Clean Energy Future Research Articles

Current Status and Development Trend of Research on Polymer-Based Kinetic Inhibitors for Natural Gas Hydrates.

As the understanding of natural gas hydrates as a vast potential resource deepens, their importance as a future clean energy source becomes increasingly evident. However, natural gas hydrates trend towards secondary generation during extraction and transportation, leading to safety issues such as pipeline blockages. Consequently, developing new and efficient natural gas hydrate inhibitors has become a focal point in hydrate research. Kinetic hydrate inhibitors (KHIs) offer an effective solution by disrupting the nucleation and growth processes of hydrates without altering their thermodynamic equilibrium conditions. This paper systematically reviews the latest research progress and development trends in KHIs for natural gas hydrates, covering their development history, classification, and inhibition mechanisms. It particularly focuses on the chemical properties, inhibition effects, and mechanisms of polymer inhibitors such as polyvinylpyrrolidone (PVP) and polyvinylcaprolactam (PVCap). Studies indicate that these polymer inhibitors provide an economical and efficient solution due to their low dosage and environmental friendliness. Additionally, this paper explores the environmental impact and biodegradability of these inhibitors, offering guidance for future research, including the development, optimization, and environmental assessment of new inhibitors. Through a comprehensive analysis of existing research, this work aims to provide a theoretical foundation and technical reference for the commercial development of natural gas hydrates, promoting their safe and efficient use as a clean energy resource.

Effect of solar panel orientation and EV charging profile on grid design

The implementation of solar coupled with daytime electric vehicle (EV) charging, aligns seamlessly with the broader goal of transitioning to a decarbonized grid and clean energy future. This paper explores how fixed-tilt solar arrays coupled with daytime EV charging would affect a future renewable-energy-driven grid in California. We use capacity-expansion modeling to identify the lowest-cost grid design for 40 scenarios that compare two solar panel mounting configurations (east–west versus south-facing), two EV charging profiles, five tilt angles ranging from 15°to 35°, and two assumptions about a long-duration energy storage (LDES) candidate resource. We then evaluate and discuss the mix of generators selected by the model for the various scenarios, the associated curtailment, and the implications about the best approaches for adding fixed-tilt solar arrays as part of transitioning to a new energy system. Although the east–west-facing solar orientation is expected to reduce the need for diurnal storage by being able to charge EVs early and late in the day, it appears that the better matching between seasonal supply and demand for the south-facing orientation is more important.

Agronomic performance and technological quality of sugarcane submitted to different poultry litter dosages

Sugarcane is a central crop for sugar and ethanol production. Investing in sustainable practices can enhance productivity, technological quality, mitigate impacts, and contribute to a cleaner energy future. Among the factors that help increase the productivity of sugarcane, the physical, chemical and biological parameters of the soil are amongst the most important. The use of poultry litter has been an important alternative for soil improvement, as it acts as a soil conditioner. Therefore, this work aimed to verify the best doses of poultry litter for the vegetative, reproductive and technological components of sugarcane. The experiment was carried out at Usina Denusa Destilaria Nova União S/A in the municipality of Jandaia, GO. The experimental design used was a complete randomized block design with four replications: 5 × 4, totaling 20 experimental units. The evaluated factor consisted of four doses of poultry litter plus the control (0 (control), 2, 4, 6 and 8 t ha−1). In this study, were evaluated the number of tillers, lower stem diameter, average stem diameter, upper stem diameter, plant height, stem weight and productivity. The technological variables of total recoverable sugar, recoverable sugar, Brix, fiber, purity and percentage of oligosaccharides were also evaluated. It was observed, within the conditions of this experiment, that the insertion of poultry litter did not interfere significantly in most biometric, productive and technological variables of the sugarcane. But it can also be inferred that there was a statistical trend toward better results when the sugarcane was cultivated with 4 t ha-1 of poultry litter.

