MétaCan
Menu
Back to cohort
Record W4378781988 · doi:10.1021/acs.langmuir.3c00640

Insights into Permanent Encodings of Macroscopic Spike Patterns by Magnetic-Field-Directed Evaporative Self-Assembly from Ferrofluids

2023· article· en· W4378781988 on OpenAlexafffund
T Zhong, Jialin Meng, Mark P. Andrews

Bibliographic record

VenueLangmuir · 2023
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCentre québécois sur les matériaux fonctionnels
KeywordsFerrofluidMagnetic fieldMagnetic nanoparticlesChemical physicsPattern formationField strengthNanoparticleWavelengthMaterials scienceMagnetizationCondensed matter physicsChemistryNanotechnologyPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

Field-directed assembly has the potential to make large hierarchically ordered structures from nanoscale objects. Shear forces and optical, electric, and magnetic fields have been used for this purpose. Ferrofluids consist of magnetic nanoparticles hosted in mobile liquids. Though they exhibit rich structures and lattice patterns in response to an applied magnetic field, the patterns collapse when the field is removed. Recently, we adapted evaporation-induced self-assembly to obtain permanent encodings of the complex field response of magnetite nanoparticles in alkane media. The encodings are characterized by order that culminates in macrostructures comprising kinetically trapped spike patterns. The present work examines a number of variables that control pattern formation associated with this encoding. Control variables include applied magnetic field strength, magnetic field gradient, nanoparticle concentration, solvent evaporation conditions, and alkane solvent chain length. The pattern formation process is captured in six stages of evolution until the solvent host has evaporated and the pattern is permanently fixed. The macropatterns consist of hexagonal arrays that coexist with different pentagonal and heptagonal defects. The Voronoi entropy is calculated for different patterns that arise due to changes in the control parameters. Insight into order in the lattice patterns is achieved by extracting measurables like peak-to-peak spike wavelength, spike population, spike height, and base diameter from the patterns. The pattern measurables depend nonlinearly on the magnetic field gradient, solvent evaporation rate, and solvent chain length. Nanoparticle concentration does not impact the measurables significantly. Nonetheless, the results agree qualitatively with a linear expression for the critical magnetization and wavelength that explicitly contains the field gradient and surface tension.

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 score0.000
Threshold uncertainty score0.002

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)0.0000.000

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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueLangmuirSame topicPickering emulsions and particle stabilizationFrench-language works237,207