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Record W3000749896 · doi:10.1016/j.jobab.2020.03.003

Utilization of discarded crop straw to produce cellulose nanofibrils and their assemblies

2020· article· en· W3000749896 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2020
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsnot available
FundersYouth Innovation Promotion Association of the Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsCelluloseStrawMaterials scienceChemical engineeringPulp and paper industryNanotechnologyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A tremendous amount of wheat straw (WS) has been generated by wheat crops every year, while only a small percentage is being used in applications, and most get burned on the field, causing a large amount of the exhaust gas that pollutes the environment. Herein, we report on the extraction of cellulose nanofibrils (CNF) from the alkali treated WS by a combination of 2,2,6,6-tetramethylpyperidine-1-oxyl (TEMPO)-oxidation and mechanical disintegration method. The crystalline structures, thermal properties, natural charge of the CNF were examined. The resultant nano-building blocks of the CNF was assembled into macroscopic cellulose materials, i.e., film, aerogel, and filament in this work. Furthermore, the morphologies and microstructues as well as other properties of these three kinds of the CNF assemblies were investigated. The obtained CNF and its assemblies showed a potential application in new materials areas. This work explored a new way to utilize the discarded WS instead of being burned.

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 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 score0.008
Threshold uncertainty score0.387

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 head0.045
GPT teacher head0.281
Teacher spread0.236 · 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