Development of thermal insulation material using coconut and kenaf fiber for heat recovery enhancement

Abstract In line with the world’s Sustainable Development Goals (SDG), Malaysia aims to have a clean future energy. The main problem facing the energy revolution is the low conversion efficiency of low-grade heat to useful energy. During the process, a significant fraction of thermal energy is generally lost to the environment as waste heat. Waste heat accounts for 20-50% of industrial energy use, with Southeast Asia processing 40 million tonnes of oil equivalent. Heat losses especially in engines can reduce efficiency, leading to extensive studies to reduce heat loss and improve thermal performance. Heat recovery systems are being studied to recover lower-grade energy, but to the extent of the authors’ knowledge, the majority of them are not economically effective for low temperature waste heat. Therefore, the objectives of this study are to develop low thermal conductivity material for thermal insulators based on natural fibre and investigate their impact on thermal performance. The natural fibre-based materials that were chosen in this study are coconut husk and kenaf fibre due to their supposedly low thermal conductivity level and availability in the Southeast Asia region. The specimens were prepared using two different methods; the first two specimens using needle felting method and for the other two specimens epoxy resin was reinforced to bind the material together to become a polymer. The results revealed that coconut husk fibre reinforced with resin has the lowest thermal conductivity value among the four specimens with 0.0410 W/m.K and the lowest overall heat transfer coefficient of 2.73 W/m2.K, making it a possible thermal insulator to be proposed for heat recovery.

Contribution of renewable energy technologies in combating phenomenon of global warming and minimizing GHG emissions

The energy derived from fossil fuels significantly contributes to global warming (GW), accounting for over 75% of global greenhouse gas emissions and approximately 90% of all carbon dioxide emissions. It is crucial to rely on alternative energy from renewable energy (RE) to mitigate carbon emissions in the energy sector. Renewable energy sources have the potential to eliminate carbon from 90% of electricity generation by 2050, greatly reducing carbon emissions and helping alleviate the impacts of GW. By emphasizing the concept of zero emissions, the future of renewable energy becomes promising, with the possibility of replacing fossil fuels and limiting global temperature rise to 1.5 ℃ by 2050. In this article, renewable energy technologies and their role in various areas to combat GW are explored, examining trends and successes in supporting renewable energy policies and exploring available options to mitigate the effects of climate change and achieve a clean energy future. Moreover, RE offers a clean and sustainable alternative to fossil fuels, reducing reliance on them and minimizing greenhouse gas emissions. This paper also highlights the efforts of leading countries, including China, the United States, India, and Germany, in developing and utilizing renewable energy. These countries’ renewable energy strategies reflect their commitment to combat global warming and reduce harmful emissions for the well-being of present and future generations.

Progress and challenges of latent thermal energy storage through external field-dependent heat transfer enhancement methods

The development of Energy Storage technologies is critical to achieving a cleaner energy future. As one of the most widely used energy storage technologies, Latent Thermal Energy Storage (LTES) still suffers from poor charging and discharging performance subjected to the low thermal conductivity of Phase Change Materials (PCMs) and inefficient heat transfer process. Heat transfer enhancement techniques, such as using fins and adding highly conductive materials, have been widely developed and optimized to overcome these challenges. Recently, additional novel methods integrating adjustable external fields such as gravity, magnetic field, and electric field have been proposed to enhance the heat transfer performance of LTES, due to their advantages including easy adjustment of the field parameters according to the evolution of the heat storage process. Firstly, this work briefly summarizes the progress of conventional heat transfer enhancement methods. Secondly, the advancement of heat transfer enhancement by integrating adjustable external field effects has been analyzed and discussed. Finally, the potential of external fields to improve the heat storage performance of LTES under fluctuating thermal sources is discussed considering the wide existence of fluctuating energy supply and load in real applications. The main contributions from this review are: (a) The emerging heat transfer enhancement methods for LTES are comprehensively summarized and discussed for the first time; (b) The potential of different heat transfer enhancement techniques is demonstrated to overcome the poor heat storage performance under fluctuating thermal sources when considering real applications of LTES.

A machine learning ensemble approach for predicting solar-sensitive hybrid photocatalysts on hydrogen evolution

Hydrogen, as the lightest and most abundant element in the universe, has emerged as a pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such as high energy density and zero emissions upon combustion, make it a promising candidate for addressing the pressing challenges of climate change and transitioning towards a clean and renewable energy future. In an effort to improve efficiency and reduce experimental costs, we adopted machine learning techniques in this study. Our focus turned to predictive analyses of hydrogen evolution values using three photocatalysts, namely, graphene-supported LaFeO3 (GLFO), graphene-supported LaRuO3 (GLRO), and graphene-supported BiFeO3 (GBFO), examining their correlation with varying levels of pH, catalyst amount, and H2O2 concentration. To achieve this, a diverse range of machine learning models are used, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), XGBoost, Gradient Boosting, and AdaBoost—each bringing its strengths to the predictive modeling arena. An important step involved combining the most effective models—Random Forests, Gradient Boosting, and XGBoost—into an ensemble model. This collaborative approach aimed to leverage their collective strengths and improve overall predictability. The ensemble model emerged as a powerful tool for understanding photocatalytic hydrogen evolution. Standard metrics were employed to assess the performance of our ensemble prediction model, encompassing R squared, Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). The yielded results showcase exceptional accuracy, with R squared values of 96.9%, 99.3%, and 98% for GLFO, GBFO, and GLRO, respectively. Moreover, our model demonstrates minimal error rates across all metrics, underscoring its robust predictive capabilities and highlighting its efficacy in accurately forecasting the intricate relationships between GLFO, GBFO, and GLRO values and their influencing factors.

LoadNet: enhancing energy storage system integration in power system operation using temporal convolutional and recurrent models with self-attention

Introduction: In the context of the evolving energy landscape, the efficient integration of energy storage systems (ESS) has become essential for optimizing power system operation and accommodating renewable energy sources.Methods: This study introduces LoadNet, an innovative approach that combines the fusion of Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) models, along with a self-attention mechanism, to address the challenges associated with ESS integration in power system operation. LoadNet aims to enhance the management and utilization of ESS by effectively capturing the complex temporal dependencies present in time-series data. The fusion architecture of TCN-GRU in LoadNet enables the modeling of both short-term and long-term dependencies, allowing for accurate representation of dynamic power system behaviors. Additionally, the incorporation of a self-attention mechanism enables LoadNet to focus on relevant information, facilitating informed decision-making for optimal ESS operation. To assess the efficacy of LoadNet, comprehensive experiments were conducted using real-world power system datasets.Results and Discussion: The results demonstrate that LoadNet significantly improves the efficiency and reliability of power system operation with ESS. By effectively managing the integration of ESS, LoadNet enhances grid stability and reliability, while promoting the seamless integration of renewable energy sources. This contributes to the development of a more sustainable and resilient power system. The proposed LoadNet model represents a significant advancement in power system management. Its ability to optimize power system operation by integrating ESS using the TCN-GRU fusion and self-attention mechanism holds great promise for future power system planning and operation. Ultimately, LoadNet can pave the way for a more sustainable and efficient power grid, supporting the transition to a clean and renewable energy future.

Balancing hope and hype on hydrogen’s role in the Philippine energy transition

Hydrogen (H2) presents a unique opportunity for the Philippines’ energy landscape. Using hydrogen as an ‘energy vector’ for industrial, power, and transportation applications represents a promising and sustainable solution in its ongoing efforts to address climate change and transition towards a cleaner energy future. However, unlocking this potential requires first addressing regulatory and policy gaps. This challenge has many different facets, such as the need for regulations to support the hydrogen infrastructure development, the establishment of clear standards for safe hydrogen production, storage and handling, streamlining of permit and license applications, monitoring of solar or wind power plants coupled with electrolysis process, provision of more substantial support for research and innovation, and promotion of hydrogen-based products.This policy brief describes the current landscape and identifies the regulatory and policy gaps that policymakers must fill while highlighting the Philippines' potential for hydrogen energy and energy storage in the short and long run. It is crucial to have a complete policy framework that addresses regulatory clarity, financial incentives for infrastructure development, technical capacity, support for R&D, and strategic export planning. The Philippines can utilize its renewable resources, improve energy security, and cut emissions by filling these gaps.

Energy saving and emission reduction technologies integrating energy power and mechanical engineering

This paper discusses the importance and application prospect of energy-saving and emission-reduction technology combining energy, power and mechanical engineering in the current energy and environment fields. Firstly, the concept of integration of energy power and mechanical engineering and its significance in energy saving and emission reduction are introduced, and the important role of this technology in realizing sustainable development and meeting the challenge of climate change is emphatically expounded. Subsequently, the application practice of this technology in industrial production, construction, transportation and other fields is analyzed, and its remarkable effects in energy saving and emission reduction are summarized. This paper further discusses the important role of technological innovation and policy support in promoting the development of this technology, and emphasizes the importance of interdisciplinary cooperation and exchange in the process of technology popularization and application. Finally, the future research direction and development trend are prospected, and all parties are called upon to make joint efforts to promote the energy-saving and emission-reduction technology integrating energy, power and mechanical engineering to be more widely applied and popularized around the world, so as to contribute to building a clean, low-carbon and sustainable energy future.

Sustainability evaluation of C3MR natural gas liquefaction process: Integrating life cycle analysis with Energy, Exergy, and economic aspects

In a transition towards a clean energy future, natural gas serves as an interim fuel due to its lower emissions whereas the C3MR (propane pre-cooled mixed refrigerant process) is widely recognized for high efficiency and commercial scale application converting natural gas to LNG. Previously, numerous studies have been conducted to optimize the energy efficiency and performance of C3MR process but very little contribution has been made towards its sustainability analysis. To address this, a life cycle analysis approach is established to evaluate the carbon footprint of C3MR process. In order to showcase its link with energy consumption and put forward the groundwork of analyses, the research focuses on using simulation – assisted optimization to reduce the specific energy consumption (SEC) of C3MR process by optimizing design variables. The study highlights the use of mixed refrigerant (MR) as a process variable and validates that its optimal implementation has decreased SEC to 0.2195 kWh/kg LNG, while achieving a minimum inlet temperature approach (MITA) of main cryogenic heat exchanger (MCHX), less than 3 °C. The knowledge − based optimization approach applied in this research, developed comparative case studies on which multiple analyses are performed to verify scientific findings. Energy and exergy analyses are conducted to determine thermal efficiency of the process where the optimized case exhibits a reduced difference in its composite curves and an 8.65 % improvement in exergetic performance compared to the base case. The economic indicators assessment reveals that optimized case demonstrates lower capital and operating costs, establishing economic viability. Furthermore, the energy consumption parameters are utilized for evaluation of ecological impact ofLNGsupply chain through life cycle assessment (LCA) which reflects reduced greenhouse gas (GHG) emissions for optimized case. Hence, the current study fills existing research knowledge gaps in terms of providing a comprehensive process system engineering by evaluating energy synergistic point, thermodynamic irreversibility, process viability and sustainability using life cycle assessment.

Author Correction: Africa needs context-relevant evidence to shape its clean energy future

Author Correction: Africa needs context-relevant evidence to shape its clean energy future

Electric Vehicle Supply Chain Risk Assessment Based on Combined Weights and an Improved Matter-Element Extension Model: The Chinese Case

In order to meet energy and environmental challenges, many countries will implement the replacement of fuel vehicles for the future clean energy transition; so, the number of electric vehicles (EVs) operating in cities will grow significantly. It is crucial to assess the risks of the electric vehicle supply chain (EVSC) and prevent them. Based on this, this paper proposes an EVSC risk research framework with combined weights and an improved matter-element extension model: (i) Firstly, the EVSC evaluation index system is constructed from the six stages of supply chain planning, sales, procurement, manufacturing, distribution, after-sales, and external risks. (ii) The subjective and objective weights are calculated by the decision laboratory method and entropy weight method, respectively, and then the minimum deviation method is used for a combined design to overcome the defects of a single method. (iii) An improved matter-element extension model (MEEM) is constructed by introducing asymmetric proximity degree and risk bias. (iv) The model is applied to a case study and its feasibility and superiority are verified through sensitivity analysis and comparative analysis. The final results show that the method and framework proposed in this paper are in line with EVSC risk assessment standards and superior to other models, which can help EVSC managers to identify potential risks, formulate appropriate risk prevention measures, promote the stable development of electric vehicles, and provide a reference for the development of energy and environment.

Recovery of rare earth elements from low-grade coal fly ash using a recyclable protein biosorbent.

Rare earth elements (REEs), including those in the lanthanide series, are crucial components essential for clean energy transitions, but they originate from geographically limited regions. Exploiting new and diverse supply sources is vital to facilitating a clean energy future. Hence, we explored the recovery of REEs from coal fly ash (FA), a complex, low-grade industrial feedstock that is currently underutilized (leachate concentrations of REEs in FA are < 0.003mol%). Herein, we demonstrated the thermo-responsive genetically encoded REE-selective elastin-like polypeptides (RELPs) as a recyclable bioengineered protein adsorbent for the selective retrieval of REEs from coal fly ash over multiple cycles. The results showed that RELPs could be efficiently separated using temperature cycling and reused with high stability, as they retained ∼95% of their initial REE binding capacity even after four cycles. Moreover, RELPs selectively recovered high-purity REEs from the simulated solution containing one representative REE in the range of 0.0001-0.005mol%, resulting in up to a 100,000-fold increase in REE purity. This study offers a sustainable approach to diversifying REE supplies by recovering REEs from low-grade coal fly ash in industrial wastes and provides a scientific basis for the extraction of high-purity REEs for industrial purposes.

Clean energy for a sustainable future: Analysis of a PV system and LED bulbs in a hotel

Scholars are increasingly prioritising sustainability as the driving force behind their research efforts, and many businesses are placing the customer at the centre of their agendas. Hospitality facilities, such as hotels, are also making concerted efforts to mitigate climate change. The present study proposed a sustainability analysis of the installation of a photovoltaic (PV) system and the replacement of conventional lighting with light emitting diode (LED) bulbs in a hotel, considering economic, environmental and social sustainability dimensions.The results showed that NPV varied between 967 and 3624 €/kW for the PV system, with a 100 % probability of achieving a positive NPV in a high market scenario and a 79–84 % probability of the same in a low market scenario. Concerning energy efficiency, the adoption of LED bulbs determined a NPV in the range of 105–216 €/bulb. These figures were highly dependent on the percentage of self-consumed energy and the purchase price of electricity. Environmental analyses indicated that the installation of a PV system could lead to an emissions reduction of 422 gCO2eq/kWh, translating to 61 tCO2eq/year. In addition, social analyses underscored the significance of renewable installations and energy-efficiency interventions to support the ecological transition. However, consumer choices within hotels did not consistently align with sustainable models. Notably, a green premium of 13.2 €/day was recognised for hotels using renewable systems, and 8.3 €/day for those using smart lighting. The results advocate for a pragmatic sustainability model that sees green investments enhancing a hotel's sustainability. However, a shift in consumer attitudes is necessary to fully realise this potential.

Leadership and management in high-growth environments: effective strategies for the clean energy sector

The clean energy sector stands at the forefront of global efforts to combat climate change and transition towards sustainable energy sources. In this rapidly evolving landscape, effective leadership and management are crucial for driving innovation, managing growth, and navigating complex challenges. This abstract presents an overview of key strategies for leadership and management tailored to the unique demands of high-growth environments within the clean energy sector. Firstly, visionary leadership is essential for setting ambitious goals and inspiring teams to pursue innovation and excellence. Leaders must possess a deep understanding of market trends, technological advancements, and regulatory landscapes to effectively steer their organizations towards success. Additionally, adaptive leadership skills are necessary to respond swiftly to changing market dynamics and capitalize on emerging opportunities. Strategic management plays a critical role in ensuring the efficient allocation of resources, optimizing operations, and scaling up business operations sustainably. Talent acquisition and retention are key priorities, requiring a focus on attracting diverse talent and fostering a culture of continuous learning and development. Furthermore, building a culture of innovation and sustainability is essential for driving long-term success in the clean energy sector. Companies must encourage entrepreneurial thinking, foster collaboration across disciplines, and prioritize environmental stewardship in their operations. Despite the immense potential of the clean energy sector, companies face regulatory and policy hurdles that require proactive engagement and advocacy efforts. Navigating government regulations, advocating for pro-renewable policies, and engaging with stakeholders are critical components of effective leadership and management in this space. Through case studies and best practices, this abstract highlights successful leadership and management models, lessons learned from industry leaders, and emerging trends shaping the future of the clean energy sector. By embracing these strategies, leaders can position their organizations for sustainable growth and contribute to the global transition towards a clean energy future. Keywords: Leadership, Management, High-Growth Environments, Clean Energy Sector.

