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Record W3032032082 · doi:10.1002/advs.202000310

Solution–Liquid–Solid Growth and Catalytic Applications of Silica Nanorod Arrays

2020· article· en· W3032032082 on OpenAlex
Yaosi Fang, Kangxiao Lv, Zhao Li, Ning Kong, Shenghua Wang, Ao‐Bo Xu, Zhiyi Wu, Fengluan Jiang, Chaoran Li, Geoffrey A. Ozin, Le He

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Science · 2020
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsWestern UniversityUniversity of Toronto
FundersHigher Education Discipline Innovation ProjectPriority Academic Program Development of Jiangsu Higher Education InstitutionsNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsNanorodMaterials scienceNanostructureNanotechnologyWaferFabricationSubstrate (aquarium)Chemical engineering

Abstract

fetched live from OpenAlex

Abstract As an analogue to the vapor–liquid–solid process, the solution–liquid–solid (SLS) method offers a mild solution‐phase route to colloidal 1D nanostructures with controlled sizes, compositions, and properties. However, direct growth of 1D nanostructure arrays through SLS processes remains in its infancy. Herein, this study shows that SLS processes are also suitable for the growth of nanorod arrays on the substrate. As a proof of concept, seedless growth of silica nanorod arrays on a variety of hydrophilic substrates such as pristine and oxide‐modified glass, metal sheets, Si wafers, and biaxially oriented polypropylene film are demonstrated. Also, the silica nanorod arrays can be used as a new platform for the fabrication of catalysts for photothermal CO 2 hydrogenation and the reduction of 4‐nitrophenol reactions. This work offers some fundamental insight into the SLS growth process and opens a new avenue for the mild preparation of functional 1D nanostructure arrays for various applications.

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 score0.016
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.252
Teacher spread0.235 · 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