Evidence map›Paper›PMID 35745356›Full record

ArticleNanomaterials (Basel, Switzerland)2022

Unveiling Evolutionary Path of Nanogenerator Technology: A Novel Method Based on Sentence-BERT.

Huailan Liu, Rui Zhang, Yufei Liu, Cunxiang He

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Huailan LiuSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Rui ZhangSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Yufei LiuCenter for Strategic Studies, Chinese Academy of Engineering, Beijing 100088, China.
Cunxiang HeSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.

Funding

Construction Project of China Knowledge Center for Engineering Sciences and Technology CKCEST-2022-1-30National Natural Science Foundation of China 72104224, 71974107, L2124002, 91646102
6 · The paper itself

Abstract

In recent years, nanogenerator technology has developed rapidly with the rise of cloud computing, artificial intelligence, and other fields. Therefore, the quick identification of the evolutionary path of nanogenerator technology from a large amount of data attracts much attention. It is of great significance in grasping technical trends and analyzing technical areas of interest. However, there are some limitations in previous studies. On the one hand, previous research on technological evolution has generally utilized bibliometrics, patent analysis, and citations between patents and papers, ignoring the rich semantic information contained therein; on the other hand, its evolution analysis perspective is single, and it is difficult to obtain accurate results. Therefore, this paper proposes a new framework based on the methods of Sentence-BERT and phrase mining, using multi-source data, such as papers and patents, to unveil the evolutionary path of nanogenerator technology. Firstly, using text vectorization, clustering algorithms, and the phrase mining method, current technical themes of significant interest to researchers can be obtained. Next, this paper correlates the multi-source fusion themes through semantic similarity calculation and demonstrates the multi-dimensional technology evolutionary path by using the "theme river map". Finally, this paper presents an evolution analysis from the perspective of frontier research and technology research, so as to discover the development focus of nanogenerators and predict the future application prospects of nanogenerator technology.

Indexed as

multi-source datananogeneratortechnology evolutionary pathtext vectorizationtheme miningtheme river map

Identifiers

PMID35745356
PMCPMC9229696

What OpenQuestion holds

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Registered trials

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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.