Important Energy Research Articles

Wind farms reduce grassland plant community diversity and lead to plant community convergence

Climate warming has become a hot issue of common concern all over the world, and wind energy has become an important clean energy source. Wind farms, usually built in wild lands like grassland, may cause damage to the initial ecosystem and biodiversity. However, the impact of wind farms on the functional diversity of plant communities remains a subject with unclear outcomes. In this study, we chose 108 sample plots and identified 10 plant functional traits through a field vegetation survey. We used general linear regression analysis to assess how wind farm influenced vegetation community diversity, focusing on ten distinct plant functional traits. The study revealed that wind farm had significant impacts on grassland plant communities, diminishing diversity and functional traits, which leads to species composition convergence. Additionally, wind farm increased certain functional traits, like height and leaf area, while decreasing phosphorus content. Furthermore, the productivity of these plant communities was reduced by wind farm presence. This study highlights the negative consequences of wind farms in Inner Mongolia on plant diversity, aiming to offer scientific recommendations for the optimal arrangement of wind farms to safeguard biodiversity.

Comparison of Environmental Benefits between Photovoltaic and Wind Power Based on LCA Method

Since the 21st century, climate change is a global issue that affects every corner of the world and extreme weather occurs frequently. The Paris Agreement proposes that countries should strengthen their response to the threat of climate change. Countries around the world are actively seeking energy transition. Photovoltaic power generation and wind power generation are the most important renewable energy generation methods in the world. These two technologies are pollution-free and zero carbon emission during the power generation process. But from the perspective of the full life cycle, there is still some controversy over the environmental benefits of both at present. This article normalizes and analyzes the input-output data of the cradle to grave process using the LCA methodology, and the results indicate that the environmental impact of photovoltaic power generation throughout the full life cycle is significantly greater than that of wind power generation. Based on the above conclusions, several measures are proposed to improve the ecological benefits of both photovoltaic and wind power generation.

Hepatic metabolism and ketone production in metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is present in 25-35% of individuals in the United States. The purpose of this review is to provide the contextual framework for hepatic ketogenesis in MASLD and to spotlight recent advances that have improved our understanding of the mechanisms that drive its development and progression. Traditionally, hepatic ketogenesis has only been considered metabolically during prolonged fasting/starvation or with carbohydrate deplete ketogenic diets where ketones provide important alternative energy sources. Over the past 2 years, it has become increasingly clear from preclinical rodent and human clinical studies that hepatic ketogenic insufficiency is a key contributor to the initiation and progression of MASLD. A more thorough understanding of the metabolic dysregulation that occurs between the liver and extrahepatic tissues has significant potential in the development of innovative nutritional and pharmacological approaches to the treatment of MASLD.

Comparison of transient shrinkage behaviours between binary/ternary- FeO-rich oxides in CO/H2

Using clean energy in the ironmaking industry is expected to reduce the negative impacts on our environment. H2, one of the most important clean energies, has a great potential to partially replace CO in the blast furnace process, thus cutting down CO2 emission. In order to unravel the distinct effects on the shrinkage behaviour between CO and H2, four binary- FeO-rich oxides and four ternary- FeO-rich oxides were employed to compare their performance under the simulated blast furnace cohesive zone conditions. The results show that the formed olivine and solid solution have the intention to dominate the shrinkage of packed bed below 900°C, while the formed spinel compounds with higher melting point determine the shrinkage above 1300°C. In comparison to CO, H2 has a faster gaseous reduction rate. Therefore, the higher quantity of reduced iron and less disintegration of coke in the packed bed simultaneously suppresses the shrinkage between 900°C and 1000°C. Besides, the much slower iron carbonization rate in H2 postpones the re-accelerating of shrinkage as a result of melting and dripping to higher temperatures.

PARL regulates porcine oocyte meiotic maturation by mediating mitochondrial activity.

