Energy-related Challenges Research Articles

High-Precision Numerical Investigation of a VAWT Starting Process

For both conventional and renewable energy conversion processes, computational fluid dynamics (CFD) has been used to address more energy-related challenges in recent decades. Using CFD to investigate vertical-axis wind turbines has become more common in recent years. The main goals of this application have been to more accurately predict the turbine’s performance and to comprehend the complicated nature of the complex turbulent flow. The vertical-axis wind turbine (VAWT) simulation for energy-generating applications has several intricate components. One of them is the study of the chaotic flow that occurs during the first stages of the starting process, and which greatly influences overall effectiveness. In this article, the performance of the wind turbine was increased using a passive flow control approach. The numerical research was carried out using Large Eddy Simulation for four alternative tip speed ratios in both cases, the classic and the optimized case, equipped with a vortex trap on the extrados of the blades. The power and torque coefficient variations, as well as the velocity magnitude contours, show that the starting process may begin with a significant improvement in efficiency when flow control is used.

Unraveling the phase transition and electrochemical application of MoSe2 material for energy conversion and storage devices

Layered transition metal selenides have garnered widespread attention as the potential non-noble metal-based materials to cater to diverse energy conversion and storage aspects. Therefore, we have implemented an integrated experimental and theoretical methodology to explore the application of molybdenum diselenide (MoSe2) for HER, OER, and supercapacitor avenues via employing nanostructural and surface engineering performance enhancement strategy. Herein, we have demonstrated the successful execution of a laboratory-scale electrolyzer for water splitting with a low cell voltage of 1.54 V at 10 mA cm−2 and 1.74 V at 50 mA cm−2 current rate for 50 h. This was accomplished using synthesized exfoliated conductive carbon enwrapped MoSe2-E/C material. Further, the DFT calculations revealed the origin of better electrochemical performance on MoSe2-E (103) plane. Moreover, MoSe2-E/C showcased a high capacitance of 734 F g−1 (@ 1 A g−1) and 472 F g−1 (@ 20 A g−1) in a three-electrode setup and symmetric cell configuration respectively along with capacity retention of 95.02 % at a current density of 10 A g−1 after 2000 cycles. Hence, the prepared material exhibited its pertinence for rendering distinctive energy-related challenges owing to its unique structural arrangement.

Mixed-Metal Alloying in Hybrid Bronzes.

We show that substitutional alloying during the aqueous self-assembly of layered organic-templated metal oxides produces single-phase mixed-metal hybrids. Single-crystal X-ray diffraction, bulk elemental analyses, and vibrational and electronic spectroscopies corroborate a solid solution of Mo and W atoms at lattice sites within the two-dimensional metal oxide layers. Mild postsynthetic reduction then introduces relatively delocalized electrons to afford mixed-metal hybrid bronzes. To our knowledge, this represents the first demonstration of mixed-metal alloying in a hybrid metal oxide and a rare example of solid-solution formation at low temperature. We show this approach yields mixed-metal congeners with optical band gaps over 130 meV smaller than those of single-metal analogs, while achieving activation energies (Ea) of conduction as low as 78.4(2) meV. Further, metal substitution appears to tune collective electronic phenomena by suppressing the non-Arrhenius behavior observed for Mo-based hybrids. This work considerably expands the nascent hybrid bronze platform to help address energy-related challenges and fundamental solid-state physical questions.

Fabrication of rGO-modified ternary metal chalcogenide hybrid nanocomposite(rGO/Cu2MnSnS4) for high-performance supercapacitors

Efficient supercapacitor electrodes play a crucial role in addressing energy-related challenges and contributing to solutions for the global energy crisis. Recently, Metal chalcogenide/reduced graphene oxide (rGO) composites have garnered considerable attention due to their potential as electrode materials for supercapacitor applications. This study investigates the synergistic catalytic performance achieved by integrating ternary metal-based chalcogenides (Cu2MnSnS4) with 2D carbonaceous materials, highlighting their enhanced conductivity and catalytic activity for applications in energy conversion and environmental remediation. The current study involves the synthesis of a nanocomposite comprising rGO and copper manganese tin sulphide (Cu2MnSnS4), intended for use as an electrode material in energy storage devices. The structural characterization of the rGO/Cu2MnSnS4 nanocomposite was verified through X-ray diffraction, and the morphological analysis was conducted using scanning electron microscopy (SEM). The hybrid Cu2MnSnS4/rGO electrodes have demonstrated remarkable electrochemical characteristics, notably surpassing the performance of pure Cu2MnSnS4 in an alkaline electrolyte. Specifically, the maximum specific capacitance of Cu2MnSnS4/rGO reaches 1539 F g−1 at a scan rate of 10 mV s−1, whereas pure Cu2MnSnS4/rGO achieves a maximum specific capacitance of 948 F g−1 at the same scan rate. The findings from the electrochemical performance evaluation of the electrode material suggest that incorporating into rGO into Cu2MnSnS4 can significantly boost the supercapacitor performance of the Cu2MnSnS4 electrodes. This innovative combination has notably enhanced the overall electrochemical properties of the electrode materials, establishing it as a promising candidate for use in supercapacitor devices.

