Evidence map›Paper›PMID 34215575›Full record

ArticleScience advances2021

On-chip transporting arresting and characterizing individual nano-objects in biological ionic liquids.

Christian Höller, Gabriel Schnoering, Hadi Eghlidi, Maarit Suomalainen, Urs F Greber, Dimos Poulikakos

Abstract read
In one paragraph

Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Christian HöllerLaboratory of Thermodynamics in Emerging Technologies, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-5972-9950
Gabriel SchnoeringLaboratory of Thermodynamics in Emerging Technologies, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-9231-9021
Hadi EghlidiLaboratory of Thermodynamics in Emerging Technologies, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland.
Maarit SuomalainenInstitute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-3276-3008
Urs F GreberInstitute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-2278-120X
Dimos PoulikakosLaboratory of Thermodynamics in Emerging Technologies, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland. dpoulikakos@ethz.ch.ORCID http://orcid.org/0000-0001-5733-6478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding and controlling the individual behavior of nanoscopic matter in liquids, the environment in which many such entities are functioning, is both inherently challenging and important to many natural and man-made applications. Here, we transport individual nano-objects, from an assembly in a biological ionic solution, through a nanochannel network and confine them in electrokinetic nanovalves, created by the collaborative effect of an applied ac electric field and a rationally engineered nanotopography, locally amplifying this field. The motion of so-confined fluorescent nano-objects is tracked, and its kinetics provides important information, enabling the determination of their particle diffusion coefficient, hydrodynamic radius, and electrical conductivity, which are elucidated for artificial polystyrene nanospheres and subsequently for sub-100-nm conjugated polymer nanoparticles and adenoviruses. The on-chip, individual nano-object resolution method presented here is a powerful approach to aid research and development in broad application areas such as medicine, chemistry, and biology.

Identifiers

PMID34215575
PMCPMC11057703

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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.