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Record W3160271364 · doi:10.1002/admi.202001181

Ultrathin‐Walled 3D Inorganic Nanostructured Networks Templated from Cross‐Linked Cellulose Nanocrystal Aerogels

2021· article· en· W3160271364 on OpenAlexafffund
Arto Hiltunen, Tyler Or, Kimmo Lahtonen, Harri Ali‐Löytty, Nikolai V. Tkachenko, Mika Valden, Essi Sarlin, Emily D. Cranston, Jose Moran‐Mirabal, Jaana Vapaavuori

Bibliographic record

VenueAdvanced Materials Interfaces · 2021
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British ColumbiaMcMaster University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaAcademy of FinlandUniversities Space Research AssociationMcMaster University
KeywordsMaterials scienceAerogelAtomic layer depositionFabricationNanocrystalNanotechnologyCalcinationNanoporousNanostructureCoatingSubstrate (aquarium)Layer (electronics)CatalysisChemical engineering

Abstract

fetched live from OpenAlex

Abstract A key challenge in the development of materials for applications in the fields of opto‐ and nanoelectronics, catalysis, separation, and energy conversion is the ability to fabricate 3D inorganic semiconductive nanostructures in a precisely‐controlled and cost‐effective manner. This work describes the fabrication of 3D nanostructured TiO2 monoliths by coating ultraporous cross‐linked cellulose nanocrystal (CNC) aerogel templates with TiO2 layers of controlled thickness via atomic layer deposition (ALD). Following calcination, the resulting hollow inorganic ultraporous 3D networks form the thinnest self‐supporting semiconductive structure (7 nm) fabricated directly on a conductive substrate. The CNC‐templated ALD–TiO2 electrodes are applied toward photoelectrochemical water splitting. The results show that a TiO2 coating as thin as 15 nm produces a maximum water splitting efficiency, resulting in materials savings and reduced fabrication time.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.279
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes2
Has abstractyes

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Same venueAdvanced Materials InterfacesSame topicAdvanced Cellulose Research StudiesFrench-language works237,207