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Journal of Sustainability for Energy
Journal of Sustainability for Energy (JSE)
ISSN (print): 2958-1907
ISSN (online): 2958-1915
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2024: Vol. 3

The Journal of Sustainability for Energy (JSE), distinct for its focus on current energy challenges and sustainable solutions, stands out in its field with peer-reviewed, open-access content. This journal emphasizes the practical implications and theoretical aspects of sustainable energy, contributing significantly to global energy discourse. What sets JSE apart is its dedicated exploration of innovative applications in energy sustainability, making it a critical resource for researchers and practitioners alike. Unlike other journals, JSE uniquely blends theoretical research with practical insights in the field of sustainable energy. Published quarterly by Acadlore, the journal typically releases its four issues in March, June, September, and December each year.

  • Professional Service - Every article submitted undergoes an intensive yet swift peer review and editing process, adhering to the highest publication standards.

  • Prompt Publication - Thanks to our proficiency in orchestrating the peer-review, editing, and production processes, all accepted articles see rapid publication.

  • Open Access - Every published article is instantly accessible to a global readership, allowing for uninhibited sharing across various platforms at any time.

nicola cardinale
University of Basilicata, Italy
Research interests: Exergy Analysis; Life Cycle Assessment; Temperature and Humidity Performance of Buildings and Building Components; Renewable and Alternative Energy Sources; Ventilation and Diffusion of Pollutants in Confined Spaces; Heat Transfer with Phase Change; Lighting and Acoustic Measurements; Heat Generators; Chimney Performance; Refrigeration Technology; Bioclimatic Materials; Diffusion of Air Pollutants
adriana greco
Università degli Studi di Napoli Federico II, Italy
Research interests: Energetic and Exergetic Analysis of Vapour Compression Plants; Refrigerant Fluids; Convective Condensation; Convective Boiling; Solid State Refrigeration

Aims & Scope


Journal of Sustainability for Energy (JSE) is an innovative open-access journal focused on the multifaceted aspects of energy sustainability. Its mission is to publish groundbreaking applied research spanning a wide array of disciplines related to sustainable energy use. JSE serves as a platform for disseminating innovative approaches that enhance sustainable energy practices. The journal welcomes a variety of submissions including reviews, research papers, short communications, and Special Issues on specific topics, particularly those that bridge the gap between research, development, and practical implementation.

JSE aims to inspire scientists to publish comprehensive theoretical and experimental results, with no limitations on paper length to ensure detailed and replicable findings. Distinctive features of JSE include:

  • Every publication benefits from prominent indexing, ensuring widespread recognition.

  • A distinguished editorial team upholds unparalleled quality and broad appeal.

  • Seamless online discoverability of each article maximizes its global reach.

  • An author-centric and transparent publication process enhances submission experience.


JSE's scope is extensive and diverse, differentiating it from other journals in its field by covering:

  • Carbon Reduction: Focuses on methods and technologies aimed at reducing carbon emissions, including carbon capture and storage, as well as policies and practices for lowering the carbon footprint in energy production and usage.

  • Clean Energy Conversion and Utilization: Explores innovative approaches to converting and utilizing clean energy sources, such as solar, wind, and hydroelectric power, to reduce reliance on fossil fuels.

  • Energy Sustainability: Investigates sustainable energy practices, including the development of renewable energy sources, energy efficiency improvements, and long-term sustainability strategies in energy production and consumption.

  • Life Cycle Assessment: Detailed examination of the environmental impact of energy systems throughout their entire life cycle, from production to disposal, including assessments of resource consumption and emissions.

  • Environmental Pollution Reduction: Studies focused on reducing pollution caused by energy production and usage, such as emissions from power plants, industrial processes, and transportation.

  • Climate Change Mitigation: Research on how energy systems can be optimized to mitigate the effects of climate change, including strategies for reducing greenhouse gas emissions and adapting to changing climate conditions.

  • Distributed Energy Systems: Analysis of decentralized energy systems, such as microgrids and distributed generation, which can enhance energy resilience and sustainability at a local level.

  • Advanced Conversion Technologies: Articles on cutting-edge technologies for converting various forms of energy into usable power, with a focus on efficiency and reducing environmental impact.