PARL is a rhomboid membrane protein that plays a crucial role in regulating the metabolism and maintaining the homeostasis of mitochondria which provide important energy and material reserves for oocyte maturation. However, the impact of PARL on oocyte maturation remains poorly understood. Here, we elucidated the pivotal role of PARL in oocyte maturation through its regulatory effects on mitochondrial activity. Specifically, our findings revealed that inhibiting PARL expression by interfering with RNA transcription in oocytes led to a substantial decrease in the rate of first polar body extrusion and early development of parthenogenetically activated embryos. Moreover, PARL deficiency disrupted mitochondrial distribution and activity, leading to the accumulation of ROS, abnormal distribution of CGs and actin, increased tubulin acetylation modification, disturbed spindle assembly and chromosome alignment, ultimately caused DNA damage in porcine oocytes at the metaphase II stage. Intriguingly, PARL deficiency did not cause occurrence of apoptosis in oocytes. Furthermore, our study highlighted that PARL deficiency caused the aberrant expression of genes associated with oocyte maturation, particularly those genes associated with mitochondrial function and DNA integrity. Collectively, these results demonstrate that the indispensable role of PARL in orchestrating porcine oocyte meiotic maturation though its modulation of mitochondrial activity.

Pollution Reduction and Carbon Reduction Technology Based on Pressure Swing Physical Adsorption Method in Power Enterprises

With the increasing global attention to environmental issues and climate change, power companies, as an important energy production sector, are facing severe challenges in reducing pollution and carbon emissions. In view of this, this study is based on the metal organic framework MIL-101(Cr), physically encapsulating metalloporphyrins and synthesizing a FeTPP@MIL-101(Cr) complex. Then, the surface characteristics and adsorption performance of the composite are evaluated, and the pressure swing physical adsorption method is introduced to achieve the goal of carbon reduction and pollution reduction. The ICP-OES loading results showed that the corresponding encapsulation amounts in MIL@-A and MIL@-B composites were 5.24% and 3.20%, respectively. Moreover, when the temperature increased from 273 K to 298 K, the adsorption capacity of all test gases on the three samples showed a decreasing trend. Under ideal atmospheric pressure conditions, the adsorption capacity of MIL@-A encapsulation for CO2 did not decrease and increased, while the adsorption capacity for N2 was relatively small, but still had a certain adsorption capacity. The above results indicate that combining the pressure swing physical adsorption method with FeTPP@MIL-101(Cr) complexes can effectively adsorb pollutants generated by power enterprises, achieve predetermined goals, and help promote clean production in power enterprises.

The fault diagnosis method for overall wind turbine systems with an integrated feature extraction method

Wind power has become one of the most important clean energy sources today, and the complex environment and physical structures lead to high operation and maintenance costs. Achieving rapid and precise wind turbine fault diagnosis can potentially decrease wind power’s operational and maintenance expenses. The conventional fault detection methods of the wind turbine system usually focus on one specific component, with multiple limitations, high computational complexity and low prediction efficiency. In this paper, a kind of feature extraction method integrated heatmap with MMSVM-RFE is applied on XGBoost model to diagnose overall wind turbine faults. The heatmap-MMSVM-RFE model presented in this paper fuses the advantages of the physical interpretability of the heatmap model with the mathematical statistics of the SVM model. A new criterion Ψ(α) is defined to assess whether the multi-faults model is comprehensively diagnosed. In the case study, the heatmap-MMSVM-RFE-XGBoost model has achieved the highest classification accuracy rate of 91%, which can broadly categorize faults. Compared to Random Forest and LightGBM, the integrated fault diagnosis model we propose improves Ψ(α) by 0.4% and 0.3%.

Proton Storage Chemistry in Aqueous Zinc-Inorganic Batteries with Moderate Electrolytes.

The proton (H+) has been proved to be another important energy storage ion besides Zn2+ in aqueous zinc-inorganic batteries with moderate electrolytes. H+ storage usually possesses better thermodynamics and reaction kinetics than Zn2+, and is found to be an important addition for Zn2+ storage. Thus, understanding, characterizing, and modulating H+ storage in inorganic cathode materials is particularly important. In this review, recent advances regarding the proton storage chemistry in aqueous zinc-inorganic batteries with moderate electrolytes are systematically reviewed. First, the four proton storage reaction patterns of H+ insertion, H+/Zn2+ co-insertion, H+-dependent conversion, and H+-dependent dissolution/deposition reaction are explicitly presented. Meanwhile, the proton storage processes of multi-sites and multi-steps, and the Hopping and Grotthuss proton transport mechanisms are carefully introduced. Second, the characterization techniques of proton storage are systematically classified into four types of electrochemical characterization techniques of batteries, structural characterization techniques of inorganic cathodes, pH characterization technique of electrolyte, and quantitative analysis technologies of H+ storage contribution. Third, the structural engineering of proton storage modulation is preliminarily refined to be interlayer engineering, doping engineering, defect engineering, composite engineering, and other engineering. Finally, the emerging challenges and perspectives about future directions of proton storage chemistry are proposed.

