Achieve Energy Sustainability Research Articles

Hollow core-shell heterojunction TAPB-COF@ZnIn2S4 as highly efficient photocatalysts for carbon dioxide reduction.

The conversion of carbon dioxide (CO2) into carbon-neutral fuels using solar energy is crucial for achieving energy sustainability. However, the high carrier charge recombination and low CO2 adsorption capacity of the photocatalysts present significant challenges. In this paper, a TAPB-COF@ZnIn2S4-30 (TAPB-COFZ-30) heterojunction photocatalyst was constructed by in situ growth of ZnIn2S4 (ZIS) on a hollow covalent organic framework (HCOF) with a hollow core-shell structure for CO2 to CO conversion. Both experimental studies and theoretical calculations indicate that the construction of heterojunctions improves the efficiency of carrier separation and utilisation in photocatalysis. The yield of photoreduction of CO2 to CO by the TAPB-COFZ-30 heterojunction photocatalyst reached 2895.94 μmol g-1 with high selectivity (95.75%). This study provides a feasible strategy for constructing highly active core-shell composite photocatalysts to optimize CO2 reduction.

Ultrafast Synthesis of IrB1.15 Nanocrystals for Efficient Chlorine and Hydrogen Evolution Reactions in Saline Water.

The production of storable hydrogen fuel through water electrolysis powered by renewable energy sources such as solar, marine, geothermal, and wind energy presents a promising pathway toward achieving energy sustainability. Nevertheless, state-of-the-art electrolysis requires support from ancillary processes which often incur financial and energy costs. Developing electrolysers capable of directly operating with water that contains impurities can circumvent these processes. Herein, we demonstrate the efficient and durable electrolysis of saline water to produce chlorine gas (Cl2) and hydrogen using structurally ordered IrB1.15, synthesized through ultrafast joule heating. IrB1.15 exhibits remarkable performance, achieving overpotentials of 75 mV for the chlorine evolution reaction (CER) and 12 mV for hydrogen evolution reactions (HER) at current densities of 10 mA cm-2. Moreover, IrB1.15 displays a durability of over 90 h towards both CER and HER. Density functional theory reveals that IrB1.15 has adsorption energies significantly closer to 0 eV for Cl and H, compared to IrO2 and Pt/C. Furthermore, in situ Raman investigations reveal that Ir in IrB1.15 serves as the active center for CER, while the introduction of B atoms to Ir lattices mitigates the formation of absorbed hydrogen species on the Ir surface, thereby enhancing the performance of IrB1.15 in HER.

Ultrafast Synthesis of IrB1.15 Nanocrystals for Efficient Chlorine and Hydrogen Evolution Reactions in Saline Water

The production of storable hydrogen fuel through water electrolysis powered by renewable energy sources such as solar, marine, geothermal, and wind energy presents a promising pathway toward achieving energy sustainability. Nevertheless, state‐of‐the‐art electrolysis requires support from ancillary processes which often incur financial and energy costs. Developing electrolysers capable of directly operating with water that contains impurities can circumvent these processes. Herein, we demonstrate the efficient and durable electrolysis of saline water to produce chlorine gas (Cl2) and hydrogen using structurally ordered IrB1.15, synthesized through ultrafast joule heating. IrB1.15 exhibits remarkable performance, achieving overpotentials of 75 mV for the chlorine evolution reaction (CER) and 12 mV for hydrogen evolution reactions (HER) at current densities of 10 mA cm−2. Moreover, IrB1.15 displays a durability of over 90 h towards both CER and HER. Density functional theory reveals that IrB1.15 has adsorption energies significantly closer to 0 eV for Cl and H, compared to IrO2 and Pt/C. Furthermore, in‐situ Raman investigations reveal that Ir in IrB1.15 serves as the active center for CER, while the introduction of B atoms to Ir lattices mitigates the formation of absorbed hydrogen species on the Ir surface, thereby enhancing the performance of IrB1.15 in HER.