  • Innovative Technologies in Fossil and Renewable Energy: Exploration of new technologies in both fossil fuel-based and renewable energy sectors, aiming to improve efficiency and sustainability.

  • Integrated Energy Systems: Studies on the integration and optimization of different energy sources and systems to create more efficient and sustainable energy solutions.

  • Sustainable Energy Systems: Covers the development, implementation, and optimization of systems designed for sustainable energy production, distribution, and consumption.

  • Renewable Energy: Detailed research on advancements in renewable energy technologies, such as solar panels, wind turbines, and bioenergy, and their integration into existing energy systems.

  • Optimization of Energy Processes: Techniques and methodologies for enhancing the efficiency and effectiveness of energy-related processes, including production, distribution, and consumption.

  • Smart Materials for Energy Reduction Management: Focus on the use of innovative materials and technologies for reducing energy consumption in various applications.

  • Integration of Smart and Flexible Systems: Articles on combining intelligent technology solutions with flexible operational systems for optimal energy management and efficiency.

  • Smart Grids and Mini/Micro Grids: Research on the development and implementation of smart grids and smaller-scale grid systems that enhance energy distribution efficiency and reliability.

  • Smart grids and mini/micro grids

  • IoT Systems for Energy Savings: Studies on the application of Internet of Things (IoT) technologies in monitoring, controlling, and optimizing energy usage for maximum savings.

  • Energy Conservation Strategies: Strategies and policies aimed at conserving energy across various sectors, including industrial, commercial, and residential applications.

  • Energy Storage: In-depth analysis of energy storage technologies and methods, including batteries, thermal storage, and pumped hydro storage, and their role in stabilizing energy grids.

  • Impacts of Energy Policies: Evaluation of the environmental, social, and economic impacts of various energy policies, and how they influence energy sustainability.

Recent Articles
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Open Access
Research article
Improvement the Preparation of C4 Oolefin Through Ethanol Coupling and Optimization the Gray Correlation Degree Algorithm
pengyuan li ,
qingquan xu ,
cheng huang ,
haoqing wang ,
yisen wang ,
zibo wang ,
yibo zhang ,
ao wang ,
tianci cui ,
xinyue ni ,
yutong wang ,
chen gong
Available online: 03-29-2024


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C4 olefin is an important chemical raw material, but traditional production methods use limited and polluting fossil energy as raw materials. Ethanol stands out from many alternative energy sources because of its wide sources, easy conversion, and low pollution. The preparation of C4 olefins from ethanol has become an effective alternative route for olefin production, which has great environmental and economic value. Metal oxides are the main catalysts for the preparation of C4 olefins from ethanol. In this paper, a $\mathrm{SiO}_2$-$\mathrm{HAP}$ catalyst with both acid and base active sites was designed, and Co metal with dehydrogenation activity was supported on its surface. To improve the catalytic activity and improve the conversion of ethanol and the selectivity of C4 olefin, experiments were carried out by changing the process parameters such as $\mathrm{Co}$ loading (weight ratio of $\mathrm{Co}$ to $\mathrm{SiO}_2$), HAP (hydroxyapatite) mass, ethanol concentration, and reaction temperature. The improved gray relational degree algorithm was used to analyze the relational degree of process parameters with ethanol conversion and C4 olefin selectivity. Experimental results show that the detection accuracy of this algorithm for C4 olefin selectivity is better than that of the traditional algorithm without considering the difference in change rate between data, the detection accuracy is improved by 50%, and the detection accuracy of ethanol conversion is improved by 2%.

Open Access
Research article
Analyzing the Impact of Solar Irradiance on a 50W Monocrystalline Silicon Solar Panel's Performance
hariyanto hariyanto ,
yakobus kogoya ,
daniel parenden ,
nurjannah yusman ,
farid sariman
Available online: 03-25-2024


