have made limited progress. This perspective provides a thoughtful examination of the growth of chemical pulping, particularly the kraft process, in the production of consumer goods and its environmental consequences. It also presents key insights into the bottlenecks in developing truly sustainable biomass conversion technologies and explores potential alternatives to traditional chemical pulping.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.223
Teacher spread0.216 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2024
Admission routes1
Has abstractyes

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