Developing sustainable chalcogenide for energy storage: Investigating the semiconducting MnS2: CuS: CoS2: Ni2S3 quaternary complexes as supercapacitor electrode material

Electrochemical energy storage is crucial in today’s urbanized world to achieve energy sustainability. Using a single source precursor technique, a unique and energy-efficient semiconducting [manganese: copper: cobalt: nickel] sulphide (MnS2: CuS: CoS2: Ni2S3) composite chalcogenide system has been synthesized for the first time. The resulting dithiocarbamate metallic sulfide exhibits a median crystallite size of 36.55 nm as well as a relatively small band gap of 2.61 eV. Many bonds, including the metal sulfide bond, were found, according to a functional group analysis. MnS2: CuS: CoS2: Ni2S3 was morphologically manifested as irregularly shaped particles that tended to form sphere-like shapes. MnS2: CuS: CoS2: Ni2S3 based electrode was measured for electrochemical charge-storing behaviour. With an excellent capacitance spanning around 956.76F g−1, the tetra-chalcogenide-decorated electrode demonstrated a favourable capacity for charge storage, according to the results of cyclic voltammetry conducted in 1 M potassium hydroxide. This suggests that there is a lot of potential for long-term energy storage using the electrode. This electrode elucidated the particular power density of 10020.12 W kg−1 in addition to a lowered series resistance of (Rs) = 1.98 Ω based on the impedance investigations.

Kinematics-guided data-driven energy surrogate model for robotic additive manufacturing

With the increase in the usage of industrial robots for manufacturing applications, there will be a corresponding rise in energy consumption. Especially, robotic additive manufacturing (AM) has demonstrated significant potential for working autonomously in hazardous or extraterrestrial settings, as well as for producing large-scale structures. Recent advancements have made it possible for teams of robots to collaborate for printing structures even larger than their sizes together. Utilizing robots efficiently for AM is essential for achieving energy sustainability goals. The literature on energy models for robots and AM processes lacks a comprehensive energy model for robotic AM. To address this gap, a multi-point trajectory-based energy model is proposed for robotic AM. The model is created to help users manufacture parts in an energy-efficient way. These simulations require a significant amount of computation time, which limits their usage to offline purposes only. Hence, we propose two energy surrogate models for real-time predictions: a pure data-driven model and a kinematics-guided data-driven model. The kinematics-guided approach is an enhanced version of pure data-driven model which learns from inverse kinematics solutions along the trajectory to understand the robot’s dynamics and kinematics. There were two test cases conducted. The first test case consisted of paths that were feasible, printable, and within the robot’s reach, while the second test case consisted of a mixture of paths that were both feasible and infeasible. In comparison to the pure data-driven approach, the kinematics-guided approach stood out in both testing cases. Two real-world case studies have been used to demonstrate that the proposed approach can be used in lieu of simulations for real-time applications. Especially in the second case, where the part was placed very close to the robot making a portion of the part infeasible to print, the proposed approach correctly identified that it was not possible to print the geometry due to the robot’s kinematics. The proposed kinematics-guided approach is 195 and 700 times faster than the simulation results, respectively, in two case studies, and thus supporting the use of the proposed approach for real-time applications.

System design and analysis of thermal power dispatch systems for boiling water reactors

Nuclear power plants are crucial to meeting net zero emission goals and achieving energy sustainability. Integrating these plants with clean energy technologies such as high-temperature steam electrolysis (HTSE) may improve the efficiency and economic competitiveness of these plants. The current study investigates the design and operation of a thermal power dispatch (TPD) system for coupling boiling water reactors (BWRs) to HTSE plants. The TPD system extracts a portion of the steam from the reactor’s main steam line and transfers its thermal energy to an HTSE plant through a power transport loop. A TPD system for 5 % steam extraction has been designed and the system performance during steady and transient operations has been analyzed. The TPD system dispatched a total of 197 MW thermal energy to the HTSE plant under nominal design conditions. Saturated steam at 7.17 MPa from the BWR plant was condensed and subcooled to a temperature of 168 °C, while a mass flow rate of 91.1 kg/s of superheated steam was dispatched to the HTSE plant. Furthermore, the system performance during transient operation showed a continuous transition from the initial hot standby mode to the nominal power dispatch level. The transient simulation results emphasized the importance of investigating component level performance for the TPD system design. The current results will guide future works on the development of integrated energy systems for hydrogen production or process heat applications.

A Comprehensive Review of the Current Status of Smart Grid Technologies for Renewable Energies Integration and Future Trends: The Role of Machine Learning and Energy Storage Systems

The integration of renewable energy sources (RES) into smart grids has been considered crucial for advancing towards a sustainable and resilient energy infrastructure. Their integration is vital for achieving energy sustainability among all clean energy sources, including wind, solar, and hydropower. This review paper provides a thoughtful analysis of the current status of the smart grid, focusing on integrating various RES, such as wind and solar, into the smart grid. This review highlights the significant role of RES in reducing greenhouse gas emissions and reducing traditional fossil fuel reliability, thereby contributing to environmental sustainability and empowering energy security. Moreover, key advancements in smart grid technologies, such as Advanced Metering Infrastructure (AMI), Distributed Control Systems (DCS), and Supervisory Control and Data Acquisition (SCADA) systems, are explored to clarify the related topics to the smart grid. The usage of various technologies enhances grid reliability, efficiency, and resilience are introduced. This paper also investigates the application of Machine Learning (ML) techniques in energy management optimization within smart grids with the usage of various optimization techniques. The findings emphasize the transformative impact of integrating RES and advanced smart grid technologies alongside the need for continued innovation and supportive policy frameworks to achieve a sustainable energy future.

The effectiveness of applying the economic and technological dimensions of the kingdom of Saudi Arabia’s vision 2030 to achieve the competitive advantage of the Hail Region

This research focuses on examining the impact of Saudi Arabia’s Vision 2030 on the energy industry, specifically in the Hail region, by exploring the role of technological and economic strategies in fostering sustainable energy development. The study aims to identify key factors that facilitate the implementation of Vision 2030 to assess the current energy landscape in Saudi Arabia. By delving into the economic and technological dimensions of Vision 2030, the research seeks to determine the essential components that the Kingdom of Saudi Arabia needs to establish systems and initiatives that align with global scientific and technological advances, ensuring competitiveness and progress in the global arena. By surveying 60 faculty members from Hail University, the study employs a descriptive-analytical approach to unravel how economic activities and technological advancements collaborate to shape a sustainable and competitive energy sector. The findings highlight the crucial role of technological innovations, including advances in administrative processes, human resource management, regulatory frameworks, and technical infrastructure related to energy efficiency and renewable energy technologies. Furthermore, the study evaluates economic aspects such as labor market reforms, skill development programs, and support for emerging energy enterprises. The results underscore the positive impact of technological and economic interventions on the energy sector in the Hail region, with significant improvements in energy project management efficiency and the creation of a conducive environment for sustainable energy practices. The study reveals that the integration of technological and economic initiatives has led to notable improvements in the energy sector, reflected in average values ranging from 68% to 84%. These results underscore the fundamental role of Vision 2030 in advancing sustainable energy development and underscore the importance of leveraging economic and technological strategies to achieve energy sustainability and competitive advantage. This research contributes to understanding how Saudi Arabia’s Vision 2030 is driving progress in the energy industry and emphasizes the importance of integrating economic and technological approaches in shaping a sustainable energy landscape. The findings provide valuable information for policymakers and stakeholders in the energy sector, highlighting the need for concerted efforts to harness economic and technological advancements to promote sustainable energy development. By showcasing the transformative impact of Vision 2030 on the energy sector in the Hail region, this study underscores the originality and importance of research in advancing the goals of sustainable energy development in Saudi Arabia.

Energy, Society and Sociodemographic Constraints Nexus: Development and Future Prospects

To overcome the challenges faced by the energy sector, policymakers need to prioritize the development of strategic policies that promote the adoption of waste-to-energy technologies, Tidal energy, solar power systems, and wind farms. These policies should emphasize the integration of renewable energy sources into the existing energy infrastructure, ensuring a more sustainable and resilient energy supply for urban areas. The study underscores the importance of collaboration between various stakeholders, including government bodies, private sector entities, and local communities. By fostering partnerships and creating incentives, it becomes possible to mobilize resources and expertise towards the implementation of renewable energy projects. This collaboration would not only address the energy crisis but also contribute to job creation and overall socioeconomic development. Proper utilization of renewable energy resources can resolve the dilemma of energy crises in the country. According to our results, solar stood first in the overall ranking followed by Tidal, waste-to-energy, and wind energies. Solar performed better in indigenous manufacturing and development, resource potential, and technological development. Pakistan has abundant green energy resources which could be utilized by the formation of a proper policy roadmap and mitigation of policy pathways to overcome the hazardous dependence on fossil fuels for energy requirements. The implementation of policies adopted should be assured to achieve energy sustainability

Advances in hydrogen storage materials: harnessing innovative technology, from machine learning to computational chemistry, for energy storage solutions

The demand for clean and sustainable energy solutions is escalating as the global population grows and economies develop. Fossil fuels, which currently dominate the energy sector, contribute to greenhouse gas emissions and environmental degradation. In response to these challenges, hydrogen storage technologies have emerged as a promising avenue for achieving energy sustainability. This review provides an overview of recent advancements in hydrogen storage materials and technologies, emphasizing the importance of efficient storage for maximizing hydrogen's potential. The review highlights physical storage methods such as compressed hydrogen (reaching pressures of up to 70 MPa) and material-based approaches utilizing metal hydrides and carbon-containing substances. It also explores design considerations, computational chemistry, high-throughput screening, and machine-learning techniques employed in developing efficient hydrogen storage materials. This comprehensive analysis showcases the potential of hydrogen storage in addressing energy demands, reducing greenhouse gas emissions, and driving clean energy innovation.

Evaluation and performance comparison of different models for global solar radiation forecasting: a case study on five cities

AbstractRecently, solar energy has emerged as the most promising renewable energy source to meet the world’s energy demands. However, to harness the potential of solar energy, accurate data on solar radiation are crucial. It is considered the first step in assessing solar resources for various applications and achieving energy sustainability goals. Due to the unavailability of solar radiation measurements in many parts of the world, several models have been developed to predict global solar radiation (GSR) at these locations. Thus, this study aims to evaluate the proficiency of several GSR models at five new locations and determine the most suitable one for GSR prediction. The study has further developed solar radiation models for these new locations, as well as general ones for the entire region, which does not have any GSR models despite the existence of many planned solar energy facilities in this area. Additionally, the study investigates the effect of changing the length of the validation dataset on models’ performance and accuracy, as well as assesses the introduced models’ generalization capability. To achieve these objectives, the observed data of GSR for approximately 37 years at studied locations are used to develop and validate the proposed models. The study’s findings reveal that Model 1 provides the best performance at all locations, with accuracy, coefficient of determination ($$R^{2}$$ R 2 ), ranging from 95 to 98%, except for the coastal location, where it is from 91 to 95%. The remaining performance indicators of the best models, such as RMSE, MABE, MAPE, and $$r$$ r , are good, and their values range from 0.7863 to 1.9097 (MJ m−2 day−1), from 0.6430 to 1.7060 (MJ m−2 day−1), from 3.4319 to 10.0890 (%), and from 0.9914 to 0.9981, respectively. The length of the validation dataset has a slight effect on the models’ performance, ranging from about 1% to 2%. Therefore, Model 1 is the recommended solar radiation model, which can provide precise and rapid estimates of global solar radiation. This approach could be used in the design and performance evaluation of many solar applications. The primary benefit of this approach in the current investigation is that temperature data are continuously and effortlessly recorded for various purposes.

Cell-Free Networking for Integrated Data and Energy Transfer: Digital Twin Based Double Parameterized DQN for Energy Sustainability

Cell-free networking enables full cooperation among distributed access points (APs). This paper focuses on reducing the long-term energy consumption of a cell-free network in the downlink integrated data and energy transfer (IDET) for achieving energy sustainability. The resultant design includes both the AP classification on a large time-scale and the beamforming of the APs on a small time-scale in order to simultaneously satisfy the IDET requirements of data users and energy users. For dealing with binary integer actions (AP classification) and continuous actions (beamforming) together, we innovatively propose a stable double parameterized deep-Q-network (DP-DQN), which can be enhanced by a digital twin (DT) running in the intelligent core processor (ICP) so as to achieve faster and more stable convergence. Therefore, the cell-free network may avoid suffering from performance fluctuation during the training process. The simulation results demonstrate that our DP-DQN exceeds in convergence compared to other benchmarks while guaranteeing an optimal solution.

Metal-Organic Framework Derived Bi-O-Sn/C Nanostructure: Tailoring the Adsorption Site of Dominant Intermediate for Highly Efficient CO2 Electroreduction to Formate.

Electrochemical CO2 reduction into high-value-added formic acid/formate is an attractive strategy to mitigate global warming and achieve energy sustainability. However, the adsorption energy of most catalysts for the key intermediate *OCHO is usually weak, and how to rationally optimize the adsorption of *OCHO is challenging. Here, an effective Bi-Sn bimetallic electrocatalyst (Bi1 -O-Sn1 @C) where a Bi-O-Sn bridge-type nanostructure is constructed with O as an electron bridge is reported. The electronic structure of Sn is precisely tuned by electron transfer from Bi to Sn through O bridge, resulting in the optimal adsorption energy of intermediate *OCHO on the surface of Sn and the enhanced activity for formate production. Thus, the Bi1 -O-Sn1 @C exhibits an excellent Faradaic efficiency (FE) of 97.7% at -1.1V (vs RHE) for CO2 reduction to formate (HCOO- ) and a high current density of 310mAcm-2 at -1.5V, which is one of the best results catalyzed by Bi- and Sn-based catalysts reported previously. Impressively, the FE exceeds 93% at a wide potential range from -0.9 to -1.4V. In-situ ATR-FTIR, in-situ Raman, and DFT calculations confirm the unique role of the bridge-type structure of Bi-O-Sn in highly efficient electrocatalytic reduction of CO2 into formate.

Energy sustainability blueprint: A critical analysis of macro and micro influential factors in Pakistan

Achieving energy sustainability requires conceptualised strategies that identify governing aspects and influential factors. Energy sustainability has been attempted by focusing mainly on macro aspects of the energy infrastructure (EI), while its conjunction with the micro-environment has been overlooked. Additionally, the previous literature mostly focused on other issues and ignored assessing energy sustainability considering macro and micro aspects of energy in the context of developing countries like Pakistan. Therefore, in this study, a comprehensive decision-making framework (DMF) was constructed by adopting a multiple-case study approach, which was a novel contribution to the literature. The DMF constituted influential factors (IFs) discovered by focusing on the macro and micro aspects of the entire EI and analysed by soliciting the experts’ opinions. To establish the presence of discovered IFs in the DMF, the IFs were first tested and validated by calculating the content validity index. Second, the sustainability aspects and factors were ranked based on their optimal weights calculated using the best-worst method (BWM) and compared using a statistical mean scoring technique. The significance index of IFs was then calculated to determine their essential potential for the DMF. Referring to the quantitative assessment of IFs, the problem and objectives trees encompassing strengths, weaknesses, opportunities, and threats to the EI of Pakistan were established. Findings revealed that micro aspects, such as ‘energy system flexibility’, ‘share of renewables in the energy mix’, and ‘durability of renewables’ were more critical than macro aspects. The study findings will aid policymakers, stakeholders, and government agencies from developing countries like Pakistan to get better insight into the impact of each macro and micro factor for developing sustainable energy infrastructure.

Review of the Recent Developments About the Hybrid Propelled Aircraft

In the past decades, the exponential rise in fossil fuel consumption has led to a pressing need for sustainable energy solutions. This surge in fossil fuel use has not only caused severe environmental repercussions but has also raised questions about our global dependence on such non-renewable resources. Addressing these detrimental effects, NASA has urged the aeronautic industry to reduce aircraft fuel burn by a substantial 70% before 2025. As a result of comprehensive government and industry studies, electric aircraft propulsion has emerged as a pivotal focus of research. This encompasses various architectures, such as full-electric, hybrid electric, and turbo-electric systems. The aim is to significantly diminish the environmental impact of aviation and make it more sustainable for the future of passenger flight. This paper provides an overview of the latest state-of-the-art innovations in propulsion systems. It delves into the operational principles, technological requirements, ongoing research, and development efforts pertaining to all components essential for effecting this transformation in aviation technology. Additionally, the document will showcase existing commercial products, prototypes, and demonstrators to offer a comprehensive picture of the current scenario. Overall, this research is a vital step toward achieving energy sustainability and reducing the environmental footprint of the aviation industry. By exploring and advancing electric aircraft propulsion, humanity can move closer to a cleaner, greener future for air travel.

Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models

Rooftop photovoltaic panels (RPVs) are being increasingly used in urban areas as a promising means of achieving energy sustainability. Determining proper layouts of RPVs that make the best use of rooftop areas is of importance as they have a considerable impact on the RPVs performance in efficiently producing energy. In this study, a new spatial methodology for automatically determining the proper layouts of RPVs is proposed. It aims to both extract planar rooftop segments and identify feasible layouts with the highest number of RPVs in highly irradiated areas. It leverages digital surface models (DSMs) to consider roof shapes and occlusions in placing RPVs. The innovations of the work are twofold: (a) a new method for plane segmentation, and (b) a new method for optimally placing RPVs based on metaheuristic optimization, which best utilizes the limited rooftop areas. The proposed methodology is evaluated on two test sites that differ in urban morphology, building size, and spatial resolution. The results show that the plane segmentation method can accurately extract planar segments, achieving 88.7% and 99.5% precision in the test sites. In addition, the results indicate that complex rooftops are adequately handled for placing RPVs, and overestimation of solar energy potential is avoided if detailed analysis based on panel placement is employed.

New liquid fraction measurement methodology for phase change material analysis based on X-ray computed tomography

To tackle climate change, it is of fundamental importance to develop more efficient systems to convert and manage energy. Latent Thermal Energy Storage (LTES) systems, which are based on Phase Change Materials (PCMs), present many interesting features that can lead us to achieve energy sustainability. In fact, these systems can be employed in many applications (e.g., HVAC, buildings thermal management, thermal energy recovery). To use PCMs, it is crucial to understand and monitor their phase-change behaviour. However, the evaluation of two-phase systems is still difficult because of the intrinsic complexity and transient behaviour.In the present study, a new methodology to measure liquid fraction is proposed. X-ray Computed Tomography (XCT) is used to follow the solidification process of eicosane. XCT and the acquisition settings were optimised to ensure maximum contrast between the phases. Then, the solidification process of eicosane was dynamically studied and the volumetric liquid fraction was extracted. Finally, via the Ansys Fluent software, a CFD model, based on the enthalpy-porosity method, was implemented to simulate the solidification of eicosane. The numerical results were compared against the experimental data, showing excellent agreement. This novel experimental methodology opens new possibilities to characterise and understand the solid-liquid phase transition process of PCMs, by directly observing and quantifying the solid/liquid phase evolution in time, the volumetric shrinkage, the presence of voids and the different phases that might occur during the phase-change process.

