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Record W4220895999 · doi:10.1002/smll.202200220

Structured Ultra‐Flyweight Aerogels by Interfacial Complexation: Self‐Assembly Enabling Multiscale Designs

2022· article· en· W4220895999 on OpenAlex
Milad Kamkar, Ahmadreza Ghaffarkhah, Rubina Ajdary, Yi Lu, Farhad Ahmadijokani, Sameer Mhatre, Elnaz Erfanian, Uttandaraman Sundararaj, Mohammad Arjmand, Orlando J. Rojas

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

VenueSmall · 2022
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of CalgaryUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaAalto-YliopistoCanada Excellence Research Chairs, Government of CanadaCanada Foundation for Innovation
KeywordsMaterials scienceNanotechnologyMicrofluidicsSoft materialsSmart materialPhase (matter)

Abstract

fetched live from OpenAlex

The rapid co-assembly of graphene oxide (GO) nanosheets and a surfactant at the oil/water (O/W) interface is harnessed to develop a new class of soft materials comprising continuous, multilayer, interpenetrated, and tubular structures. The process uses a microfluidic approach that enables interfacial complexation of two-phase systems, herein, termed as "liquid streaming" (LS). LS is demonstrated as a general method to design multifunctional soft materials of specific hierarchical order and morphology, conveniently controlled by the nature of the oil phase and extrusion's injection pressure, print-head speed, and nozzle diameter. The as-obtained LS systems can be readily converted into ultra-flyweight aerogels displaying worm-like morphologies with multiscale porosities (micro- and macro-scaled). The presence of reduced GO nanosheets in such large surface area systems renders materials with outstanding mechanical compressibility and tailorable electrical activity. This platform for engineering soft materials and solid constructs opens up new horizons toward advanced functionality and tunability, as demonstrated here for ultralight printed conductive circuits and electromagnetic interference shields.

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 categoriesInsufficient payload (model declined to judge)
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 score0.023
Threshold uncertainty score0.997

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)0.0040.000

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 head0.041
GPT teacher head0.247
Teacher spread0.206 · 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