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Solar energy, a ubiquitous and environmentally friendly source, plays a pivotal role in mitigating carbon emissions and reducing air pollution. This study evaluates the performance of a 50-watt monocrystalline solar panel over a thirty-day period in October 2022, within Merauke Regency, South Papua Province, Indonesia. Adopting an experimental research methodology and comprehensive data collection, measurements of solar intensity, temperature, voltage, and current were systematically gathered using temperature sensors, ammeters, and voltmeters. These measurements were obtained by positioning the solar panel at a perpendicular angle to direct sunlight, with data recorded between 9:00 and 16:00 Eastern Indonesia Time. The analysis of the collected data was conducted to ascertain the panel's efficacy, revealing an average output of 20.68 volts, 1.95 amperes, 40.37 watts, and a 9% efficiency. Notably, peak performance was observed on the tenth day, characterized by 21.30 volts, 2.24 amperes, 47.71 watts, and an efficiency of 11.01%. The findings of this investigation are anticipated to inform the installation and utilization strategies of similar solar panel types within Merauke Regency and potentially broader applications. This study underscores the critical influence of solar irradiance on the operational performance of monocrystalline silicon solar panels, contributing valuable insights to the field of renewable energy research.


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Among the various heat transfer mechanisms, boiling heat transfer is distinguished by its capacity to dissipate substantial heat via the latent heat of vaporization with minimal temperature differentials. This phenomenon is pivotal across a range of industrial applications, including the cooling of macro- and micro-electronic devices, boiler tubes in power generation plants, evaporators in refrigeration systems, and nuclear reactors, where the nucleate pool boiling regime and two-phase flow are of particular interest. The drive to enhance heat exchange systems' efficiency has consistently focused on minimizing heat loss through system miniaturization. This investigation employs numerical simulations via the Fluent software to elucidate the heat transfer and cooling processes facilitated by nanofluids with varied concentrations on differently shaped finned surfaces, alongside the utilization of water and ethylene glycol as base fluids. Specifically, the thermal performance of $\mathrm{Al}_2 \mathrm{O}_3$-water nanofluids at different concentrations (0, 0.3, 0.6, 1, 1.2, and 1.4 percent by volume) was scrutinized under boiling conditions across surfaces endowed with circular, triangular, and square fins. The study confirmed that the incorporation of $\mathrm{Al}_2 \mathrm{O}_3$ nanoparticles into the water base fluid not only enhances its thermal conductivity but, in conjunction with micro-finned surfaces, also augments the available surface area, thereby improving wettability. These modifications collectively contribute to a marked increase in the heat transfer coefficient (HTC) and a reduction in the critical heat flux (CHF). Furthermore, it was observed that at a 0.3% volume concentration of $\mathrm{Al}_2 \mathrm{O}_3$ with square fins, the temperature span extends from 373.1 to 383.1 K. Nonetheless, the long-term stability and efficacy of nanofluids are subject to potential impacts from nanoparticle aggregation and sedimentation. This study underlines the synergistic effect of nanoparticle-enhanced fluids and micro-finned surface architectures in bolstering pool boiling heat transfer, signifying a promising avenue for thermal management advancements in various industrial domains.


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In the quest for sustainable and environmentally friendly biofuels, Calophyllum inophyllum L., commonly known as Nyamplung, presents a promising feedstock due to its high oil content (75%) and a significant proportion of unsaturated fatty acids (approximately 71%). Notably, the oil extracted from this species exhibits higher viscosity and reduced capillarity compared to conventional kerosene, posing unique challenges for biodiesel conversion. This study explores the efficacy of electromagnetic induction heating as a novel transesterification method to produce biodiesel from Nyamplung oil. The process was optimized across a range of temperatures (45-65°C), reaction times (0.43-1.03 minutes), methanol to oil molar ratios (6:1), and a catalyst concentration of KOH at 2% of the total weight of oil and methanol. The conversion of Nyamplung oil into biodiesel was primarily assessed through the formation of methyl esters, with Gas Chromatography-Mass Spectrometry (GC-MS) employed for analytical verification. A comprehensive kinetic analysis revealed a transesterification reaction rate constant of rT=6.46×1014e(-1,068.93/RT) [ME], indicating an activation energy requirement of 1,068 kJ/mol at the operational peak temperature of 65°C. This activation energy is notably lower than that observed with microwave heating, suggesting electromagnetic induction as a more efficient heating mechanism for this reaction. The findings underscore the potential of electromagnetic induction heating in enhancing the conversion efficiency of high-viscosity feedstocks like Nyamplung oil into biodiesel, offering a promising avenue for the production of renewable energy sources. The detailed evaluation of reaction kinetics and activation energies within this study not only contributes to the optimization of biodiesel production processes but also reinforces the viability of Calophyllum inophyllum L. as a sustainable biofuel precursor.

Open Access
Research article
Leveraging Artificial Intelligence for Enhanced Sustainable Energy Management
swapandeep kaur ,
raman kumar ,
kanwardeep singh ,
yinglai huang
Available online: 02-03-2024


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The integration of Artificial Intelligence (AI) into sustainable energy management presents a transformative opportunity to elevate the sustainability, reliability, and efficiency of energy systems. This article conducts an exhaustive analysis of the critical aspects concerning the AI-sustainable energy nexus, encompassing the challenges in technological integration and the facilitation of intelligent decision-making processes pivotal for sustainable energy frameworks. It is demonstrated that AI applications, ranging from optimization algorithms to predictive analytics, possess a revolutionary capacity to bolster intelligent decision-making in sustainable energy. However, this integration is not without its challenges, which span technological complexities and socio-economic impacts. The article underscores the imperative for deploying AI in a manner that is transparent, equitable, and inclusive. Best practices and solutions are proposed to navigate these challenges effectively. Additionally, the discourse extends to recent advancements in AI, including edge computing, quantum computing, and explainable AI, offering insights into the evolving landscape of sustainable energy. Future research directions are delineated, emphasizing the importance of enhancing explainability, mitigating bias, advancing privacy-preserving techniques, examining socio-economic ramifications, exploring models of human-AI collaboration, fortifying security measures, and evaluating the impact of emerging technologies. This comprehensive analysis aims to inform academics, practitioners, and policymakers, guiding the creation of a resilient and sustainable energy future.


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The quest for superior wear-resistant coatings has led to significant advancements in laser cladding technology, yet the escalating requirements for durability under operational conditions challenge the efficacy of existing solutions. This investigation delves into the enhancement of wear resistance in coatings through the integration of particle reinforcement phases, identified as a cost-effective strategy for augmenting coating performance. Emphasis is placed on the systematic classification of particle reinforcements and the methodologies employed for their incorporation. The focus is particularly cast on the incorporation of hard and self-lubricating particles into laser-clad wear-resistant coatings, highlighting innovations in particle addition techniques. An examination of the mechanisms through which hard particlescomprising oxides, carbides, nitrides, borides, and their multifaceted compoundsreinforce coatings is presented, delineating the influence of particle content, size, and morphology on wear resistance. Additionally, the paper explores the state of research on the self-lubricating properties imparted by sulfides, fluorides, graphite, and MAX phase particles under varied thermal conditions. A critical analysis of the benefits and limitations associated with the use of hard and self-lubricating particles in the enhancement of coating durability is conducted. This comprehensive review serves not only to elucidate the current landscape of particle-reinforced, laser-clad coatings but also to inform future research directions aimed at developing coatings capable of withstanding high temperatures and exhibiting exceptional hardness. The commitment to leveraging in situ synthesis for the development of these advanced materials underscores the potential for significant breakthroughs in the field of wear-resistant coatings.


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In this investigation, the enhancement of heat transfer in pipes facilitated by Fe3O4-distilled water nanofluid under the influence of magnetic fields is comprehensively studied. The research primarily focuses on examining the alterations in the thermal boundary layer and fluid flow patterns caused by the application of magnetic fields. It is observed that magnetic fields induce the formation of vortexes, thereby actively influencing the flow patterns within the fluid. These vortexes play a pivotal role in promoting thermal diffusion, resulting in an improved heat transfer rate. The core aim of this study is to quantitatively assess the impact of magnetic nanofluids on the coefficient of heat transfer. A model tube, possessing an inner diameter of 25.4 mm and a length of 210 mm, serves as the basis for the simulations. The investigation encompasses a range of inlet velocities (0.05, 0.1, and 0.5 m/s) and exit pressures to analyze the magnetic field's effect on heat transfer and fluid dynamics. Magnetic flux intensities of one, two, and three Tesla are employed. Notably, the highest temperature of 349 K is recorded in the presence of three magnets, indicating an escalation in temperature with an increase in magnetic strength. However, a diminishing temperature rise is noted over a specified distance with additional magnets. For instance, at a distance of 100 mm, the temperature peaks at 340 K with one magnet, whereas with two magnets, this temperature is attained at a mere 50 mm, suggesting enhanced magnetizer efficiency. Furthermore, the introduction of a magnetic field at the tube's center reveals that high flow velocities tend to counteract the magnetic influence due to their superior force, which impedes the incorporation of metal particles into the fluid. As the magnetic flux value escalates, the nanofluid's magnetic particles either congregate or disperse, thereby obstructing flow and intensifying channel vortices. This phenomenon results in heightened turbulence, instigated by the magnets, which in turn precipitates a rapid increase in fluid flow velocity, thereby impeding the fluid's capacity to adequately absorb heat for efficient heating.


