Evidence map›Paper›PMID 42502190›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2026

Adaptive Metafilm With Scalable Phase-Tunable Emissivity for Energy-Efficient Thermal Management.

James Laurence Ruello, Sudip Kumar Pal, Xiaoqing Yu, Joonyoung Yoo, Sihyun Jang, Gayeong Kim, Gunwoo Kim

Abstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2026. 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

7 authors.

James Laurence RuelloDepartment of Organic Materials and Textile Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.ORCID https://orcid.org/0000-0002-5757-6989
Sudip Kumar PalDepartment of Organic Materials and Textile Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.ORCID https://orcid.org/0000-0003-4854-1650
Xiaoqing YuDepartment of Organic Materials and Textile Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.
Joonyoung YooDepartment of Organic Materials and Textile Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.
Sihyun JangDepartment of Organic Materials and Textile Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.
Gayeong KimDepartment of Carbon Materials and Fiber Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.
Gunwoo KimDepartment of Organic Materials and Textile Engineering, Jeonbuk National University, Jeonju-si, Jeonbuk, Republic of Korea.ORCID https://orcid.org/0009-0002-0063-7186

Funding

Ministry of Education and Jeonbuk State, South Korea 2025-RISE-13-JBUMinistry of Education and Jeonbuk State, South Korea RS-2023-00304743Ministry of Science and ICT (MSIT)Ministry of Science and ICT, South Korea RS-2024-00446841
6 · The paper itself

Abstract

Efficient thermal management of enclosed systems through controlled manipulation of radiative cooling power represents a key functionality of adaptive composite metamaterials. Such materials enable precise regulation of heat emission under varying environmental conditions while maintaining scalability and durability. Here, we present an adaptive metafilm (AMF) that autonomously tunes its infrared (IR) emissivity near ambient temperature. The AMF is fabricated by embedding tungsten-doped vanadium dioxide (W-VO

Indexed as

adaptive metafilm (AMF)aluminum sputteringmultiple scatteringnet‑zero thermal management

Identifiers

PMID42502190
PMCPMC13548933

What OpenQuestion holds

Textmetadata
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.