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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Features from Perovskite Project Database

Authors: Sepúlveda, Alexander;

Features from Perovskite Project Database

Abstract

The data are drawn from the Perovskite Database Project dataset (https://www.perovskitedatabase.com/). In this study, a coding process is applied in which each perovskite material is represented by a four-dimensional vector obtained through a Local Linear Embedding (LLE) procedure. Additional descriptors capture characteristics related to the synthesis process of the perovskite solar cell.

Related Organizations
Keywords

Machine learning, Perovskite Solar Cells

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average