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Record W3198480345 · doi:10.1039/d1nr04697g

Tailoring the mechanoresponsive release from silica nanocapsules

2021· article· en· W3198480345 on OpenAlexaff
Fabian Uebel, Héloïse Thérien‐Aubin, Katharina Landfester

Bibliographic record

VenueNanoscale · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMemorial University of Newfoundland
FundersMax-Planck-Gesellschaft
KeywordsNanocapsulesMaterials scienceNanotechnologyNanoparticle

Abstract

fetched live from OpenAlex

Triggering the release of encapsulated cargos using mechanical stress acting on a nanocarrier is a strategy with potential applications from drug delivery to self-healing coatings. The mechanically triggered release of encapsulated molecules can be controlled by tuning the mechanical properties of the nanocapsules, which are strongly linked to the nanocapsule architecture. Here, silica nanocarriers were designed to tune precisely the release initiated by mechanical stress. We synthesized silica nanocapsules (SiNCs) with a finely tunable diameter and shell thickness and performed AFM nanoindentation experiments to determine the breaking force of single SiNCs. We demonstrated that it is possible to trigger the release of encapsulated payload by the application of an external mechanical force on the SiNCs. Furthermore, we successfully controlled the breaking force and the amount of released payload by tailoring the architecture of the nanocarriers, illustrating how such mechanoresponsive SiNCs could be used as responsive nanocarriers for the delivery of molecular cargos.

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 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 score0.133
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.009
GPT teacher head0.250
Teacher spread0.242 · 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.

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

Citations7
Published2021
Admission routes1
Has abstractyes

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