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Enhancing Performance and Stability in Perovskite Solar Cells: Materials Design and Engineering Approaches

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".

Deadline for manuscript submissions: 30 January 2026 | Viewed by 730

Special Issue Editors

Dr. Muhammad Azam

E-Mail Website
Guest Editor
School of Integrated Circuit Science and Engineering (Exemplary School of Microelectronics), University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: perovskite solar cells; photodetectors; organic solar cell; thin film
Dr. Junsheng Luo

E-Mail Website
Guest Editor
School of Integrated Circuit Science and Engineering (Exemplary School of Microelectronics), University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: organic optoelectronic functional materials and thin film devices; perovskite solar cells

Special Issue Information

Dear Colleagues,

Perovskite solar cells (PSCs) have emerged as one of the most promising next-generation photovoltaic technologies, achieving remarkable power conversion efficiencies (PCEs) approaching 27% in just over a decade of research. The rapid progress in device performance is largely attributed to the tunability of perovskite materials, innovative interface engineering, and novel device architectures. However, long-term operational stability remains a key challenge hindering the commercial viability of PSCs, especially under real-world conditions such as moisture, heat, light exposure, and bias stress according to International Summit on Organic Photovoltaic Stability (ISOS) protocols. Materials degradation, ion migration, interfacial reactions, and environmental sensitivity demand new strategies to ensure robust device performance and reliability.

This Special Issue aims to bring together cutting-edge research focused on advancing both the efficiency and stability of perovskite solar cells through material design and engineering approaches. We invite original research articles, reviews, and perspectives that explore innovative materials, doping strategies, interface optimization, encapsulation techniques, and degradation mechanisms.

Scope and Topics of Interest include (but are not limited to) the following:

  • Development of novel perovskite compositions for improved stability;
  • Doping and additive engineering for enhanced device performance;
  • Design of dopant-free and stable hole/electron transport layers;
  • Interface and surface passivation strategies;
  • Structural engineering in 2D/3D perovskites;
  • Encapsulation and environmental protection techniques;
  • Mechanistic studies on degradation and ion migration;
  • Scalable fabrication and industrial relevance;
  • Device architecture optimization (n-i-p, p-i-n, tandem);
  • Stability testing protocols and standardization efforts according to ISOS.

We welcome contributions that bridge fundamental understanding with practical solutions for durable and efficient PSCs.

Dr. Muhammad Azam
Dr. Junsheng Luo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • perovskite solar cells
  • additive engineering
  • stability
  • interface engineering
  • ion migration

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Published Papers (1 paper)

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Research

22 pages, 1206 KB  
Article
Genetic Algorithm-Based Hybrid Deep Learning Framework for Stability Prediction of ABO3 Perovskites in Solar Cell Applications
by Samad Wali, Muhammad Irfan Khan, Miao Zhang and Abdul Shakoor
Energies 2025, 18(19), 5052; https://doi.org/10.3390/en18195052 - 23 Sep 2025
Viewed by 550
Abstract
The intrinsic structural stability of ABO3 perovskite materials is a pivotal factor determining their efficiency and durability in photovoltaic applications. However, accurately predicting stability, commonly measured by the energy above hull metric, remains challenging due to the complex interplay of compositional, crystallographic, [...] Read more.
The intrinsic structural stability of ABO3 perovskite materials is a pivotal factor determining their efficiency and durability in photovoltaic applications. However, accurately predicting stability, commonly measured by the energy above hull metric, remains challenging due to the complex interplay of compositional, crystallographic, and electronic features. To address this challenge, we propose a streamlined hybrid machine learning framework that combines the sequence modeling capability of Long Short-Term Memory (LSTM) networks with the robustness of Random Forest regressors. A genetic algorithm-based feature selection strategy is incorporated to identify the most relevant descriptors and reduce noise, thereby enhancing both predictive accuracy and interpretability. Comprehensive evaluations on a curated ABO3 dataset demonstrate strong performance, achieving an R2 of 0.98 on training data and 0.83 on independent test data, with a Mean Absolute Error (MAE) of 8.78 for training and 21.23 for testing, and Root Mean Squared Error (RMSE) values that further confirm predictive reliability. These results validate the effectiveness of the proposed approach in capturing the multifactorial nature of perovskite stability while ensuring robust generalization. This study highlights a practical and reliable pathway for accelerating the discovery and optimization of stable perovskite materials, contributing to the development of more durable next-generation solar technologies. Full article
(This article belongs to the Special Issue Enhancing Performance and Stability in Perovskite Solar Cells: Materials Design and Engineering Approaches)
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