Evidence map›Paper›PMID 39713727›Full record

ArticleACS nanoscience Au2024

Molecular Additives as Competitive Binding Agents to Control Supramolecular-Driven Nanoparticle Assembly.

Rebecca L Li, Nicholas Sbalbi, Matthew Ye, Robert J Macfarlane

Abstract read
In one paragraph

Article in ACS nanoscience Au, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rebecca L LiDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.ORCID https://orcid.org/0000-0001-7208-3413
Nicholas SbalbiDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.ORCID https://orcid.org/0000-0001-9945-3955
Matthew YeDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Robert J MacfarlaneDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.ORCID https://orcid.org/0000-0001-9449-2680

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colloidal nanoparticle assembly methods can produce intricate superlattice structures and often use knowledge of atomic crystallization behaviors to guide their design. While this analogy has enabled multiple routes to programming colloidal crystallization thermodynamics, fewer tools or strategies exist to manipulate nanoparticle superlattice growth kinetics in a controlled manner. Here we investigate how small-molecule additives can be used to modulate the thermodynamics and kinetics of supramolecular-chemistry-driven nanoparticle assembly. Specifically, we introduce monovalent binding agents into the superlattice growth solution that compete with the multivalent interparticle bonding interactions driving particle assembly, thereby altering interparticle bond strength by reducing the number of bridging complexes formed between particles. In this manner, the assemblies can be steered to avoid kinetic traps and crystallize into faceted single crystals under isothermal conditions, alleviating the need for precise thermal control that has conventionally been required to produce large, faceted crystals in prior assembly methods.

Identifiers

PMID39713727
PMCPMC11659897

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.