Vulnerable groups' access to agroforestry ecosystem services in north-eastern mountains in Tanzania and its implication on special needs inclusivity

Mountainous environments are particularly vulnerable to land degradation due to steep slopes, fragile soils, increasing population, severe shortages of pastureland, and climate change. This situation results in a loss of ecosystem services (ES), which unequally affects vulnerable groups who rely on access to ES closer to their homes. This study assesses the extent to which vulnerable groups access agroforestry systems’ ES in the Northern Mountains of Tanzania. A socioeconomic survey and descriptive and inferential statistics were employed to identify individual households with vulnerabilities and analyze their attributes and access to ES. Correlation analysis was employed to determine the relationships between the different types and levels of vulnerability and access to different ES from agroforestry. The results showed that the main types of vulnerabilities identified were single-headed households, including female-headed households, widowed-headed households, and households with one or more people living with a cognitive or physical disability. The results revealed that across the studied agroforestry systems, female-headed households are facing problems in accessing food (92%), timber (86%) and energy (75%). People living with disabilities indicated that they were problematic in accessing food (90%) and energy (76%). Among the studied Agroforestry systems, female-headed households in Miraba faced more difficulties in accessing the most important ES, that is, food (60%), timber (53%), and energy (50%). Our study can be of interest to future policy interventions for vulnerable groups, including special needs inclusivity in society. Finally, we discuss the potential implications of social support and welfare programmes in the northern mountainous environments of Tanzania.

Improving Solar Radiation Prediction in China: A Stacking Model Approach with Categorical Boosting Feature Selection

Solar radiation is an important energy source, and accurately predicting it [daily global and diffuse solar radiation (Rs and Rd)] is essential for research on surface energy exchange, hydrologic systems, and agricultural production. However, Rs and Rd estimation relies on meteorological data and related model parameters, which leads to inaccuracy in some regions. To improve the estimation accuracy and generalization ability of the Rs and Rd models, 17 representative radiation stations in China were selected. The categorical boosting (CatBoost) feature selection algorithm was utilized to construct a novel stacking model from sample and parameter diversity perspectives. The results revealed that the characteristics related to sunshine duration (n) and ozone (O3) significantly affect solar radiation prediction. The proposed new ensemble model framework had better accuracy than base models in root mean square error (RMSE), coefficient of determination (R2), mean absolute error (MAE), and global performance index (GPI). The solar radiation prediction model is more applicable to coastal areas, such as Shanghai and Guangzhou, than to inland regions of China. The range and mean of RMSE, MAE, and R2 for Rs prediction are 1.5737–3.7482 (1.9318), 1.1773–2.6814 (1.4336), and 0.7597–0.9655 (0.9226), respectively; for Rd prediction, they are 1.2589–2.9038 (1.8201), 0.9811–2.1024 (1.3493), and 0.5153–0.9217 (0.7248), respectively. The results of this study can provide a reference for Rs and Rd estimation and related applications in China.

