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Record W3129164616 · doi:10.26685/urncst.200

Cellulose in Nature - Versatile sources for Novel Applications: A Literature Review

2021· review· en· W3129164616 on OpenAlexaff
Dusan Pesic

Bibliographic record

VenueUndergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · 2021
Typereview
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsCelluloseBacterial celluloseMicrocrystalline celluloseExtraction (chemistry)BacteriaCrystallinityAlgaePulp and paper industryChemistryBiologyBotanyChromatographyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Introduction: Cellulose is the most abundant organic compound and the main component of the plant cell wall. However, it can be derived from other sources: tunicates, algae, and bacteria. Different sources of cellulose were shown to produce end-products of different mechanical properties and were considered for producing cellulose in non-industrial conditions. Methods: Procedures for the extraction of cellulose from different sources are described. They are similar for plants and algae, including bleaching and purification processes amongst others, while bacteria found in symbiotic cultures of bacteria and yeasts (SCOBYs) are capable of growing cellulose layers above their cultivation media. After extraction or bacterial cultivation, mechanical treatments are performed in order to modify new cellulose layers for specific applications. Results: Plant sources of cellulose are various and widely available, and often used for the industrial production of cellulose. Algae-derived microcrystalline cellulose (MCC) is similar to that from plant sources, but has higher crystallinity and, often, requires simpler extraction processes. Finally, cellulose grown by bacteria found in SCOBYs is the most optimal for non-industrial conditions, owing to the simplest cultivation and extraction procedures. Discussion: On a large scale, plant sources of cellulose are the optimal ones. The main downside of algal cellulose is that it is season-dependent, and more difficult to acquire than bacterial and plant sources. While having access to laboratory conditions for incubations and using a pure bacterial culture would be preferable, cultivation methods are simple enough to be adapted for home conditions. Also, conditions of incubation can be varied based upon the intended properties of the end-product: the efficiency of cellulose growth and its properties depend on the chosen carbon source. When bacteria produce a cellulose layer or it is extracted from another source, mechanical treatments for tuning porosity and other properties are applied. Conclusion: Sources of cellulose are numerous, and some are more suitable than others for non-industrial production, namely, using easily obtainable SCOBYs. This allows for a wide variety of applications: from artificial skin and face masks, to sustainable batteries and different food products.

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)0.016
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.008
Science and technology studies0.0010.005
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.009
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 head0.087
GPT teacher head0.480
Teacher spread0.392 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations3
Published2021
Admission routes1
Has abstractyes

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