Energy advances最新文献

Semi-analytical models describing transport phenomena governed by the Laplace equation (like conduction of charge carriers or heat) are presented for the case of a porous composite with two solid phases and one pore-phase (i.e., two conducting and one insulating phase), closing the existing gap in the literature for fast and accurate predictions for this particular case. The models allow for an efficient screening of promising concepts and material combinations, as they are computationally much more efficient compared to numerical simulations on a 3D geometry. Three different semi-analytical models (Maxwell, Xu and MST models) are compared and validated using a microstructure dataset of perovskite–CGO solid oxide cell electrodes obtained by stochastic modeling. Based on the results from both numerical and semi-analytical models, the effects of the resulting composite transport properties are discussed for the application example of these fully ceramic electrodes. CGO and the used LSTN perovskite are both mixed ionic and electronic conductors (MIECs), which leads to different reaction mechanisms and associated requirements for the microstructure design compared to, e.g., Ni–YSZ. Due to the MIEC-property of both solid phases, the transport of neither electrons nor oxygen ions is limited to a single phase. Consequently, the composite conductivity, which is inherent to MIEC electrodes, opens a much larger design space for microstructure optimization compared to the single-phase conductivity of conventional electrodes, which are prone to percolation failure.

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The energy sector is transitioning to a low-carbon era requiring the wide use of renewable energy sources, mainly wind and solar. In this context, aluminum could serve as a sustainable energy carrier as it stores energy in a safe and compact way. It could be used to help decarbonize remote communities and industries, trade energy on a global scale, or provide seasonal energy storage. The Hall–Héroult process, reducing aluminum oxides to aluminum, is already a technology deployed at an industrial scale. The maturity of this industry could therefore be leveraged to store electricity. To convert aluminum back to power, it can be fully oxidized with high-temperature liquid water. The hydrogen and high-temperature heat produced can then be converted to power using a combination of heat engines and/or fuel cells. For this concept to be viable, the oxides produced must be collected and reduced in a sustainable way. In this work, aluminum recharging costs were evaluated by reviewing the current reduction process and the literature available on the development of inert anodes, a technology enabling carbon-free smelting. Results show that aluminum can be cost-competitive on a chemical energy basis with most common hydrogen carriers discussed in the literature. To contextualize the findings, a remote mine case study integrates transportation, storage and power generation costs for aluminum, compared to liquefied hydrogen and ammonia. The analysis reveals that aluminum is comparable to other carbon-free solutions, although they all currently remain more expensive than diesel fuel at an input electricity price of $30/MWh_e. Aluminum emerges as marginally more expensive than the direct use of ammonia, while avoiding concerns related to toxicity and NO_x emissions. This study thus positions aluminum as a promising energy carrier that merits further consideration in various other applications.

This research aims to advance the field of vanadium redox flow batteries (VRFBs) by introducing a pioneering approach to optimize the microstructural characteristics of carbon cloth electrodes. Addressing the traditional challenge of developing high-performance electrode materials for VRFBs, this study employs a robust, generalizable, and cost-effective data-driven modeling and optimization framework. A novel sampling strategy using low-discrepancy Latin Hypercube and quasi-Monte Carlo methods generates a small-scale, high-fidelity dataset with essential space-filling qualities for training supervised machine learning models. This study goes beyond conventional methods by constructing two surrogate models: a random forest regressor and a gradient boosting regressor as objective functions for optimization. The integration of a non-dominated sorting genetic algorithm II (NSGA-II) for multi-objective optimization facilitates exhaustive exploration of the surrogate models, leading to the identification of electrode designs that yield enhanced energy efficiencies (EEs) under specific operating conditions. The application of NSGA-II in exploring surrogate models not only facilitates the discovery of realistic design combinations but also adeptly manages trade-offs between features. The mean pore diameter was reduced compared to the tested carbon cloth electrodes while maintaining a similar permeability value based on the results obtained using the developed algorithms. Based on this suggestion, a new type of carbon cloth electrode has been fabricated by introducing a carbonaceous binder into the woven fabric to make carbon cloths with more complex pore structures and reduced mean pore diameter. The new electrode demonstrates 24% and 66% reduction in average ohmic and mass transport resistances, respectively, validating the machine-learning recommendations. This research highlights the critical role of improved electrical conductivity and porosity in carbon materials, showing their direct correlation with increased EE. Overall, this study represents a significant step forward in developing more efficient and practical VRFBs, offering a valuable contribution to the renewable energy storage landscape.

The renaissance of photochemistry and the explosion of photo- and photoelectro-catalysis open new opportunities in organic photocatalyst design and applications towards solar fuels and sustainable organic reactivity. In this perspective, we discuss the relevant case of quinacridone (QA) dyes: these have long been known to the scientific community, but their application in photocatalysis is recent and still explored in a limited way. This is somehow surprising given that QA is a cheap and readily available organic pigment, and in front of the appealing properties of QA derivatives, including intense absorption in the visible region, balanced redox properties making them suitable for both oxidative and reductive photochemistry, and versatility to several operative conditions. We will discuss recent examples of photo- and photoelectrochemical processes taking advantage of QA dyes, from solution photocatalysis to photoactive materials and devices (nanoparticles, covalent organic frameworks, photoelectrodes); the target applications include water splitting, carbon dioxide reduction, and organic transformations. We aim to show the potential of organic photocatalyst design and implementation, and to inspire the readers with new opportunities in this field.

