Evidence map›Paper›PMID 39104559›Full record

ReviewRSC advances2024

NIR-induced photothermal-responsive shape memory polyurethane for versatile smart material applications.

Ki Yan Lam, Choy Sin Lee, Rachel Yie Hang Tan

Abstract readReview
In one paragraph

Review in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

3 authors.

Ki Yan LamDepartment of Pharmaceutical Chemistry, School of Pharmacy, IMU University No. 126, Jalan Jalil Perkasa 19, Bukit Jalil 57000 Kuala Lumpur Malaysia choysin_lee@imu.edu.my.ORCID https://orcid.org/0000-0002-2258-097X
Choy Sin LeeDepartment of Pharmaceutical Chemistry, School of Pharmacy, IMU University No. 126, Jalan Jalil Perkasa 19, Bukit Jalil 57000 Kuala Lumpur Malaysia choysin_lee@imu.edu.my.ORCID https://orcid.org/0000-0002-9275-8067
Rachel Yie Hang TanSchool of Postgraduate Studies, IMU University No. 126, Jalan Jalil Perkasa 19, Bukit Jalil 57000 Kuala Lumpur Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stimuli responsiveness has been an attractive feature of smart material design, allowing the chemical and physical properties of the materials to change in response to small environmental variations. The versatile shape memory polyurethane (SMPU) has been advanced into thermally-responsive SMPU, enabling its use in neurovascular stents, smart fibers for compression garments, and thermal-responsive components for aircraft and aerospace structures. While thermally-induced SMPU materials exhibit excellent shape recovery and fixity, they encounter limitations such as long response times, energy-intensive heating processes, and potential damage to heat-sensitive components, hindering their wide application. Thus, SMPU has further advanced into a photothermal-responsive material by incorporating photothermal agents into the polymer matrix, offering faster response times, compatibility with heat-sensitive materials, and enhanced mechanical properties, expanding the versatility and applicability of shape memory technology. This review focuses on the classes of NIR-induced photothermal agent used in SMPU systems, their synthesis methods, and photothermal-responsive mechanism under NIR-light, which offers a dual responsiveness to the host SMPU. The advantages and limitations of NIR-induced photothermal SMPU are reviewed, and challenges in their development are discussed.

Identifiers

PMID39104559
PMCPMC11299057

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.