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Record W3173937453 · doi:10.1002/bbb.2261

Isolation of lignin‐containing cellulose nanocrystals: life‐cycle environmental impacts and opportunities for improvement

2021· article· en· W3173937453 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

VenueBiofuels Bioproducts and Biorefining · 2021
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLife-cycle assessmentPulp and paper industryCelluloseNanocelluloseLigninEnvironmental scienceGlobal-warming potentialOxalic acidEnvironmental pollutionNanomaterialsChemistryMaterials scienceWaste managementNanotechnologyOrganic chemistryEnvironmental protectionProduction (economics)Greenhouse gasEngineering

Abstract

fetched live from OpenAlex

Abstract Deep eutectic solvent (DES) has recently been attracting great interest for its role in isolating nanocellulose owing to its distinct advantages of biodegradability, low toxicity, and recyclability. Lignin‐containing cellulose nanocrystals (LCNCs) obtained using DES pretreatment has led to an improvement in the production of nanomaterials. Understanding the potential environmental impacts of this novel technology at the laboratory scale provides important insights to improve its sustainability at full scale in the future. This study evaluates the environmental impacts of the production of LCNCs from thermomechanical pulp (TMP) following acidic DES pretreatment (using a binary system of ‘choline chloride – oxalic acid dihydrate’ or a ternary system of ‘choline chloride – oxalic acid dihydrate – p ‐toluenesulfonic acid’) based on various laboratory trials. The evaluation was conducted through a cradle‐to‐gate life‐cycle assessment for global warming potential (GWP), acidification potential (AP) and the cumulative energy demand (MJ). The average GWP, AP, and energy use were 39 kg CO 2 ‐eq, 0.17 kg SO 2 ‐eq, and 995 MJ per kg LCNCs, respectively. The sensitivity analysis showed that different degrees of reduction in environmental impact could be achieved by varying the input volume and/or reuse frequency of DES solutions. The largest reductions in GWP, AP, and energy use were achieved by reducing the input volume of DES solutions to 20% of its default value. The results of this LCA study illustrate the direction for future research and development (R&D) to further improve the sustainability of this DES‐mediated LCNC production technology. Through comparisons with the existing literature, this study also confirms the predominant contribution of chemical manufacturing to the overall environmental impacts of nanocellulose isolation technologies in general. © 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 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)0.001
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 score0.022
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.044
GPT teacher head0.269
Teacher spread0.226 · 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