New Breakthrough in CO2 Electroreduction: Nitrided Copper-Iron Composite Oxides Transform Carbon Dioxide into Valuable Chemicals！

2024-10-08

We are excited to announce a groundbreaking study published in the latest issue of Energy Storage and Conversion (Volume 2, Issue 2, 2024), featuring a novel material that significantly advances the field of carbon dioxide (CO2) electroreduction. The article introduces a new class of catalysts derived from layered double hydroxides (LDHs) that have demonstrated exceptional performance in converting CO2 into methane (CH4) and formic acid (HCOOH).

Revolutionizing CO2 Reduction with Nitrided Copper-Iron Oxides

Researchers at the State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, have developed an innovative approach to electrocatalytic CO2 reduction. By utilizing a gas-phase nitriding process with urea as the nitrogen source, they have successfully synthesized amorphous nitrided copper-iron oxides from CuFe-LDH precursors. This material has shown a remarkable total Faraday efficiency of 74.7% at -0.7 V vs. RHE, coupled with impressive durability in H-cell testing for continuous 10-hour periods.

Addressing Global Warming with Advanced Material Science

The study addresses the pressing issue of global warming by targeting the major contributor to this crisis—CO2 emissions. The combustion of fossil fuels is a significant source of atmospheric CO2, and this research offers a promising solution to transform these emissions into valuable chemical products, thereby contributing to a more sustainable future.

In-Depth Analysis and Cutting-Edge Techniques

The research team conducted a comprehensive analysis of the synthesized material using state-of-the-art techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), and X-ray photoelectron spectroscopy (XPS). These analyses revealed the amorphous nature of the material, which is crucial for generating active defect sites that enhance catalytic reactions.

Electrochemical Performance and Reaction Mechanisms

The electrochemical performance of the nitrided copper-iron composite oxides was evaluated in a 0.5 M KHCO3 electrolyte, demonstrating a lower onset potential and high selectivity for C1 products. The team also employed in situ attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) to elucidate the reaction mechanisms, providing insights into the conversion of CO2 to *COOH and subsequent formation of HCOOH and CH4.

A Promising Future for CO2 Electroreduction Catalysts

This study not only showcases the potential of amorphous copper-iron oxide nitrides as catalysts for CO2 electroreduction but also paves the way for the design of more efficient catalysts. The findings are a testament to the commitment of the scientific community to tackle environmental challenges through advanced material science and electrochemistry.

Acknowledgments and Contributions

The article acknowledges the contributions of all authors and the support from the National Natural Science Foundation of China, the Fundamental Research Funds for the Central Universities, and the Program for Changjiang Scholars and Innovative Research Teams in University.

For more detailed information, tables, and figures, please refer to the article content.

About Energy Storage and Conversion: Energy Storage and Conversion is a leading journal dedicated to publishing high-quality research on energy-related topics, fostering innovation, and promoting sustainable energy solutions.

Join us in celebrating this significant advancement in the quest for sustainable energy and environmental solutions.

Editor-in-Chief

Prof. Xiaohu Yang

Xi'an Jiaotong University, China

eISSN

3029-2778

Publication Frequency

Quarterly

About the Publisher

Academic Publishing insists on taking academic exchange and publication as the main line, carrying out comprehensive management based on science and technology, and fully exploring excellent international publishing resources. Within 5 years, it will form a strategic framework and scale with science (S), technology (T), medicine (M), education (E), and humanities and arts (H) as the main publishing fields. Academic Publishing is headquartered in Singapore and based in Malaysia, with the United States and China providing the main scientific and academic resources. At the same time, it has established long-term good cooperative relations with other publishing companies, scientific research communities, and academic organizations in more than a dozen countries and regions. Academic Publishing uses English and Chinese as its main publishing languages, mainly publishing books, journals, and conference papers in print and online. The vast majority of publications follow the international open access policy, providing stable and long-term quality and professional publications. With the joint efforts of the expert team and our professional editorial team, our publications will gradually be indexed by international databases in stages to provide convenient and professional retrieval for various scholars. At the same time, manuscripts we accept will be subject to the peer review principle, and cutting-edge and innovative research articles will be preferentially accepted for peer reference and discussion. All kinds of our publications are welcome for peer to contribute, access, and download.

more

Volume Arrangement

2024

2023

Featured Articles

Nitrided Copper-Iron Composite Oxides Derived from Layered Double Hydroxides for Enhanced Carbon Dioxide Electroreduction to Methane and Formic Acid

The reduction of carbon dioxide to valuable chemical products is a promising solution to address carbon balance and energy issues. Herein, amorphous nitrided copper-iron oxides are prepared by gas-phase nitriding of Cu Fe-layered double hydroxide precursor s with urea as nitrogen source. Amorphous materials are more likely to generate defect vacancies during the reaction process, and these vacancies can function as active sites for catalytic reactions. Therefore, the obtained materials show high activity for CO 2 electroreduction to methane and formic acid, achieving a total Faraday efficiency of 74.7% at −0.7 V vs RHE and exhibiting a continuous 10 h durability in the H-cell. The uniformly distributed Cu + sites act as active sites by losing electrons to activate CO 2 . During the CO 2 electroreduction , CO 2 is converted to *COOH via proton-electron coupling, *COOH combines directly with a proton in solution to produce the HCOOH product, and the other part of *COOH undergoes a protonated dehydration process to form the *CHO intermediate which dehydrates again to form CH 4 . This study provides a new approach for designing CO 2 electroreduction catalysts.