A scientometrics analysis and visualization of the ecological impact of photovoltaic projects

The topic of global climate change has heated up in recent years, and other environmental and energy-related challenges have been continuously gaining attention. At the same time, the concept of sustainable development and carbon-neutral strategies have emerged. Photovoltaic electricity is strongly promoted by pertinent policies as a high-quality substitute for conventional energy sources. Meanwhile, the potential ecological impacts of photovoltaic (PV) projects should also be noted. Currently, there is a lack of comprehensive research on the ecological impact of photovoltaic projects. It is of great necessity to summarize the research status and future trends of this topic from the perspective of a literature review. Therefore, a scientometrics analysis and visualization of the ecological impact of photovoltaic projects was conducted in this study, using CiteSpace as the visualization tool. Web of Science and Scopus were selected as the databases, and the retrieved articles were analyzed using co-occurrence and cluster analysis to discover hot research subjects and evolving trends, as well as to examine institutional, national, and author collaborations. The results help in the present study field of the ecological effect of photovoltaic projects in identifying and understanding trends and patterns. This study offers theoretical support for PV site selection and ecological protection nearby. It can also motivate academics, politicians, institutions, and governments to formulate ecologically friendly roadmaps and regimes in balancing PV development and ecological protection.

Conversion of CO2 into fibrous carbon materials using Ga-based liquid alloys

This study investigates the catalytic reduction of CO2 using various ratios of Ga-based liquid alloys under different conditions. We explored the alloying of liquid gallium with metals like indium (In) and magnesium (Mg) through mechanical stirring and heating. The alloys, once prepared, were exposed to CO2 in a reactor, with the Ga-In-Mg alloy demonstrating optimal reaction effects. In an exemplary synthesis, 1 g of Ga was combined with 30 wt% In and 7 wt% Mg, yielding a 7 wt% Ga-In-Mg alloy. This alloy, when reacted with CO2 for 10 h, exhibited a maximum weight gain of 445 mg. Elemental analysis showed a carbon content increase from 4.56 % to 72.56 % post-reaction. The reacted alloy, post-acid washing and electron microscopy examination, revealed the production of fibrous carbon materials approximately 7 μm wide. The primary objectives of this research were to identify the optimal temperature for CO2 reduction by the alloy and to determine the most efficient alloy catalyst using orthogonal experimental methods. Furthermore, we aimed to elucidate the catalytic mechanism of gallium-based liquid metal in CO2 reduction. The study also involved analyzing the adsorption and reaction processes by fitting the adsorption and reaction kinetic curves of the liquid metal with CO2. Achieving these objectives could enable the conversion of CO2 into solid carbon products, aligning with current environmental and sustainable development goals. This research offers new insights and innovative approaches to tackling energy-related challenges, highlighting the potential of liquid metal alloys in carbon capture and reduction applications.

The impacts of residential buildings’ energy compliance standards on Iran’s GHG emissions toward achieving the Paris Agreement

Countries have been driven to undertake energy conservation measures to lessen their negative environmental effects due to rising CO2 emissions worldwide. To effectively forecast the future status and evaluate the efficacy of energy-saving and mitigation scenarios, estimating energy consumption and the associated CO2 emissions from fossil fuels is essential. The domestic sector in Iran, liable for using around 30% of the total energy consumption, is the focus of this research. The research has developed a model for future energy consumption and greenhouse gas emissions distinctive to the features of the Iranian residential building stock by considering climate change and using statistical data. To assess prospective results, the Business-As-Usual and energy conservation scenarios are compared. The research also evaluates the potential of energy savings and CO2 reduction across several provinces. The fulfillment of the energy compliance requirements confined in the National Building Regulations by considering the impact of climate change on energy consumption in dwellings of different climate regions has been prioritized. The results show that under different mitigation scenarios, CO2 emissions in the household sector are projected to decrease by 15.7%, 18.4%, 26.8%, and 31.8% by 2030 and 2050. According to the Paris Agreement, these reductions are consistent with Iran's Intended Nationally Determined Contribution. The study emphasizes the significance of targeted measures and policy implementations to lower CO2 emissions in the domestic sector substantially, supporting global efforts to mitigate climate change. The methodology described here addresses energy-related challenges within the constraints of available data on the residential building stock statistic. While acknowledging the potential for further refinement, the country's development of a detailed typology of residential buildings holds promise for enhancing the precision of the modeling in future studies and enabling more robust assessments of energy-saving strategies.

