Evidence map›Paper›PMID 39599265›Full record

ArticlePolymers2024

Laser-Induced Silver Nanowires/Polymer Composites for Flexible Electronics and Electromagnetic Compatibility Application.

Il'ya Bril', Anton Voronin, Yuri Fadeev, Alexander Pavlikov, Ilya Govorun, Ivan Podshivalov, Bogdan Parshin, Mstislav Makeev, Pavel Mikhalev, Kseniya Afanasova and 2 more

Abstract read
In one paragraph

Article in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. 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

12 authors.

Il'ya Bril'Federal Research Center, Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (FRC KSC SB RAS), 660036 Krasnoyarsk, Russia.ORCID 0000-0002-1752-093X
Anton VoroninFederal Research Center, Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (FRC KSC SB RAS), 660036 Krasnoyarsk, Russia.ORCID 0000-0001-6908-9945
Yuri FadeevFederal Research Center, Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (FRC KSC SB RAS), 660036 Krasnoyarsk, Russia.
Alexander PavlikovSiberian Federal University, 660041 Krasnoyarsk, Russia.ORCID 0000-0003-1522-1845
Ilya GovorunKirensky Institute of Physics, Federal Research Center KSC SB RAS, 660036 Krasnoyarsk, Russia.
Ivan PodshivalovKirensky Institute of Physics, Federal Research Center KSC SB RAS, 660036 Krasnoyarsk, Russia.
Bogdan ParshinDepartment of Radio-Electronic Systems and Devices, Bauman Moscow State Technical University, 105005 Moscow, Russia.
Mstislav MakeevDepartment of Radio-Electronic Systems and Devices, Bauman Moscow State Technical University, 105005 Moscow, Russia.ORCID 0000-0001-8945-3919
Pavel MikhalevDepartment of Radio-Electronic Systems and Devices, Bauman Moscow State Technical University, 105005 Moscow, Russia.ORCID 0000-0003-0672-4627
Kseniya AfanasovaFederal Research Center, Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (FRC KSC SB RAS), 660036 Krasnoyarsk, Russia.
Mikhail SimuninFederal Research Center, Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (FRC KSC SB RAS), 660036 Krasnoyarsk, Russia.ORCID 0000-0001-9317-1113
Stanislav KhartovFederal Research Center, Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (FRC KSC SB RAS), 660036 Krasnoyarsk, Russia.

Funding

Ministry of Science and Higher Education of the Russian Federation FSFN-2024-0016Ministry of Science and Higher Education of the Russian Federation FWES-2024-0026
6 · The paper itself

Abstract

Nowadays, the Internet of Things (IOT), electronics, and neural interfaces are becoming an integral part of our life. These technologies place unprecedentedly high demands on materials in terms of their mechanical and electrical properties. There are several strategies for forming conductive layers in such composites, e.g., volume blending to achieve a percolation threshold, inkjet printing, lithography, and laser processing. The latter is a low-cost, environmentally friendly, scalable way to produce composites. In our work, we synthesized AgNW and characterized them using Ultraviolet-visible spectroscopy (UV-vis), Transmission electron microscopy (TEM), and Selective area electron diffraction (SAED). We found that our AgNW absorbed in the UV-vis range of 345 to 410 nm. This is due to the plasmon resonance phenomenon of AgNW. Then, we applied the dispersion of AgNW on the surface of the polymer substrate, dried them and we got the films of AgNW.. We irradiated these films with a 432 nm laser. As a result of the treatment, we observed two processes. The first one was the sintering and partial melting of nanowires under the influence of laser radiation, as a consequence of which, the sheet resistance dropped more than twice. The second was the melting of the polymer at the interface and the subsequent integration of AgNW into the substrate. This allowed us to improve the adhesion from 0-1 B to 5 B, and to obtain a composite capable of bending, with radius of 0.5 mm. We also evaluated the shielding efficiency of the obtained composites. The shielding efficiency for 500-600 nm thick porous film samples were 40 dB, and for 3.1-4.1 µm porous films the shielding efficiency was about 85-90 dB in a frequency range of 0.01-40 GHz. The data obtained by us are the basis for producing flexible electronic components based on AgNW/PET composite for various applications using laser processing methods.

Indexed as

flexible electronicssheet resistanceshielding efficiencysilver nanowires

Identifiers

PMID39599265
PMCPMC11598760

What OpenQuestion holds

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Registered trials

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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.