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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 OpenAlexaff
Chenglin Yi, Hong Liu, Shaoyi Zhang, Yiqun Yang, Yan Zhang, Zhong‐Yuan Lu, Eugenia Kumacheva, Zhihong Nie

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.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.021
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

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

Citations217
Published2020
Admission routes1
Has abstractyes

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