Harnessing artificial intelligence for data-driven energy predictive analytics: A systematic survey towards enhancing sustainability

The escalating trends in energy consumption and the associated emissions of pollutants in the past century have led to energy depletion and environmental pollution. Achieving comprehensive sustainability requires the optimization of energy efficiency and the implementation of efficient energy management strategies. Artificial intelligence (AI), a prominent machine learning paradigm, has gained significant traction in control applications and found extensive utility in various energy-related domains. The utilization of AI techniques for addressing energy-related challenges is favored due to their aptitude for handling complex and nonlinear data structures. Based on the preliminary inquiries, it has been observed that predictive analytics, prominently driven by artificial neural network (ANN) algorithms, assumes a crucial position in energy management across various sectors. This paper presents a comprehensive bibliometric analysis to gain deeper insights into the progression of AI in energy research from 2003 to 2023. AI models can be used to accurately predict energy consumption, load profiles, and resource planning, ensuring consistent performance and efficient resource utilization. This review article summarizes the existing literature on the implementation of AI in the development of energy management systems. Additionally, it explores the challenges and potential areas of research in applying ANN to energy system management. The study demonstrates that ANN can effectively address integration issues between energy and power systems, such as solar and wind forecasting, power system frequency analysis and control, and transient stability assessment. Based on the comprehensive state-of-the-art study, it can be inferred that the implementation of AI has consistently led to energy reductions exceeding 25%. Furthermore, this article discusses future research directions in this field.

Innovative Catalyst Design of Sea-Urchin-like NiCoP Nanoneedle Arrays Supported on N-Doped Carbon Nanospheres for Enhanced HER Performance.

Hydrogen (H2) stands as a clean energy alternative to fossil fuels, especially within the domain of the hydrogen evolution reaction (HER), offering prospective solutions to mitigate both environmental and energy-related challenges. In this work, we successfully synthesized a sea-urchin-like catalyst, specifically a nickel-cobalt phosphide nanoneedle array on N-doped carbon nanospheres (Ni0.5Co1.5P@NCSs), for efficient HER by a sequential hydrothermal and low-temperature phosphating process. The catalyst exhibits sea-urchin-like structures, offering a specific surface area of 298 m2 g-1 and consequently furnishing a greater abundance of active sites. Comparing with non-sea-urchin-like Ni0.5Co1.5P@CN catalysts, the Ni0.5Co1.5P@NCSs exhibit an overpotential of 163 mV at 10 mA cm-2, a Tafel slope of 60 mV dec-1, and a maintained current density of approximately 90% during 50 h of continuous electrolysis. Experiments demonstrate that the outstanding electrochemical properties of the Ni0.5Co1.5P@NCSs originate from nitrogen doping of carbon spheres, the distinctive morphology of sea-urchin-like nanoneedle arrays, and simultaneous enhancements in intermediate adsorption energy, charge transfer, and electrolyte diffusion channel shortening. This work emphasizes a preparation strategy for synthesizing an attractive electrocatalyst with a low cost and efficient HER performance.

Review paper on Green Hydrogen Production, Storage, and Utilization Techniques in Libya

the world is currently facing energy-related challenges due to the cost and pollution of non-renewable energy sources and the increasing power demand from renewable energy sources. Green hydrogen is a promising solution in Libya for converting renewable energy into usable fuel. This paper covers the types of hydrogen, its features, preparation methods, and uses. Green hydrogen production is still limited in the world due to safety requirements because hydrogen has a relatively low ignition temperature and an extensive ignition range and is considered a hazardous element, the lack of infrastructure in Libya, as well as the high cost of production currently. However, the production costs of one megawatt of green hydrogen and fossil fuels are insignificant. This suggests that electricity production from green hydrogen could become an economic competitor to fossil fuels in Libya. This is due to the cost of adding renewable energy to the public electricity grid. Also, the production of gray hydrogen is possible in Libya because of oil through the installation of systems for converting methane gas and capturing carbon dioxide gas.

The Evolution of Wireless Sensor Networks through Smart Radios for Energy Efficiency

This article investigates the significant influence of smart radios on the energy efficiency of Wireless Sensor Networks (WSNs). It explores the incorporation of intelligent radios as a crucial element to enhance WSNs’ sustainability, providing a novel approach to tackle energy-related challenges. Smart radios are essential for prolonging the lifespan of sensor devices and reducing the environmental effect of WSNs by autonomously adjusting communication protocols and optimizing energy consumption. This paper also highlights the differences between 5G and 6G technologies within the WSNs framework. While 5G brought improvements in data speed and connectivity, 6G represents a significant progress by prioritizing energy efficiency as a fundamental goal. This shift represents a fundamental change, with a primary focus on achieving extremely low energy consumption and ensuring the sustainable operation of WSNs. The paper examines crucial technological factors enabling 6G to outperform its predecessor, establishing it as a revolutionary force in the field of wireless communication for sensor networks. This research illuminates the crucial function performed by smart radios in connecting the desire for energy efficiency with the changing environment of wireless sensor networks.

Review of Energy-Related Machine Learning Applications in Drying Processes

Drying processes are among the most energy-intensive industrial processes. There is a need for development of the efficient methods needed for estimating, measuring, and reducing energy use. Different machine learning algorithms might provide some of the answers to these issues in a faster and less costly way, without the need for time-consuming and expensive experiments done at different scales of the dryers. The aim of this paper was to provide a comprehensive overview of machine learning applications for addressing energy-related challenges by exploration of different energy types and energy reduction opportunities. Also, the analysis of the applied algorithms, their specific applications and a critical evaluation of the obtained results are provided. The paper is based on the necessity of the improvements in energy use needed for drying related on the existing data. The overview of the ways for such achievements, and a general classification of machine learning algorithm are the background of the paper. The methods used are the machine learning techniques employed in different energy-related issues for drying processes. The paper focuses on the applications of artificial neural networks and other machine learning algorithms and models for different energy-related issues, including different energy types applications, challenges associated with energy consumption, and opportunities for energy reduction. Not only the applied algorithms, but also their specific applications, and the statistical analysis of the obtained results are also overviewed. Finally, a critical evaluation of the findings highlighting the potentials of machine learning algorithms in addressing energy-related challenges (such as estimation of energy consumption, opportunities for energy reduction, and use of different energy sources) is provided. The presented analysis underscored the effectiveness of machine learning applications for these purposes.

Recent Advances in Black Phosphorous-Based Photocatalysts for Degradation of Emerging Contaminants.

The recalcitrant nature of emerging contaminants (ECs) in aquatic environments necessitates the development of effective strategies for their remediation, given the considerable impacts they pose on both human health and the delicate balance of the ecosystem. Semiconductor-based photocatalytic technology is recognized for its dual benefits in effectively addressing both ECs and energy-related challenges simultaneously. Among the plethora of photocatalysts, black phosphorus (BP) stands as a promising nonmetallic candidate, offering a host of advantages including its tunable direct band gap, broad-spectrum light absorption capabilities, and exceptional charge mobility. Nevertheless, pristine BP frequently underperforms, primarily due to issues related to its limited ambient stability and the rapid recombination of photogenerated electron-hole pairs. To overcome these challenges, substantial research efforts have been devoted to the creation of BP-based photocatalysts in recent years. However, there is a noticeable absence of reviews regarding the advancement of BP-based materials for the degradation of ECs in aqueous solutions. Therefore, to fill this gap, a comprehensive review is undertaken. In this review, we first present an in-depth examination of the fabrication processes for bulk BP and BP nanosheets (BPNS). The review conducts a thorough analysis and comparison of the merits and limitations inherent in each method, thereby delineating the most auspicious avenues for future research. Then, in line with the pathways followed by photogenerated electron-hole pairs at the interface, BP-based photocatalysts are systematically categorized into heterojunctions (Type I, Type II, Z-scheme, and S-scheme) and hybrids, and their photocatalytic performances against various ECs and the corresponding degradation mechanisms are comprehensively summarized. Finally, this review presents personal insights into the prospective avenues for advancing the field of BP-based photocatalysts for ECs remediation.

