Evidence map›Paper›PMID 42310373›Full record

ArticleScientific reports2026

High power density in a fully printed origami-inspired rolled thermoelectric generator enabled by paper self-folding.

Hayato Yokoyama, Motoki Maeda, Giovanna Latronico, Paolo Mele, Hiroki Shigemune

Abstract read
In one paragraph

Article in Scientific reports, 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

5 authors.

Hayato YokoyamaGraduate School of Engineering Science, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-Ku, Tokyo, 135-8548, Japan.
Motoki MaedaGraduate School of Engineering Science, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-Ku, Tokyo, 135-8548, Japan.
Giovanna LatronicoCNR-ICMATE, Institute of Condensed Matter Chemistry and Technologies for Energy, National Research Council, Via Previati 1/E, 23900, Lecco, Italy.
Paolo MeleCollege of Engineering, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-Ku, Tokyo, 134-8548, Japan.
Hiroki ShigemuneCollege of Engineering, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-Ku, Tokyo, 134-8548, Japan. hshige@shibaura-it.ac.jp.

Funding

Japan Society for the Promotion of Science JP24H00728
6 · The paper itself

Abstract

Thermoelectric generators (TEGs) can harvest waste heat for small electronics. However, printed planar TEGs are often limited by low thermocouple density within a given footprint. Here, we present a paper-based rolled thermoelectric generator (Rolled TEG) that autonomously transforms from a planar sheet into a cylindrical geometry via paper self-folding using a fully printed fabrication process. Silver nanoparticle ink is inkjet printed to form electrodes and interconnects, while PEDOT:PSS is screen printed to form p-type thermoelectric legs, enabling series-connected architectures on paper substrates. The self-folding transformation rearranges thermocouples onto the inner cylindrical surface, increasing thermocouple density per projected installation area while preserving leg length and electrical connectivity. By systematically examining printing conditions and electrode pattern design, we clarify how internal resistance and output characteristics are governed and demonstrate that the rolled geometry enhances footprint-normalized power generation by achieving a footprint-normalized power density of 18.9 nW cm

Indexed as

Origami devicePaper-based devicePrinted electronicsSelf-foldingThermoelectric generator

Identifiers

PMID42310373
PMCPMC13542274

What OpenQuestion holds

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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.