Evidence map›Paper›PMID 35277947›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022

Optimizing Piezoelectric Nanocomposites by High-Throughput Phase-Field Simulation and Machine Learning.

Weixiong Li, Tiannan Yang, Changshu Liu, Yuhui Huang, Chunxu Chen, Hong Pan, Guangzhong Xie, Huiling Tai, Yadong Jiang, Yongjun Wu and 4 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
  2. Physics-Embedded Neural Network: A Novel Approach to Design Polymeric Materials.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  3. Review
  4. Article
  5. Topology in Biological Piezoelectric Materials.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. A Review of Ultrathin Piezoelectric Films.Materials (Basel, Switzerland) · 2023
    Review
  11. Article
  12. Review
  13. Article
  14. Fully integrated wearable humidity sensor for respiration monitoring.Frontiers in bioengineering and biotechnology · 2022
    Article
  15. 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

14 authors.

Weixiong LiSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Tiannan YangSchool of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.
Changshu LiuSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Yuhui HuangLab of Dielectric Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310027, P. R. China.
Chunxu ChenSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Hong PanSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Guangzhong XieSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Huiling TaiSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Yadong JiangSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Yongjun WuLab of Dielectric Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310027, P. R. China.
Zhao KangSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Long-Qing ChenSchool of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.
Yuanjie SuSchool of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Zijian HongLab of Dielectric Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310027, P. R. China.ORCID 0000-0002-3491-0884

Funding

Basic Energy Sciences DE-SC0020145National Natural Science Foundation of China 62074027Office of ScienceU.S. Department of EnergyZhejiang Provincial Natural Science Foundation LD22E030005
6 · The paper itself

Abstract

Piezoelectric nanocomposites with oxide fillers in a polymer matrix combine the merit of high piezoelectric response of the oxides and flexibility as well as biocompatibility of the polymers. Understanding the role of the choice of materials and the filler-matrix architecture is critical to achieving desired functionality of a composite towards applications in flexible electronics and energy harvest devices. Herein, a high-throughput phase-field simulation is conducted to systematically reveal the influence of morphology and spatial orientation of an oxide filler on the piezoelectric, mechanical, and dielectric properties of the piezoelectric nanocomposites. It is discovered that with a constant filler volume fraction, a composite composed of vertical pillars exhibits superior piezoelectric response and electromechanical coupling coefficient as compared to the other geometric configurations. An analytical regression is established from a linear regression-based machine learning model, which can be employed to predict the performance of nanocomposites filled with oxides with a given set of piezoelectric coefficient, dielectric permittivity, and stiffness. This work not only sheds light on the fundamental mechanism of piezoelectric nanocomposites, but also offers a promising material design strategy for developing high-performance polymer/inorganic oxide composite-based wearable electronics.

Indexed as

NanocompositesElectronicsMachine LearningOxidesPolymersOxidesPolymershigh-throughput phase-field simulationmachine learningnanocompositespiezoelectric coefficient

Identifiers

PMID35277947
PMCPMC9069389

What OpenQuestion holds

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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.