**Material Selection, Optimization, and Performance Prediction of Perovskite Solar Cells Using a Gradient Boosting Machine Learning Model**

Research focuses on material selection, optimization, and performance prediction of aerospace structures using machine learning techniques to identify lightweight, durable, and high-performance materials for advanced aerospace applications.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-19
DOI
https://doi.org/10.5281/zenodo.23464673
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

**Material Selection, Optimization, and Performance Prediction of Perovskite Solar Cells Using a Gradient Boosting Machine Learning Model**

Muhammad Rizwan Javed
Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Materials Science
article

**Material Selection, Optimization, and Performance Prediction of Perovskite Solar Cells Using a Gradient Boosting Machine Learning Model**

Muhammad Rizwan Javed
article en

Abstract

Research focuses on material selection, optimization, and performance prediction of aerospace structures using machine learning techniques to identify lightweight, durable, and high-performance materials for advanced aerospace applications.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 28%
Machine Learning in Materials Science
DOIOpen Access PDFOpenAlex
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**Material Selection, Optimization, and Performance Prediction of Perovskite Solar Cells Using a Gradient Boosting Machine Learning Model** — Muhammad Rizwan Javed · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS