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Critical to boosting photoelectrochemical (PEC) performance is improving visible light absorption, accelerating carrier separation, and reducing electron–hole pair recombination. In this investigation, the PVD/RF method was employed to fabricate WO3 thin films that were subsequently treated using the surface treatment process, and the film surface was modified by introducing varying concentrations of cobalt nanoparticles, a non-noble metal, as an effective Co catalyst. The results show that the impact of loaded cobalt nanoparticles on the film surface can explain the extended absorption spectrum of visible light, efficiently capturing photogenerated electrons. This leads to an increased concentration of charge carriers, promoting a faster rate of carrier separation and enhancing interface charge transfer efficiency. Compared with a pristine WO3 thin film photoanode, the photocurrent of the as-prepared Co/WO3 films shows a higher PEC activity, with more than a one-fold increase in photocurrent density from 1.020 mA/cm2 to 1.485 mA/cm2 under simulated solar radiation. The phase, crystallinity, and surface of the prepared films were analysed using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy. The PVD/RF method, scanning electron microscopy (FE-SEM), and high-resolution transmission electron microscopy (HR-TEM) were employed to assess the surface morphology of the fabricated film electrode. Optical properties were studied using UV–vis absorbance spectroscopy. Simultaneously, the photoelectrochemical properties of both films were evaluated using linear sweep voltammetry and electrochemical impedance spectroscopy (EIS). These results offer a valuable reference for designing high-performance photoanodes on a large scale for photoelectrochemical (PEC) applications.

Photocatalytic hydrogen evolution represents a transformative avenue in addressing the challenges of fossil fuels, heralding a renewable and pristine alternative to conventional fossil fuel-driven energy paradigms. Yet, a formidable challenge is crafting a high-efficacy, stable photocatalyst that optimizes solar energy transduction and charge partitioning even under adversarial conditions. Within the scope of this investigation, tantalum–iron heterojunction composites characterized by intricate, discoidal nanostructured materials were meticulously synthesized using a solvothermal-augmented calcination protocol. The X-ray diffraction, coupled with Rietveld refinements delineated the nuanced alterations in phase constitution and structural intricacies engendered by disparate calcination thermal regimes. An exhaustive study encompassing nano-morphology, electronic band attributes, bandgap dynamics, and a rigorous appraisal of their photocatalytic prowess has been executed for the composite array. Intriguingly, the specimen denoted as 1000-1, a heterojunction composite of TaO2/Ta2O5/FeTaO4, manifested an exemplary photocatalytic hydrogen evolution capacity, registering at 51.24 µmol/g, which eclipses its counterpart, 1100-1 (Ta2O5/FeTaO4), by an impressive margin. Such revelations amplify the prospective utility of these tantalum iron matrices, endorsing their candidacy as potent agents for sustainable hydrogen production via photocatalysis.

Amidst the global challenges posed by pollution, escalating energy expenses, and the imminent threat of global warming, the pursuit of sustainable energy solutions has become increasingly imperative. Thermoelectricity, a promising form of green energy, can harness waste heat and directly convert it into electricity. This technology has captivated attention for centuries due to its environmentally friendly characteristics, mechanical stability, versatility in size and substrate, and absence of moving components. Its applications span diverse domains, encompassing heat recovery, cooling, sensing, and operating at low and high temperatures. However, developing thermoelectric materials with high-performance efficiency faces obstacles such as high cost, toxicity, and reliance on rare-earth elements. To address these challenges, this comprehensive review encompasses pivotal aspects of thermoelectricity, including its historical context, fundamental operating principles, cutting-edge materials, and innovative strategies. In particular, the potential of one-dimensional nanostructuring is explored as a promising avenue for advancing thermoelectric technology. The concept of one-dimensional nanostructuring is extensively examined, encompassing various configurations and their impact on the thermoelectric properties of materials. The profound influence of one-dimensional nanostructuring on thermoelectric parameters is also thoroughly discussed. The review also provides a comprehensive overview of large-scale synthesis methods for one-dimensional thermoelectric materials, delving into the measurement of thermoelectric properties specific to such materials. Finally, the review concludes by outlining prospects and identifying potential directions for further advancements in the field.