AlZnO magnetron sputtered thin film for photovoltaic application

Aluminum zinc oxide (AZO) is a nontoxic and a low-cost material that finds application as a transparent conducting electrode in photovoltaic devices. In this study the (direct current) DC magnetron sputtering of AZO films is carried out at different deposition times of 5, 10, 15, 20 and 25 min’s at room temperature and it’s structural, optical, electrical and morphological properties are studied for its use as a front contact for thin film solar cell application. The structural study suggests that the preferred orientation of grains along (002) plane having hexagonal structure and the optical and the electrical studies suggest that the films show an average transmission of 70% and a resistivity of the order of 10 -4 Ωcm. On the other hand, the scanning electron microscopy (SEM) images suggest the formation of packed grains having a homogeneous surface. Moreover in order to study the optoelectronic properties of prepared samples, the electronic and optical calculations of the AZO are performed by the first-principles calculations using density functional theory (DFT).

Investigation of self-excited induction generator for supporting domestic loads and its extension to a microgrid

This study provides a technical and financial analysis for the incorporation of a microgrid structure with a wind energy conversion system for producing electricity. This study’s primary aim is to provide solutions for issues that arise when isolated induction generators are employed with microgrids. A closed-loop smart electronic load controller is used to regulate the loads in the system that are supplied by the generation. A switched variable capacitor bank is used to supply reactive power initially during a voltage dip at varying winds and loads to sustain the voltage profile. Additionally, a simple voltage control loop-based controller for the generator side converter maintains the voltage at a steady level. Using HOMER software, an economic study of the suggested wind-based microgrid structure is also presented. A laboratory experimental setup is used to support the MATLAB/Simulink study of the proposed method and its control. The findings back the feasibility of implementing the suggested plan in grid-isolated regions for supplying critical loads.

Research progress on ZnO/MoS2/rGO ternary photocatalysts

Energy shortage and environmental pollution have become one of the important global issues, and semiconductor photocatalytic technology is considered as one of the effective means to solve these problems. As a new and efficient green material, ZnO has attracted wide attention. ZnO is widely used in the field of photocatalysis due to its non-toxicity, low cost, environmental friendliness, adjustable band gap, high electron density, and chemical stability. However, the recombination of photogenerated charge carriers in ZnO hinders its practical application and lowers the utilization efficiency of visible light. On the other hand, molybdenum disulfide/reduced graphene oxide (MoS 2 /rGO), as a binary non-precious metal co-catalyst, has a larger specific surface area, suitable band gap width, and visible light response capability compared to single-phase graphene co-catalyst. Therefore, introducing MoS 2 /rGO co-catalyst into the ZnO system can provide more active sites, reduce the probability of photogenerated charge carrier recombination, and improve the utilization efficiency of visible light. In this review, we summarize the hydrothermal synthesis methods for preparing this highly demanded nanocomposite material, including one-step and stepwise methods. Subsequently, we elaborate on the mechanism of enhancing light absorption and achieving efficient electron-hole separation behavior in the ternary system heterojunction structure during the photocatalytic process. Due to its significant advantages, this ternary system heterojunction structure has been widely applied in the field of photocatalysis, including applications such as pollutant degradation, sterilization, and water splitting.

Wind power forecasting technologies: A review

This study addresses the critical role of wind power forecasting in ensuring stable and reliable power system operations. Wind Power Forecasting is critical for the efficient operation of plant, time scheduling, and it’s balancing of power generation with grid integration systems. Due to its dependency on dynamic climatic conditions and associated factors, accurate wind power forecasting is challenging. The research delves into various aspects, including input data, input selection techniques, data pre-processing, and forecasting methods, with the aim of motivating researchers to design highly efficient online/offline models on weather-based data. The overarching goal is to enhance the reliability and stability of power systems while optimizing energy resource utilization. The analysis reveals that hybrid models offer more accurate results, highlighting their significance in the current era. This study investigates different Wind Power Forecasting (WPF) models from existing literature, focusing on input variables, time horizons, climatic conditions, pre-processing techniques, and sample sizes that affect model accuracy. It covers statistical models like ARMA and ARIMA, along with AI techniques including Deep Learning (DL), Machine Learning (ML), and neural networks, to estimate wind power.