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Record W3084646008 · doi:10.1126/science.aba8653

Self-limiting directional nanoparticle bonding governed by reaction stoichiometry

2020· article· en· W3084646008 on OpenAlex

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.

Bibliographic record

VenueScience · 2020
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsNanoparticleCovalent bondNanotechnologyMaterials scienceColloidStoichiometryYield (engineering)Chemical physicsNanomaterialsPolymerNanostructureMoleculeFabricationChemistryPhysical chemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Nanoparticle clusters with molecular-like configurations are an emerging class of colloidal materials. Particles decorated with attractive surface patches acting as analogs of functional groups are used to assemble colloidal molecules (CMs); however, high-yield generation of patchy nanoparticles remains a challenge. We show that for nanoparticles capped with complementary reactive polymers, a stoichiometric reaction leads to reorganization of the uniform ligand shell and self-limiting nanoparticle bonding, whereas electrostatic repulsion between colloidal bonds governs CM symmetry. This mechanism enables high-yield CM generation and their programmable organization in hierarchical nanostructures. Our work bridges the gap between covalent bonding taking place at an atomic level and colloidal bonding occurring at the length scale two orders of magnitude larger and broadens the methods for nanomaterial fabrication.

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)0.001
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 score0.026
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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