Review of Serious Energy Games: Objectives, Approaches, Applications, Data Integration, and Performance Assessment

In recent years, serious energy games (SEGs) garnered increasing attention as an innovative and effective approach to tackling energy-related challenges. This review delves into the multifaceted landscape of SEG, specifically focusing on their wide-ranging applications in various contexts. The study investigates potential enhancements in user engagement achieved through integrating social connections, personalization, and data integration. Among the main challenges identified, previous studies overlooked the full potential of serious games in addressing emerging needs in energy systems, opting for oversimplified approaches. Further, these studies exhibit limited scalability and constrained generalizability, which poses challenges in applying their findings to larger energy systems and diverse scenarios. By incorporating lessons learned from prior experiences, this review aims to propel the development of SEG toward more innovative and impactful directions. It is firmly believed that positive behavior changes among individuals can be effectively encouraged by using SEG.

Is energy aid allocated fairly? A global energy vulnerability perspective

The escalating climate change crisis is causing many developing countries to become more vulnerable to energy-related challenges, highlighting the issue of fairness in allocating energy aid. Given this context, it is important to ensure countries that face higher energy vulnerabilities receive a greater share of energy aid funding. This study aims to assess the impact of energy vulnerability on energy aid allocation using a double-hurdle model and a panel of 124 countries from 2002 to 2019. We rely on an index of energy vulnerability to understand the differences in the amount of aid available to different energy-vulnerable recipients, and study the transmission mechanisms underlying this relationship. Our results suggest that the allocation of energy aid has been largely fair. Specifically, energy-vulnerable countries are more likely to be selected as recipients of energy aid during the selection stage, and subsequently receive a greater share of this aid during the allocation stage. However, this effect is heterogeneous and asymmetric. Donors tend to allocate energy aid to countries characterized by relatively low quality of government, low income levels, and limited access to energy assistance. Furthermore, disparities exist in the impact of energy vulnerability on different types of energy support. Specifically, countries with higher energy vulnerability receive a greater proportion of energy policy and energy distribution aid, but are allocated a relatively small share of aid to their non-renewable energy-generation sectors. Additionally, the relationship between energy vulnerability and renewable energy generation aid is not statistically significant. Our results highlight the importance of considering energy vulnerability when allocating energy assistance, and have both scholarly and practical significance. Our findings also have important policy implications for donors by providing guidance on how to promote a fairer allocation of energy aid.

Optimized Energy-Efficient Routing Protocol for Wireless Sensor Network Integrated with IoT: An Approach Based on Deep Convolutional Neural Network and Metaheuristic Algorithms

Wireless sensor networks (WSNs) have emerged as a significant architecture for data collection in various applications. However, the integration of WSNs with IoT poses energy-related challenges due to limited sensor node energy, increased energy consumption for wireless data sharing, and the necessity of energy-efficient routing protocols for reliable transmission and reduced energy consumption. This paper proposes an optimized energy-efficient routing protocol for wireless sensor networks integrated with the Internet of Things. The protocol aims to improve network lifetime and secure data transmission by identifying the optimal Cluster Heads (CHs) in the network, selected using a Tree Hierarchical Deep Convolutional Neural Network. To achieve this, the paper introduces a fitness function that takes into account cluster density, traffic rate, energy, collision, delay throughput, and distance from the capacity node. Additionally, the paper considers three factors, including trust, connectivity, and QoS, to determine the best course of action. The paper also presents a novel optimization approach, using the hybrid Marine Predators Algorithm (MPA) and Woodpecker Mating Algorithm (WMA), to optimize trust, connectivity, and QoS parameters for optimal path selection with minimal delay. The simulation process is implemented in MATLAB, and the developed method’s efficiency is evaluated using several performance metrics. The results of the simulation demonstrate the effectiveness of the proposed method, which achieved significantly lower delay (99.67%, 98.38%, 89.34%, and 97.45%), higher delivery ratio (89.34%, 89.34%, 83.12%, and 88.96%), and lower packet drop (93.15%, 91.25%, 79.90%, and 92.88%) in comparison to existing methods. These outcomes indicate the potential of the optimized energy-efficient routing protocol to improve network lifetime and ensure secure data transmission in WSNs integrated with IoT.

Photocatalytic dehydrogenation of ammonia borane over Ti3C2/MOF-supported Pd-doped Co nanoparticles

Pd-Doped Co nanoparticles were incorporated into Ti3C2/UiO-66-NH2 composite. The heterogeneous catalyst exhibited outstanding catalytic activity for the dehydrogenation of ammonia borane under light irradiation at 298 K.