DESIGN OF HIGH HEAD RUNNERS OF FRANSIC TURBINES

The energy characteristics of the hydroturbine, reflecting the total effect of the interaction of the flow with the working bodies, allow us to judge the operation of the machine as a whole. Information about the energy qualities of individual elements of the flow space is provided by the energy balance. Using the data of the energy balance, it is possible to identify the most favorable conditions for the joint operation of the elements of the flow space, that is, to achieve their agreement to increase the level of efficiency – the most important energy indicator of the hydroturbine. In order to improve the energy performance of the designed hydroturbine, various analyzes are conducted, that is, the dependence of the kinematic and energy characteristics of the hydroturbine on its geometric parameters is investigated. Such an analysis is carried out to find the most rational options for the flow space. The paper presents the design of the flow space of the high head hydroturbine FR400, performed with the help of programs developed at the department "Hydraulic machines named after G. F. Proskura". The method of energy characteristics analysis, based on the application of dimensionless parameters, is described. To improve the energy indicators at the preliminary stage of the hydro turbine design, multivariate calculations of the influence of the geometric indicators of the runner on the formation of the energy indicators of the hydroturbine are carried out. To substantiate and analyze the results, a predictive universal characteristic of the hydroturbine is built. To analyze the formation of energy characteristics of hydroturbines, the general kinematic properties of spatial lattices, as well as the general regularities of the interaction of the fluid flow with the runner, were used. The analysis of energy losses in the flow space of the high head turbine Francis: the spiral case, the guide vane, the runner and the draft tube at the optimal operating mode of the hydroturbine, as well as the analysis of the effect of the geometric elements of the runner on the changes in energy losses in the flow space, was performed. The given results of the calculation study confirm that in order to increase the level of efficiency, while maintaining the indicators of the optimal mode, it is necessary to change both the position of the starting edge of the impeller and the law of the distribution of angles along it.

Preparation and performance study of self-repairing coating with superhydrophobic properties

Electricity has become one of the most important energy sources required for the operation of today’s society, and related electrical facilities are constantly being constructed. However, the environment in which electrical facilities are located is complex, how to protect their key components from corrosion has become an urgent problem to be solved. In this study, a kind of superhydrophobic coating with self-repairing properties was prepared based on polycarbonate polyurethane, which can be used to some extent as an anti-corrosion coating in electrical systems. A series of polyurethanes were prepared by adjusting the ratio of various crosslinkers, and the formula that can produce the best comprehensive performance was determined. Specifically, due to the action of disulfide bonds and hydrogen bonds, the prepared polyurethane can achieve a maximum fracture strength of 7.99 MPa and a fracture elongation of 749.19 %, while also having a self-repairing efficiency of 90.86 %. By spraying modified SiO2 to the surface, the polyurethane surface has excellent superhydrophobic properties, with a maximum WCA of 169.67°, and still maintains superhydrophobic properties after being worn for 2100 cm by 800 mesh sandpaper. And the coating also has excellent anti-corrosion property with protecting Q235 metal steel from corrosion in NSS test for 120 h. It has shown great potential in the anti-corrosion application of metal materials in electrical systems.

Role of Fatty Acids β-Oxidation in the Metabolic Interactions Between Organs.

In recent decades, several discoveries have been made that force us to reconsider old ideas about mitochondria and energy metabolism in the light of these discoveries. In this review, we discuss metabolic interaction between various organs, the metabolic significance of the primary substrates and their metabolic pathways, namely aerobic glycolysis, lactate shuttling, and fatty acids β-oxidation. We rely on the new ideas about the supramolecular structure of the mitochondrial respiratory chain (respirasome), the necessity of supporting substrates for fatty acids β-oxidation, and the reverse electron transfer via succinate dehydrogenase during β-oxidation. We conclude that ATP production during fatty acid β-oxidation has its upper limits and thus cannot support high energy demands alone. Meanwhile, β-oxidation creates conditions that significantly accelerate the cycle: glucose-aerobic glycolysis-lactate-gluconeogenesis-glucose. Therefore, glycolytic ATP production becomes an important energy source in high energy demand. In addition, lactate serves as a mitochondrial substrate after converting to pyruvate + H+ by the mitochondrial lactate dehydrogenase. All coupled metabolic pathways are irreversible, and the enzymes are organized into multienzyme structures.

Data-Quality-Navigated Machine Learning Strategy with Chemical Intuition to Improve Generalization.

