Evidence map›Paper›PMID 34207009›Full record

ArticlePolymers2021

Amphiphilic Polymer Nanoreactors for Multiple Step, One-Pot Reactions and Spontaneous Product Separation.

Andrew Harrison, Christina Tang

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 33% of its field
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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. 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

2 authors at 1 institution in 1 country.

Andrew HarrisonDepartment of Chemical and Life Sciences Engineering, Virginia Commonwealth University, Richmond, VA 23284-3028, USA.
Christina TangDepartment of Chemical and Life Sciences Engineering, Virginia Commonwealth University, Richmond, VA 23284-3028, USA.ORCID 0000-0001-6204-0129
Virginia Commonwealth University · US

Funding

National Science Foundation 1651957
6 · The paper itself

Abstract

Performing multiple reaction steps in "one pot" to avoid the need to isolate intermediates is a promising approach for reducing solvent waste associated with liquid phase chemical processing. In this work, we incorporated gold nanoparticle catalysts into polymer nanoreactors via amphiphilic block copolymer directed self-assembly. With the polymer nanoreactors dispersed in water as the bulk solvent, we demonstrated the ability to facilitate two reaction steps in one pot with spontaneous precipitation of the product from the reaction mixture. Specifically, we achieved imide synthesis from 4-nitrophenol and benzaldehyde as a model reaction. The reaction occured in water at ambient conditions; the desired 4-benzylideneaminophenol product spontaneously precipitated from the reaction mixture while the nanoreactors remained stable in dispersion. A 65% isolated yield was achieved. In contrast, PEGylated gold nanoparticles and citrate stabilized gold nanoparticles precipitated with the reaction product, which would complicate both the isolation of the product as well as reuse of the catalyst. Thus, amphiphilic nanoreactors dispersed in water are a promising approach for reducing solvent waste associated with liquid phase chemical processing by using water as the bulk solvent, eliminating the need to isolate intermediates, achieving spontaneous product separation to facilitate the recycling of the reaction mixture, and simplifying the isolation of the desired product.

Indexed as

micellemulticomponent reactionnanoprecipitationnanoreactorself-assembly

Identifiers

PMID34207009
PMCPMC8234837
OpenAlexW3176540141

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.