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Innovative Catalytic Approaches for Energy Conversion and Storage

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: 25 August 2026 | Viewed by 914

Special Issue Editor


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Guest Editor
School of Nuclear Science, Energy and Power Engineering, Shandong University, Jinan 250001, China
Interests: air pollution control; carbon capture, utilization and storage; environmental catalysis; energy conversion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue delves into the cutting-edge catalytic strategies that are pivotal for energy conversion and storage, with a particular focus on environmental sustainability and pollution control. The topics encompass the innovative catalytic approaches for energy conversion and storage, highlighting the significance of these technologies in achieving high efficiency and large-scale applications with minimal pollution or greenhouse gas emissions.

The issue underscores the importance of air pollution control, emphasizing the role of catalytic processes in mitigating emissions from both stationary and mobile sources. Notably, the control of NOx and VOCs, which are key pollutants contributing to air pollution, is a central theme. The application of environmental catalysis in reducing nitrogen oxides from power plants and other stationary sources, as well as in processing oil to produce cleaner fuels, is discussed.

The journal also explores the computational modeling and simulation of catalytic reactions for environmental protection. This includes the development of new catalytic materials and the understanding of their performance in removing pollutants from air and water. The durability and reusability of these materials, as well as the by-products formation in the catalytic process, are critical aspects that are examined.

Nuclear energy pollution control is another significant area covered in this issue. The discussion includes the challenges and advancements in managing pollution associated with nuclear energy production, highlighting the need for effective catalytic solutions to minimize environmental impact.

The Special Issue will focus on, but is not limited to, the following themes:

  • The development of innovative catalytic materials for the elimination of gas, liquid, and solid-phase pollutants, with an emphasis on their application in real mixtures of pollutants removal from outdoor and indoor air, water, and wastewater.
  • The advancement of knowledge in recent catalytic processes such as photo-catalysis, plasma-catalysis, and electro-catalysis, applied to environmental protection, and the challenges faced in promoting their application to full scale.
  • The role of environmental catalysis in the development of new and cleaner chemical processes, characterized by the use of safer reagents and the production of limited by-products.

The application of heterogeneous catalysis in mobile and stationary air de-pollution devices, wastewater treatments, and the development of clean new fuels, such as hydrogen and biodiesel.

Dr. Xiao Zhu
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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

  • air pollution control
  • environmental catalysis
  • catalytic strategies
  • energy conversion
  • environmental sustainability
  • catalytic materials
  • clean energy technologies
  • photothermal catalysis

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Published Papers (1 paper)

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Research

19 pages, 32031 KB  
Article
Performance Prediction of Perovskite-Catalyzed CO2 Decomposition Based on Machine-Learning Method
by Jiayi Chen, Kun Wang, Huaqing Xie, Kerong Ma and Kunlun Li
Energies 2026, 19(6), 1388; https://doi.org/10.3390/en19061388 - 10 Mar 2026
Viewed by 434
Abstract
Perovskite oxides show excellent catalytic performance for thermochemical CO2 splitting, with A/B-site cation substitution further enhancing redox activity. While traditional first-principles methods are computationally expensive, machine learning (ML) provides an efficient approach to perovskite optimization. In this paper, machine learning is employed [...] Read more.
Perovskite oxides show excellent catalytic performance for thermochemical CO2 splitting, with A/B-site cation substitution further enhancing redox activity. While traditional first-principles methods are computationally expensive, machine learning (ML) provides an efficient approach to perovskite optimization. In this paper, machine learning is employed to investigate and predict the performance of perovskite catalysts in CO2 decomposition reactions. Based on 227 perovskite compositions (A1A2)(B1B2)O3 curated from experimental literature, a total of five ML models are used, including Decision Tree, Bagging, Random Forest, Extra Trees, and Gradient Boosting Regression (GBR). The Random Forest model performed best. After hyperparameter optimization, the Random Forest model achieved an R2 of 0.910 and an MAE of 41.528 on an independent test set. SHAP analysis indicated that the thermal reduction temperature (T1) and the B1-site stoichiometric fraction (C_b1) are the most influential features governing the predicted CO yield. A higher CO yield is predicted when C_b1 ranges from 0.6 to 0.8, and T1 exceeds 1300 °C. This behavior can be attributed to the enhanced formation of oxygen vacancies at elevated temperatures and the optimized electronic structure induced by appropriate B-site stoichiometry. Full article
(This article belongs to the Special Issue Innovative Catalytic Approaches for Energy Conversion and Storage)
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