Electrical energy future of Saudi Arabia: Challenges and opportunities

The economy of Saudi Arabia is primarily oil-based, and the energy system is heavily dependent on fossil fuel sources. Electrical demand in Saudi Arabia has been overgrowing due to the high rates of both population and economy. The real problem is that most of this demand has been met by polluting sources, which in turn causes severe economic and environmental challenges. Despite the abundant amount of clean and freely available renewable sources, the practice of benefiting from these sources is minimal and modest. Therefore, the country has launched a promising vision, one pillar of which is diversifying energy sources and reducing dependence on oil. Since Saudi Arabia is located within the equatorial Sun Belt area, the country is a candidate for leading the World’s renewable energy industry, particularly solar energy. This paper discusses the current energy policy in Saudi Arabia, the associated main energy-related challenges and promising opportunities, and the efforts and actions taken by the country’s policymakers to address these challenges and to take advantage of available opportunities–especially those related to electrical energy–to assure continued future prosperity for subsequent generations.

Incorporating hydrothermal liquefaction into wastewater treatment – Part I: Process optimization for energy recovery and evaluation of product distribution

• Hydrothermal liquefaction (HTL) conditions were optimized for max energy recovery. • Energy recovery was linearly and positively correlated to biocrude yield. • HTL byproducts (aqueous and hydrochar) were minimized at the optimal conditions. • High HTL reaction severities improved biocrude quality (more C and less heteroatoms). • Elemental distribution (including metals) among HTL products was evaluated. The treatment of significant amounts of municipal sewage sludge requires novel and efficient technologies. This study evaluated hydrothermal liquefaction as a means to sustainably convert sludge waste into a renewable energy source – biocrude, which can mitigate both environmental and energy-related challenges. Response surface methodology was employed to investigate the effects of reaction temperature (290–360 °C) and residence time (0–30 min) on product yield and biocrude quality. Both the highest and the lowest reaction temperature or residence time had negative effects on biocrude yield and energy recovery (ER), while high reaction severities improved biocrude quality. Under optimized conditions (332 °C for 16.9 min), biocrude yield (48.9%, dry ash-free) and ER (70.8%) were maximized. Biocrude composition followed the order of N-heterocycles > O-heterocycles > hydrocarbons, while nitrogenous compounds reduced, and hydrocarbons increased with reaction temperature. More distillable fractions in biocrude were also produced at higher reaction severities. The possible reaction pathways of biocrude formation were discussed and updated to include catalytic effects on inherent metals and Brønsted (acidic and basic) sites. The high content of O (7.8–13.1%), N (4.4–4.9%), and TAN (48.6–63.6 mg KOH/g) suggested the necessity of biocrude upgrading. Separating and recycling trace metals (e.g., 497–656 mg/kg Fe) from biocrude are necessary to relieve upgrading challenges. C, N, and P were mostly distributed into HTL biocrude, aqueous, and hydrochar, respectively, allowing their recovery. Most metals were concentrated in hydrochar. The results contribute to the advancement of the state of the art in biorefinery, which will guide the design of full-scale HTL sludge treatment systems combining resource recovery.

Superior intrinsic flame-retardant phosphorylated chitosan aerogel as fully sustainable thermal insulation bio-based material

Owing to the arising environmental pollution and energy-related challenges, the utilization of renewable polysaccharides such as chitosan (CS) in the preparation of biodegradable aerogel heat-insulation materials represents a growing interest. In this study, a simple and low-cost route was proposed to synthesize a phosphorylated chitosan (PCS) with a high substitution degree of phosphate groups in a homogeneous H3PO4/acetic acid solution, and its chemical structure was confirmed using FT–IR spectroscopy, nuclear magnetic resonance, and X–ray photoelectron spectroscopy. An outstanding intrinsic flame-retardant PCS aerogel was directly fabricated via freeze-thawing and freeze-drying process. Remarkably, limited oxygen index values of the PCS aerogels increased to above 80%, and their UL–94 test results achieved V–0 rating. The peak heat release rate and total heat release rate values of PCS-4 aerogel significantly decreased by 91.2% and 73.0% compared with those of chitosan aerogel, respectively. The bio-based PCS aerogel with superior intrinsic flame retardancy, low thermal conductivity, and excellent hydrophobicity shows promise as new sustainable flame-retardant heat-insulation material.