Effect of particle size distribution variability on the permeability of hydrate-bearing sediments: A CFD study

Natural gas hydrates (NGH) are considered as a future clean energy in the era of carbon neutrality. The seepage behaviour of hydrate-bearing sediment (HBS) and its controlling factors are significant for developing effective production strategies. In this study, we aim to elucidate how the heterogeneous spatial distribution of clayey-silty sediment particles, particularly the non-uniform particle size distribution (PSD) affects the permeability of HBS. An algorithm was developed to generate the heterogeneous spatial distribution of sediment particles based on the PSD of hydrate-bearing cores extracted from Japan Nankai Trough (D50 = 122 μm). A series simulation of fluid flow in porous media based on CFD was conducted for the HBS with varying hydrate saturations (SH). The watershed segmentation algorithm was employed for the identification of pore structure, including pore space and pore throat with a detailed analysis on the pore structure evolution with SH. Host sediments with higher uniformity result in initial high permeability but the permeability reduction with increasing SH is more significant compared with that of lower uniformity. Pore throat width reduced to less than 5 μm with SH above 50% compared with its original width of ∼30 μm. Tortuosity exhibits a linear increase with SH, while permeability decreases exponentially with increasing tortuosity. We propose an improved permeability model (KCpro) based on the classical Kozeny-Carman model accounting for the change in specific surface area for non-uniform PSD in HBS with good agreement. This study confirmed the applicability of CFD modelling as a promising tool to study the seepage behaviour of HBS complementary to classical permeability experimental tests. Results of this study provide fundamental understanding on how permeability evolves in HBS with significant PSD variations in natural gas hydrate reservoirs in nature.

Challenges creating monarch butterfly management strategies for electric power companies in the United States

Returning monarch butterflies (Danaus plexippus) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.

Navigating illegal land use in the quest for a just energy transition

Illegal land use inhibits available land for renewable resource development and hinders a just energy transition, posing a significant challenge to sustainability. This article utilizes the TOE (Technology, Organization, Environment) framework to examine the impact of under-regulation on illegal land use in China. By employing a multidisciplinary approach, the study navigates the complexities of unscrupulous land practices and uncovers their socio-economic and environmental implications. Findings from panel data analysis covering the period of 1999 to 2009 reveal several key insights. Firstly, inadequate technology hampers regulators' ability to detect illegal activities, leading to an increase in the area of illegal land use. Secondly, a high turnover rate of regulatory officers is linked to lower levels of punishment for illegal land use, thereby contributing to an expansion of illegal land use. Thirdly, a permissive government-business environment hinders the effective enforcement of the land approval system, thereby restraining the prevention of illegal land use. Through case studies and policy analyses, the research aims to reveal the challenges and obstacles arising from illegal land use in transitioning to a cleaner energy future. The findings contribute to a nuanced understanding of the obstacles posed by illegal land use, offering insights to policymakers, industry stakeholders, and advocates in navigating towards a more equitable and sustainable energy landscape.

Recent Developments in Two-Dimensional Carbon-Based Nanomaterials for Electrochemical Water Oxidation: A Mini Review

Water splitting is considered a renewable and eco−friendly technique for future clean energy requirements to realize green hydrogen production, which is, to a large extent, hindered by the oxygen evolution reaction (OER) process. In recent years, two−dimensional (2D) carbon−based electrocatalysts have drawn sustained attention owing to their good electrical conductivity, unique physicochemical properties, and excellent electrocatalytic performance. Particularly, it is easy for 2D carbon−based materials to form nanocomposites, which further provides an effective strategy for electrocatalytic applications. In this review, we discuss recent advances in synthetic methods, structure−property relationships, and a basic understanding of electrocatalytic mechanisms of 2D carbon−based electrocatalysts for water oxidation. In detail, precious, non−precious metal−doped, and non−metallic 2D carbon−based electrocatalysts, as well as 2D carbon−based confined electrocatalysts, are introduced to conduct OER. Finally, current challenges, opportunities, and perspectives for further research directions of 2D carbon−based nanomaterials are outlined. This review can provide significant comprehension of high−performance 2D carbon−based electrocatalysts for water-splitting applications.