Real-time energy management of battery storage in grid-connected microgrids can be very challenging due to the intermittent nature of renewable energy sources (RES), load variations, and variable grid tariffs. Two reinforcement learning (RL)–based energy management systems have been previously used, namely, offline and online methods. In offline RL, the agent learns the optimum policy using forecasted generation and load data. Once the convergence is achieved, battery commands are dispatched in real time. The performance of this strategy highly depends on the accuracy of the forecasted data. An agent in online RL learns the best policy by interacting with the system in real time using real data. Online RL deals better with the forecasted error but can take a longer time to converge. This paper proposes a novel dual layer Q-learning strategy to address this challenge. The first (upper) layer is conducted offline to produce directive commands for the battery system for a 24 h horizon. It uses forecasted data for generation and load. The second (lower) Q-learning-based layer refines these battery commands every 15 min by considering the changes happening in the RES and load demand in real time. This decreases the overall operating cost of the microgrid as compared with online RL by reducing the convergence time. The superiority of the proposed strategy (dual-layer RL) has been verified by simulation results after comparing it with individual offline and online RL algorithms.

Securing net-zero targets by employing sustainable materials for the built environment is highly desirable, and this can be achieved by retrofitting existing non-smart windows with thermoelectric (TE) glazing, providing improved thermal performance along with green electricity production. It is reported that TE glazing could produce ~4000 kWh of power per year in a cold climate with a temperature differential of ~22 °C. This feature of TE materials drives their emplacement as an alternative to existing glazing materials and could lead to the identification of optimum solutions for smart window development. However, few attempts have been made to employ TE materials in glazing. Therefore, in this brief review, we discuss, for the first time, the efforts made to employ TE in glazing, identify their drawbacks, and discuss potential solutions. Furthermore, the working principle, suitable materials, and methods for developing TE glazing are discussed. In addition, this article introduces a new research area and provides researchers with detailed instructions on how to build and optimize this system. The maximum efficiency of a thermoelectric material is determined by its thermoelectric figure of merit, which is a well-defined metric to characterize a device operating between the hot-side and cold-side temperatures. TE material’s figure of merit promises new perspectives on the conceivable future energy-positive built environment. The role of TE in tackling the energy crisis is also discussed, since it provides sustainable energy alternatives

Photocatalytic degradation is one of the environmentally friendly methods used in treating dye wastewater. In this study, a series of MXene/g-C3N4 heterostructure photocatalysts with different loading amounts of MXene (1, 4, 8, and 12 wt.%) were successfully synthesized via the wet impregnation method and their photocatalytic activity was evaluated via the degradation of methylene blue under visible-light irradiation. As such, the 1 wt.% MXene/g-C3N4 heterostructure photocatalyst achieved a high degradation of methylene blue compared to the pure g-C3N4 under visible-light illumination of 180 min. This significant improvement was attributed to the intimate interfacial contact, evidently from the FESEM analysis, which allows the smooth photocharge carriers to transport between g-C3N4 and MXene. Additionally, the larger BET surface area demonstrated by the 1 wt.% MXene/g-C3N4 heterostructure allowed this sample to have higher adsorption of dye molecules and provided a higher number of reactive sites, which was beneficial for the enhancement of the photocatalytic activity. Nevertheless, it was found that the excessive loading of MXene can substantially impede photocatalytic activity. This was attributed to the decrease in the active sites, as well as the weakened crystallinity of the MXene/g-C3N4 heterostructure photocatalyst, evident from the FTIR and XRD analysis. All in all, this study has shown the potential of the MXene/g-C3N4 photocatalyst as a promising photocatalyst for highly efficient wastewater treatment applications.

Supercapacitors (SCs) have received much interest due to their enhanced electrochemical performance, superior cycling life, excellent specific power, and fast charging–discharging rate. The energy density of SCs is comparable to batteries; however, their power density and cyclability are higher by several orders of magnitude relative to batteries, making them a flexible and compromising energy storage alternative, provided a proper design and efficient materials are used. This review emphasizes various types of SCs, such as electrochemical double-layer capacitors, hybrid supercapacitors, and pseudo-supercapacitors. Furthermore, various synthesis strategies, including sol-gel, electro-polymerization, hydrothermal, co-precipitation, chemical vapor deposition, direct coating, vacuum filtration, de-alloying, microwave auxiliary, in situ polymerization, electro-spinning, silar, carbonization, dipping, and drying methods, are discussed. Furthermore, various functionalizations of SC electrode materials are summarized. In addition to their potential applications, brief insights into the recent advances and associated problems are provided, along with conclusions. This review is a noteworthy addition because of its simplicity and conciseness with regard to SCs, which can be helpful for researchers who are not directly involved in electrochemical energy storage.