NiO electrodes are widely applied in p-type dye-sensitized solar cells (DSSCs) and photoelectrochemical cells, but due to excessive charge recombination, the efficiencies of these devices are still too low for commercial applications. To understand which factors induce charge recombination, we studied electrodes with a varying number of NiO layers in benchmark P1 p-DSSCs. We obtained the most efficient DSSCs with four layers of NiO (0.134%), and further insights into this optimum were obtained via dye loading studies and in operando photoelectrochemical immittance spectroscopy. These results revealed that more NiO layers led to an increasing light harvesting efficiency (η_LH), but a decreasing hole collection efficiency (η_CC), giving rise to the maximum efficiency at four NiO layers. The decreasing η_CC with more NiO layers is caused by longer hole collection times, which ultimately limits the overall efficiency. Notably, the recombination rates were independent of the number of NiO layers, and similar to those observed in the more efficient n-type DSSC analogues, but hole collection was an order of magnitude slower. Therefore, with more NiO layers, the beneficial increase in η_LH can no longer counteract the decrease in η_CC due to slow hole collection, resulting in the overall efficiency of the solar cells to maximize at four NiO layers.

The design and development of highly efficient electrocatalysts from transition metals have shown a great potential for substituting precious metal-based electrocatalysts in water-splitting processes. Cobalt oxide is one of the promising materials for oxygen evolution reaction (OER). Modifying the metal oxide by the incorporation of metal ions and substituting sulfides are effective but challenging strategies for achieving efficient OER activities. In the present work, we report the synthesis of CdCoO and CdCoS electrocatalysts deposited on the surface of nickel foam. These electrocatalysts and their composites CdCoO@CuCoO and CdCoS@CuCoS could deliver high catalytic activity for oxygen evolution reaction. The as-synthesized electrocatalysts were characterized using pXRD, FTIR spectroscopy, Raman spectroscopy, XPS, and SEM techniques. The CdCoS showed a lower OER overpotential of 199 mV at a current density of 10 mA cm⁻² and 522 mV at 60 mA cm⁻². The incorporation of Cd²⁺ ions in the cobalt oxides optimized the electronic states around the Co active sites, leading to improved catalytic activities and a lower overpotential compared to other reported cobalt oxides (such as oxyhydroxides). This work emphasizes the effect of metal-ion incorporation and sulfide modification on the OER activity of cobalt oxide for water splitting and provides a multicomponent engineering strategy for designing efficient electrocatalysts.

The urgent need for new energy storage devices has promoted studies on alkaline metal-based batteries with high energy density and long life. In this case, two-dimensional (2D) inorganic non-conductive materials have exhibited unique physicochemical properties, making them ideal candidates for energy storage and conversion owing to their planar structure, high surface-to-volume ratio, and non-electronic conductive nature. Among the 2D inorganic non-conductive materials, hexagonal boron nitride (h-BN), graphitic nitride (g-C₃N₄), montmorillonite (MMT), and vermiculite (VMT) have shown potential application in alkaline metal-based batteries. Herein, the strategies developed for the synthesis of these inorganic two-dimensional non-conductive materials in recent years and their applications as electrode material additives, metal anode supports, and building blocks of solid interfacial and separator additives in alkali metal-based batteries are comprehensively reviewed. Subsequently, challenges associated with the use of 2D materials in alkali metal-based batteries to improve their performance are discussed and possible solutions are proposed. These 2D inorganic non-conductive materials have potential to be widely used in alkali-based batteries in the future considering their unique structure and properties.

2D hybrid perovskites have been in focus as better alternatives to their 3D counterparts to solve long-term stability issues. In this regard, investigation of their stability and possible degradation mechanism in the presence of moisture is of utmost necessity. A detailed analysis with the help of ab initio molecular dynamics simulations has been carried out to understand their interaction with water interfaces for the first time. Various possible terminations of Ruddlesden–Popper (RP) and Dion–Jacobson (DJ) phases of 2D hybrid perovskites have been considered. We monitor the various possible interactions in the perovskite/water interface model to reveal the robustness of various terminations. PbI₂ terminated structures are found to interact mainly through Pb–O interactions, and the DJ phase is found to be more robust. I₂ formation is found to be the possible degradation route for I terminated phases. The importance of the bulky hydrophobic organic cation layer is highlighted, whose unique arrangement plays an essential role in resisting water infiltration and dissolution of surface components in the case of organic cation terminated phases. Interestingly, the organic cation layer is found to be robust in 2D hybrid perovskites compared to reported 3D perovskites. Our study signifies the opportunity to tune the cation layer, thereby maintaining moisture stability without compromising the optoelectronic properties of 2D hybrid perovskites, thus contributing to the fundamental understanding of 2D hybrid perovskites at water interfaces.

This work is focused on the investigation of three different Bi-based materials, i.e., CaBi₂O₂(CO₃)₂ (CBOC), Ca₄Bi₆O₁₃ (CBO), and Bi₂Ce₂O₇ (BCO), as photocatalysts in N₂O reduction. This study has emphasized the effectiveness of the bismuth ion, irrespective of its presence in different structures with self-regulating electronic and morphological properties, when employed as a photocatalyst. Monophasic CBOC, CBO, and BCO samples have been synthesized by wet-chemical methods, and they exhibit distinct morphological features such as plate-like, dumbbell-shaped, and irregularly shaped crystallites. From the UV-visible diffuse reflectance spectroscopy (DRS) data, CBO exhibits a lower optical band gap of 2.52 eV compared to CBOC (3.95 eV), which CBO is synthesized from. BCO shows the lowest optical band gap of 2.16 eV. CBO exhibits the highest photocurrent generation and the lowest value in work function measurements, following the trend as CBO > CBOC > BCO. The efficiency of the Bi-based materials in photocatalytic decomposition of N₂O also follows a similar trend as observed in the photocurrent measurements, wherein the CBO sample exhibits a maximum of 10.4% decomposition of N₂O under UV-A in 24 h. Oxygen vacancies in CBO and BCO have been reasoned to play a crucial role in the photocatalytic decomposition of N₂O.