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Record W4386092673 · doi:10.1186/s40643-023-00669-w

Super-strong and high-performance electrical film heater derived from silver nanowire/aligned bacterial cellulose film

2023· article· en· W4386092673 on OpenAlexafffund
Guichun Hu, Amir Varamesh, Na Zhong, Fangong Kong, Jinguang Hu

Bibliographic record

VenueBioresources and Bioprocessing · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Calgary
FundersCanada First Research Excellence FundUniversity of Calgary
KeywordsMaterials scienceJoule heatingHeating elementBacterial celluloseComposite materialFlexibility (engineering)NanotechnologyOptoelectronicsCelluloseChemical engineering

Abstract

fetched live from OpenAlex

Abstract High-performance electrical Joule heaters with high mechanical properties, low driving voltage, rapid response, and flexibility are highly desirable for portable thermal management. Herein, by using aligned bacterial cellulose (BC) and silver nanowire (AgNW), we fabricated a novel film heater based on Joule heating phenomena. The aligned BC film prepared by stretching BC hydrogel and hot-pressing drying technology showed outstanding mechanical properties and flexibility. The ultrahigh strength of up to 1018 MPa and the toughness of 20 MJ/m 3 were obtained for the aligned BC film with 40% wet-stretching (BC-40). In addition, the aligned BC film could be folded into desirable shapes. The AgNW was spray-coated on the surface of aligned BC-40 film and then covered with polydimethylsiloxane to form a P@AgNW@BC heater. P@AgNW@BC heater showed excellent conductivity, which endowed the film heater with an outstanding Joule heating performance. P@AgNW@BC heater could reach ~ 98 ℃ at a very low driving voltage of 4 V with a rapid heating response (13 s) and long-term temperature stability. The P@AgNW@BC heater with such an outstanding heating performance can be used as a flexible heating device for different applications in daily life like deicing/defogging device, wearable thermotherapy, etc.Affiliations: Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.yes, we confirmed the affiliations are correct. Article title: Kindly check and confirm the edit made in the article title.Thanks, the title is no problem. Graphical Abstract

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 score0.026
Threshold uncertainty score0.951

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 studies0.0010.000
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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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