Grid-connected microgrids consisting of renewable energy sources, battery storage, and load require an appropriate energy management system that controls the battery operation. Traditionally, the operation of the battery is optimised using 24 h of forecasted data of load demand and renewable energy sources (RES) generation using offline optimisation techniques, where the battery actions (charge/discharge/idle) are determined before the start of the day. Reinforcement Learning (RL) has recently been suggested as an alternative to these traditional techniques due to its ability to learn optimal policy online using real data. Two approaches of RL have been suggested in the literature viz. offline and online. In offline RL, the agent learns the optimum policy using predicted generation and load data. Once convergence is achieved, battery commands are dispatched in real time. This method is similar to traditional methods because it relies on forecasted data. In online RL, on the other hand, the agent learns the optimum policy by interacting with the system in real time using real data. This paper investigates the effectiveness of both the approaches. White Gaussian noise with different standard deviations was added to real data to create synthetic predicted data to validate the method. In the first approach, the predicted data were used by an offline RL algorithm. In the second approach, the online RL algorithm interacted with real streaming data in real time, and the agent was trained using real data. When the energy costs of the two approaches were compared, it was found that the online RL provides better results than the offline approach if the difference between real and predicted data is greater than 1.6%.

Electrochemical CO2 reduction reaction (CO2RR) provides a promising approach to curbing harmful emissions contributing to global warming. However, several challenges hinder the commercialization of this technology, including high overpotentials, electrode instability, and low Faradic efficiencies of desirable products. Several materials have been developed to overcome these challenges. This mini-review discusses the recent performance of various cobalt (Co) electrocatalysts, including Co-single atom, Co-multi metals, Co-complexes, Co-based metal–organic frameworks (MOFs), Co-based covalent organic frameworks (COFs), Co-nitrides, and Co-oxides. These materials are reviewed with respect to their stability of facilitating CO2 conversion to valuable products, and a summary of the current literature is highlighted, along with future perspectives for the development of efficient CO2RR.

Covalent organic frameworks (COFs) are emerging crystalline polymeric materials with highly ordered intrinsic and uniform pores. Their synthesis involves reticular chemistry, which offers the freedom of choosing building precursors from a large bank with distinct geometries and functionalities. The pore sizes of COFs, as well as their geometry and functionalities, can be pre-designed, giving them an immense opportunity in various fields. In this mini-review, we will focus on the use of COFs in the removal of environmentally hazardous metal ions and chemicals through adsorption and separation. The review will introduce basic aspects of COFs and their advantages over other purification materials. Various fabrication strategies of COFs will be introduced in relation to the separation field. Finally, the challenges of COFs and their future perspectives in this field will be briefly outlined.

Gold nanoparticles (Au NPs) play a significant role in science and technology because of their unique size, shape, properties and broad range of potential applications. This review focuses on the various approaches employed for the synthesis, modification and functionalization of nanostructured Au. The potential catalytic applications and their enhancement upon modification of Au nanostructures have also been discussed in detail. The present analysis also offers brief summaries of the major Au nanomaterials synthetic procedures, such as hydrothermal, solvothermal, sol-gel, direct oxidation, chemical vapor deposition, sonochemical deposition, electrochemical deposition, microwave and laser pyrolysis. Among the various strategies used for improving the catalytic performance of nanostructured Au, the modification and functionalization of nanostructured Au produced better results. Therefore, various synthesis, modification and functionalization methods employed for better catalytic outcomes of nanostructured Au have been summarized in this review.

Nanostructured Bi2WO6 thin film electrodes with enhanced solar energy conversion and photocatalytic properties have been fabricated using Aerosol-Assisted Chemical Vapor Deposition (AACVD). By conveniently controlling the deposition process parameters, Bi2WO6 electrodes were fabricated with nanoplates and hierarchical buckyball-shaped microsphere structures morphology. A detailed study has been conducted to correlate the structure and morphology with the photoelectrochemical (PEC) and photocatalytic dye degradation performance. The PEC investigations revealed that the hierarchical buckyball-shaped microsphere structured Bi2WO6 electrodes have shown the photocurrent density of 220 μAcm−2 while nanoplates have a photocurrent density of 170 μAcm−2 at 0.23 V (vs. Ag/AgCl/3M KCl) under AM1.5 illumination. The PEC characterization of Bi2WO6 electrodes also reveals that the photocurrent density and photocurrent onset potential is strongly dependent on the orientation and morphology, hence the deposition parameters. Similarly, the methylene blue (MB) and rhodamine B (RhB) photodegradation performance of Bi2WO6 electrodes also show a strong correlation with morphology. This finding provides an appropriate route to engineer the energetic and interfacial properties of Bi2WO6 electrode to enhance solar energy conversion and the photocatalytic performance of semiconductor materials.