Generalizing real-world data has been one of the most difficult challenges for application of machine learning (ML) in practice. Most ML works focused on improvements in algorithms and feature representations. However, the data quality, as the foundation of ML, has been largely overlooked, also leading to the absence of data evaluation and processing methods in ML fields. Motivated by the challenge and need, we selected an important but difficult reorganization energy (RE) prediction task as a test platform, which is an important parameter for the charge mobility of organic semiconductors (OSCs), to propose a data-quality-navigated strategy with chemical intuition. We developed a data diversity evaluation based on structure characteristics of OSC molecules, a reliability evaluation method based on prediction accuracy, a data filtering method based on the uncertainty of K-fold division, and a data split technique by clustering and stratified sampling based on four molecular descriptor-associated REs. Consequently, a representative RE data set (15,989 molecules) with high reliability and diversity can be obtained. For the feature representation, a complementary strategy is proposed by considering the chemical nature of REs and the structure characteristics of OCS molecules as well as the model algorithm. In addition, an ensemble framework consisting of two deep learning models is constructed to avoid the risk of local optimization of the single model. The robustness and generalization of our model are strongly validated against different OSC-like molecules with diverse structures and a wide range of REs and real OSC molecules, greatly outperforming eight adversarial controls. Collectively, our work not only provides a quick and reliable tool to screen efficient OSCs but also offers methodological guidelines for improving the generalization of ML.

Rotation-based heat transfer enhancement for shell-and-tube latent thermal energy storage systems: From mechanisms to applications

Latent thermal energy storage (LTES) is an important energy storage technology to mitigate the discrepancy between energy source and energy supply, and it has great application prospects in many areas, such as solar energy utilization, geothermal energy utilization and electricity storage. However, LTES systems suffer from the low thermal conductivity of most phase-change materials (PCMs), threatening their large-scale commercial applications. To tackle this challenge, heat transfer enhancement for LTES systems is critically important and has been widely investigated worldwide. Convectional heat transfer enhancement techniques, including fins, nanoparticles and multiple PCMs, can significantly improve the charging and discharging rates of an LTES system. Recently, rotation-based methods have emerged to provide new routes for the heat transfer enhancement of LTES systems, and many achievements have been obtained by researchers around the world. This study conducted a short review of the mechanisms and applications of three rotation-based heat transfer enhancement methods, aiming to provide deep insights into these novel heat transfer enhancement methods and propel their future development and applications.

Transcriptomic analysis of codon usage patterns and gene expression characteristics in leafy spurge

Leafy spurge (Euphorbia esula) is an important herb and potential energy source with medicinal value. Codon usage bias (CUB) is a static feature of genes and genomes that results from adaptation and selection during long-term evolution and facilitates molecular breeding in transgenic plants. Here, we used TransDecoder to identify candidate coding regions from the downloaded leafy spurge transcriptome and generate coding region annotation files based on reference genomes. The whole genome showed A/T bias, especially at terminal positions, and seven high-frequency codons were identified. We compared codon usage frequencies to identify candidate exogenous expression receptor systems for leafy spurge. The identified factors affecting leafy spurge CUB included natural selection and other factors, mutation pressure and base composition, with natural selection and other factors being dominant. The observed CUB was significantly positively correlated with the gene expression levels. Systematic analysis of whole-genome leafy spurge revealed that highly expressed protein-coding genes presented greater CUB than did less expressed protein-coding genes. Furthermore, the highly expressed genes tended to have terminal G/C bases. In summary, we conducted a series of related studies based on the leafy spurge whole-genome sequence and laid a foundation for selecting suitable exogenous expression receptor systems and improving gene expression levels.

A Computable General Equilibrium (CGE) Approach for Linking Energy Security and Primary Energy Supply Reduction Targets in Pakistan

This study examines the effects of reducing primary energy supply by 5%, 10%, and 15% through policy interventions from 2005 to 2050 on energy resource diversification, energy and oil import dependency, environmental emissions and energy security in Pakistan. Applying a CGE framework, the study finds that policy scenarios lead to decrease in cumulative primary energy supply, a rise in renewable energy, and a drop in greenhouse gas emissions. The results also show improved energy security, with a reduction in net energy import dependency, a decrease in net oil import dependency and a increase in energy resource diversification. These findings suggest that setting primary energy supply reduction targets could strengthen energy security in Pakistan.

