Evidence map›Paper›PMID 41299070›Full record

ArticleNature materials2026

Enabling efficient electron injection in stretchable OLED.

Wei Liu, Cheng Zhang, Zhiming Zhang, Yang Li, Shinya Wai, Aikaterini Vriza, Yahao Dai, Glingna Wang, Yunfei Wang, Benjamin T Diroll and 8 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

18 authors.

Wei Liu *Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0002-1207-204X
Cheng Zhang *Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0003-3026-1159
Zhiming Zhang *Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0001-5746-9203
Yang LiPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0003-1912-1438
Shinya WaiPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.
Aikaterini VrizaNanoscience and Technology Division, Argonne National Laboratory, Lemont, IL, USA.ORCID http://orcid.org/0000-0002-5663-8703
Yahao DaiPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.
Glingna WangPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0002-4621-5838
Yunfei WangAdvanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0001-7555-5308
Benjamin T DirollNanoscience and Technology Division, Argonne National Laboratory, Lemont, IL, USA.ORCID http://orcid.org/0000-0003-3488-0213
Naisong ShanPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0002-1476-6539
Songsong LiPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0001-9784-2877
Du ChenDepartment of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-7604-8786
Peijun GuoDepartment of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA.ORCID http://orcid.org/0000-0001-5732-7061
Chenhui ZhuAdvanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Jie XuPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0001-7842-5496
Juan J de PabloPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA. depablo@uchicago.edu.ORCID http://orcid.org/0000-0002-3526-516X
Sihong WangPritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA. sihongwang@uchicago.edu.ORCID http://orcid.org/0000-0002-3611-0004

Funding

National Science Foundation (NSF) 2239618United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research) Grant No. FA9550-22-1-0209U.S. Department of Energy (DOE) DE-AC02-06CH11357U.S. Department of Energy (DOE) DOE/BES 5J-30161-0010AU.S. Department of Health & Human Services | National Institutes of Health (NIH) 1DP2EB034563
6 · The paper itself

Abstract

Stretchable organic light-emitting diodes (OLEDs) are transforming human-machine interfaces and wearable technologies; still, their performance is considerably inferior to commercial, non-stretchable OLEDs, mainly limited by inefficient electron injection. We address this by redesigning both the electron transport layer and the cathode. For the former, we design a copolymer structure with high stretchability and ideal energy levels, achieving performance comparable with standard small-molecule electron transport layers. For the latter, we leverage the liquid metals embrittlement effect to confer stretchability to aluminium thin films, without compromising their electrical and optical characteristics. Combining these designs, we demonstrate fully stretchable OLEDs with a very high external quantum efficiency of 8% and a very low turn-on voltage of 3.5 V, which is on par with the reference rigid OLEDs utilizing the same emitter. This work tackles a crucial bottleneck in stretchable OLED development, bridging the performance gap between stretchable OLEDs and standard rigid OLEDs at the device level, paving the way for high-performance, skin-like displays.

Identifiers

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.