Evidence map›Paper›PMID 38250408›Full record

ArticleACS omega2024

Near-Infrared Triggered Degradation for Transient Electronics.

Emin Istif, Mohsin Ali, Elif Yaren Ozuaciksoz, Yagız Morova, Levent Beker

Abstract read
In one paragraph

Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Bioresorbable electrodes in implantable electronic healthcare devices.Frontiers in bioengineering and biotechnology · 2025
    Review
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

5 authors.

Emin IstifDepartment of Molecular Biology and Genetics, Faculty of Engineering and Natural Science, Kadir Has University, Istanbul 34083, Turkey.ORCID https://orcid.org/0000-0003-4700-7050
Mohsin AliDepartment of Biomedical Sciences and Engineering, Koç University, Rumelifeneri Yolu, Sarıyer, Istanbul 34450, Turkey.
Elif Yaren OzuaciksozDepartment of Biomedical Sciences and Engineering, Koç University, Rumelifeneri Yolu, Sarıyer, Istanbul 34450, Turkey.
Yagız MorovaKoç University Surface Science and Technology Center (KUYTAM), Rumelifeneri, Istanbul 34450, Turkey.
Levent BekerDepartment of Mechanical Engineering, Koç University, Rumelifeneri Yolu, Sarıyer, Istanbul 34450, Turkey.ORCID https://orcid.org/0000-0002-9777-6619

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronics that disintegrate after stable operation present exciting opportunities for niche medical implant and consumer electronics applications. The disintegration of these devices can be initiated due to their medium conditions or triggered by external stimuli, which enables on-demand transition. An external stimulation method that can penetrate deep inside the body could revolutionize the use of transient electronics as implantable medical devices (IMDs), eliminating the need for secondary surgery to remove the IMDs. We report near-infrared (NIR) light-triggered transition of metastable cyclic poly(phthalaldehyde) (cPPA) polymers. The transition of the encapsulation layer is achieved through the conversion of NIR light to heat, facilitated by bioresorbable metals, such as molybdenum (Mo). We reported a rapid degradation of cPPA encapsulation layer about 1 min, and the rate of degradation can be controlled by laser power and exposure time. This study offers a new approach for light triggerable transient electronics for IMDs due to the deep penetration depth of NIR light through to organs and tissues.

Identifiers

PMID38250408
PMCPMC10795112

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.