Development of a Superior Anion Exchange Membrane with Hyperbranched Polymer for Anion Exchange Membrane Water Electrolysis

Hydrogen is a clean and renewable energy, that provides numerous potential benefits to industries, and households, with zero greenhouse gas emissions, and increased energy security. Mainly hydrogen energy is widely seen as a key component to combat climate change that could potentially fulfill the global energy demands in the future. Hence, hydrogen production technologies are considered an important energy and R&D sector in both academics and industries. Currently, water with its abundance in electrolysis mode is known to be an effective route of green hydrogen production. Specifically, hydrogen production via anion exchange membrane water electrolysis (AEMWE) is a promising green technology gaining significant attention in recent times owing to its advantages, efficiency, and simplicity. In AEMWE, the membranes play a crucial role in determining the efficiency, stability, and pilot scale strategies. However, AEMs face several limitations due to their linear polymer backbone structure which can lead to mechanical and chemical instability, ultimately impacting the durability and performance of the AEMWE. That is, the linear backbone which is responsible for controlling the mobility of ions, affects the ionic resistance, and mechanical strength of the membrane. Given this, the present work addresses the limitations of linear polymer backbones and proposes hyperbranched polymers and dendrimers. Generally, hyperbranched polymers have highly branched structure that offers improved mechanical and chemical stability compared to linear polymers and thus enhance the stability that could provide durability and improve the performance compared to that of linear AEMs. Furthermore, blending hyperbranched polymers with dendrimers yield a high density of functional groups that facilitate ion transport and reduce ionic resistance by allowing efficient movement of ions, leading to increased efficiency in hydrogen production. The proposed innovative strategy offers a significant advancement in AEMWE systems.The production of hyperbranched polycarbonate was carried out via a polycondensation reaction involving dimethyl carbonate and trimethylolpropane ethoxylate, utilizing 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) as the catalyst. The poly(aminoamide) dendrimer was synthesized through a step-growth polymerization process catalyzed by DBU, to form a dendritic polymer. Following the synthesis, both the hyperbranched polycarbonate and the dendrimer were individually blended with polyether sulfone. The blending step aims to augment the overall performance of the resultant materials, leveraging the unique properties of each component to achieve a synergistic effect.The hyperbranching by polycarbonate is characterized by high branching and functionality, which is aimed at improving the mechanical strength and chemical stability of anion exchange membranes (AEMs). On the other hand, the poly(aminoamide) dendrimer structure (shown in the below Figure) is found to enhance the ion exchange capacity and water uptake properties, which are crucial for increasing the efficiency of hydrogen production via electrolysis. Overall the synthesized anion exchange membrane was characterized to confirm the incorporation of hyperbranched polycarbonate and poly(aminoamide) dendrimers within a polyethersulfone matrix. The detailed characterization confirmed a significant improvement in ionic conductivity and ion exchange capacity, which could facilitate the effective ionic pathways and the abundance of functional groups from the hyperbranched structures. Moreover, the membrane exhibited remarkable alkaline stability, maintaining its structural integrity and performance in strong alkaline environments, a crucial attribute for durability in practical applications. Furthermore, the results showed that the membrane achieves an optimal balance between water uptake and swelling, absorbing sufficient water to aid efficient ion transport while minimizing swelling, due to the precise hyperbranched and dendrimer network. Conclusively, the optimized hyperbranched membrane ensures effective functionality in operational stability under a variety of conditions without compromising its dimensional stability. Importantly, the membrane's mechanical integrity was tested and the results confirm the robust nature of the hyperbranched structure, indicating significant resistance to the physical stresses. Overall, the developed AEM exhibits a combination of enhanced ionic conductivity, optimal water uptake, superior alkaline stability, and robust mechanical properties, positioning it as a promising candidate for AEMWE. Figure: Schematic illustration of linear polymer backbone with hyperbranched network. Figure 1