A multi-stage optimisation-based decision-making framework for sustainable hybrid energy system in the residential sector

Integrating renewables into existing energy infrastructure to construct hybrid energy systems (HES) plays a vital role for advancing energy sustainability. While various approaches, such as energy systems analysis and linear or non-linear optimisation, have been employed to achieve energy sustainability mainly at the national or city level, there has been a lack of focus on achieving energy sustainability in the residential sector through a holistic optimal decision-making approach for efficient HES design. This study focuses on developing a multi-stage optimisation-based decision-making framework that models, quantifies, and optimises the performance indicators of HES, allowing for an assessment of the trade-off between benefits and systems costs under various design scenarios. The initial step involves designing the HES model and constructing scenarios that cater to the electrification requirements of water, energy, and food elements in the residential sector by using a systematic thinking approach. Then, a preliminary evaluation of the modelled scenarios is conducted to assess energy sustainability in terms of technical and economic aspects. Afterwards, an optimal decision-making setup is established by integrating a multi-objective HES model into the NSGA-II algorithm, which approximates the Pareto optimal solutions. These solutions are then ranked by using a multi-criteria decision-making method. According to the findings, the Quetta region in Pakistan contains the best optimal solution. The results underscore the utility of the developed framework in facilitating the optimal design of renewables-integrated HES for the residential sector. Furthermore, intergovernmental organizations can leverage this framework to formulate effective policies aimed at encouraging residents to invest in HES installation.

Green Building Best Practices in Achieving Energy and Environmental Sustainability

In the construction and building industry, sustainable development is becoming a powerful force for economic, social, and environmental gains with fewer negative consequences for the environment. It is essential to establish green and sustainable practices in the building and construction industry in order to improve energy efficiency, particularly by utilising the newest green technologies. As a result, the study’s objectives are to first investigate the most relevant practices to be used for green building employment; second, evaluate the benefits produced by the execution of green building; and third, analyse the best practices of green building characteristics. The findings of this study showed that green buildings developed using energy-efficient systems and implementing sustainable practices can reduce energy consumption, as well as lower the cost of operating and maintaining these buildings in the long term. Meanwhile, the government’s role is essential to attracting more participants in implementing sustainable practices in the construction and building sector, especially through more stringent regulations and appealing incentives.

One-Step Electrosynthesis of Bifunctional NiCu Nanosheets on Iron Foam for Remarkably Enhanced Alkaline Water Splitting

Electrocatalytic water splitting for hydrogen production driven by renewable electricity offers a promising way of achieving energy sustainability, but the design of highly efficient and cost-effective electrocatalysts is regarded as a bottleneck. Herein, a bifunctional microflowers NiCu is successfully deposited on an iron foam (IF) electrode via one-step electrolysis of spend cupronickel (SCN). Unexpectedly, the designed IF-supported NiCu (NiCu/IF) electrocatalysts exhibit excellent catalytic performance for oxygen evolution reactions (OER) and hydrogen evolution reactions (HER) in 1 M KOH. Only 98 and 267 mV are required to drive a current density of 10 mA cm−2 for HER and OER, respectively. Importantly, the self-supported NiCu/IF electrode requires a low cell voltage of 1.57 V to achieve 10 mA cm−2 of alkaline overall water splitting with extremely high stability. With the introduction of a glycerol oxidation reaction (GOR), the HER performance is further remarkably enhanced with an extremely low cell voltage of 1.29 V at 10 mA cem−2, highlighting an attractive energy-efficient hydrogen production coupled with biomass conversion process. This study reports a novel synthesis strategy for low-cost and high-performance Ni-based nanostructure catalysts using SCN as precursors, which is of vital significance for green hydrogen production and waste recycling.