Evidence map›Paper›PMID 39952948›Full record

ArticleScientific data2025

Auto-generating a database on the fabrication details of perovskite solar devices.

Agnes Valencia, Fei Liu, Xiangyang Zhang, Xiangkun Bo, Weilu Li, Walid A Daoud

Abstract read
In one paragraph

Article in Scientific data, 2025. 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

6 authors.

Agnes ValenciaDepartment of Mechanical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China.ORCID http://orcid.org/0000-0001-8279-2766
Fei LiuDepartment of Mechanical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China.
Xiangyang ZhangDepartment of Mechanical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China.ORCID http://orcid.org/0000-0001-7873-1127
Xiangkun BoDepartment of Mechanical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China.
Weilu LiDepartment of Mechanical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China.
Walid A DaoudDepartment of Mechanical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China. wdaoud@cityu.edu.hk.ORCID http://orcid.org/0000-0002-5807-5043

Funding

City University of Hong Kong (CityU) 7020038
6 · The paper itself

Abstract

The rapid development of perovskite solar devices has led to a rising number of publications over the past decade. As a result, a project aiming to compile all published device data was initiated in 2022. However, with its method of manual data collection, one of the project's hurdles is encouraging the participation of the perovskite community to spend time and effort in inputting new device data. To ensure the project's sustainability, adequate participation is necessary but is challenging to achieve. In response to this, we propose the utilization of natural language processing algorithms to extract various attributes of perovskite solar devices from journal articles. When data collection is performed by programs instead of humans, the lack of community participation can be overcome. For each device, the identifying device information, intrinsic device data, extrinsic cell definition, and the details of the fabrication procedure were extracted. A total of 30 attributes from 3164 journal articles were compiled, with an average accuracy of 0.899. The dataset and source code are made publicly available.

Identifiers

PMID39952948
PMCPMC11828846

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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.