High-Performance Bipolar Membranes for Direct Seawater Electrolysis

Hydrogen (H2) is an important energy carrier for the development and maintenance of a low-carbon economy through sustainable energy generation. Direct seawater electrolysis (DSWE), which produces hydrogen using seawater, an infinite resource, as an electrolyte, is a very promising process. However, hydroxide ions generated from the hydrogen evolution reaction at the cathode cause precipitation of multi-valent cations contained in seawater, which blocks the active sites of the catalyst and induces high cell voltage. In this study, a high-performance bipolar membrane (BPM) was developed to effectively prevent the formation of inorganic deposits in the direct seawater electrolysis process. BPM has a structure in which a cation-exchange layer and an anion-exchange layer are superimposed and the characteristic of generating H+ and OH- ions by decomposing water molecules under reverse bias conditions. Therefore, the BPM has been actively used to produce acids and bases from salts, and its use has recently been expanding in energy conversion processes such as a fuel cell. In this study, a high-performance BPM was fabricated using woven fabric support and a specially designed transition metal-based catalyst that can significantly improve water decomposition performance. The prepared membrane had an efficient water-splitting catalyst and a 3D bipolar interface, showing excellent water-splitting capability and interfacial stability. In addition, it was confirmed that using the prepared BPM greatly contributes to stable hydrogen production when applied to the DSWE process. This work was supported in part by the NRF grants (NRF-2022M3H4A4097521) as well as by the framework of the research and development program of the KIER (No. C2-2473).

Doping Effects of Metal-Doped Tin Oxide Nanoparticles Used As Carbon-Free ORR Catalysts for Polymer Electrolyte Fuel Cells

Polymer electrolyte fuel cells (PEFCs) are an important energy device for the realization of a hydrogen society. However, a longer service life is essential for the further spread of PEFCs. Currently, catalyst ( platinum supported on carbon, Pt/C) is the most mainstream cathode one. But, it has durability issues due to carbon degradation during high potential sweeps. As an alternative material to carbon, tin oxide (SnO2) is attracting attention due to its electrical conductivity and chemical stability. It has already been reported that Pt/SnO2 catalysts using SnO2 doped with antimony (Sb), niobium (Nb), tantalum (Ta), etc., and they exhibit high durability. However, they have a lower Pt electrochemical surface area (ECSA) and oxygen reduction mass activity (MA) compared to Pt/C. Therefore, further improvement of ECSA and MA is required for the practical use of Pt/SnO2. Other dopants may improve catalyst activity, so it’s worth checking the effects for doping other elements. In this study, a total of 20 metal-doped tin oxides (M-doped SnO2) were synthesized. Pt metal-doped tin oxide (Pt/ M-SnO2) was prepared by loading platinum onto the synthesized M-doped SnO2, and its catalytic performance was evaluated. M-doped SnO2 nanoparticles were synthesized by the solvothermal method. Tin chloride pentahydrate, metal chlorides as doping materials, methanol, and tetramethylammonium hydroxide solution were mixed and stirred to form a precursor. The solution was placed in a Teflon-coated stainless steel autoclave and heat treated. After 12 hours, the reactants were washed and dried to obtain M-doped SnO2. Pt/M-SnO2 was prepared using the polyol method. The prepared M-doped SnO2 powder was mixed and dispersed in a mixed solvent of ethylene glycol and water, then platinum chloride hexahydrate was added and stirred overnight. The solution was then heated at 120°C for 2 hours to produce the platinum nanoparticles on the SnO2 surface. The activity evaluation of the prepared catalysts was carried out at a rotating disk electrode in a three-electrodes cell system. The electrolyte was 0.1 M HClO4, the counter electrode was a platinum wire electrode, the reference electrode was a reversible hydrogen electrode, and the working electrode was a glassy carbon disk (GCD) electrode. Catalyst ink was dripped onto the working electrode and dry by spinning at 300 rpm for 1 hour. Measurements were performed by cyclic voltammetry (CV) and linear sweep voltammetry (LSV). From the obtained peak, ECSA and MA values were calculated. Among the Pt/M-doped SnO2, Pt/Mo-SnO2 and Pt/Sb-SnO2 showed specific peaks. In the CV, the peak area of the lower left part corresponding to the H2 adsorption was greatly enlarged in Pt/Mo-SnO2. As a result, Pt/Mo-SnO2 recorded the highest ECSA value (74.4 m2g-1 -Pt), exceeding that of Pt/pure-SnO2 (24.1 m2g-1 -Pt). In the LSV, the onset potential of the Pt/Sb-SnO2 peak shifted to the higher side than Pt/pure-SnO2. As a result, Pt/Sb-SnO2 recorded the highest value of Mass Activity (93.5 A g-1 -Pt), which is much higher than that of Pt/pure-SnO2 (17.1 A g-1 -Pt). The catalytic performance is significantly changed by doping metallic elements into tin oxide crystal.