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In the realm of enterprise technology, Internet of Things (IoT)-based wireless devices have witnessed significant advancements, enabling seamless interactions among machines, sensors, and physical objects. A critical component of IoT, Wireless Sensor Networks (WSN), have proliferated across various real-time applications, influencing daily life in both critical and non-critical domains. These WSN nodes, typically small and battery-operated, necessitate efficient energy management. This study focuses on the integration of crow search optimization and firefly algorithms to optimize energy efficiency in IoT-WSN systems. It has been observed that the energy reserve (RE) of a node and its communication costs with the base station are pivotal in determining its likelihood of becoming a Cluster Head (CH). Consequently, energy-saving data aggregation techniques are paramount to prolonging network longevity. To this end, a hybrid approach combining crow search and firefly optimization has been proposed. The crow search algorithm plays a significant role in enhancing data transfer efficiency, while the firefly algorithm is instrumental in selecting optimal cluster heads. This integrated methodology not only promises to extend the network's lifespan but also ensures a balance between energy conservation and data transmission efficacy.
Open Access
Research article
Optimization of Laminar Flow in Non-Circular Ducts: A Comprehensive CFD Analysis
mohammed hadi hameed ,
hafidh hassan mohammed ,
mohammed abdulridha abbas
Available online: 12-30-2023


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This study presents a detailed Computational fluid dynamics (CFD) analysis, focusing on optimizing laminar flow within non-circular ducts, specifically those with square, rectangular, and triangular configurations. The study centers on the effective use of mesh quality and size in these ducts, a factor which is previously underrepresented in those CFD studies that predominantly emphasized turbulent rather than laminar flows. With the help of finite element approach, this study compares the performance of these non-circular ducts, employing Reynolds numbers ranging from 1600 to 2000 and mesh sizes of 6, 12, and 18 mm. A ribbed duct style, arranged in a hybrid manner, is adopted to further this study. Analysis in this paper applied the Single predictive optimization (SPO) technique to the identification of the K-$\varepsilon$-Standard as the preferred viscosity model and a hybrid rib distribution as optimal within the triangular duct configuration. Parameters of a Reynolds number of 1600 and a mesh size of 18 mm emerged as the most effective values for this duct style. Then, the attained results of the Analysis of variance (ANOVA) indicated the F-Criterion's insignificance for Reynolds laminar levels, rendering the laminar viscosity model less relevant within the test section. Additionally, the implementation of the Six sigma procedure (SSP) markedly enhanced both the performance factor (PF) and turbulence intensity, which were observed at 4.90% and 146.77%, respectively. This improvement was most notable in the triangular duct, characterized by rib heights of 66 mm (semi-circle), 66 mm (rectangular), and 38.126 mm (triangular).

Open Access
Research article
Optimization and Performance Analysis of Microalgae Oil-Derived Biodiesel/Diesel Blends: An Emission Test Study
olusola d. ogundele ,
isiaka a. amoo ,
adeniyi o. adesina ,
afeez abidemi
Available online: 12-29-2023


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The deleterious environmental impacts of crude oil, notably significant pollution and escalated greenhouse gas emissions, necessitate alternative fuels. In this context, biodiesel, particularly when blended with diesel, emerges as a viable substitute. This study investigates the emissions and performance characteristics of diesel-biodiesel blends, utilizing microalgae oil-based biodiesel. Variations in the catalyst (potassium hydroxide, KOH), reaction duration (30-110 minutes), and temperature (30-70oC) were explored to determine their influence on biodiesel yield. The biodiesel produced was characterized using Fourier-transform infrared spectroscopy (FTIR), revealing distinct absorption bands indicative of various functional groups present. Furthermore, emission testing was conducted on a TecQuipment TD202 diesel engine, a naturally aspirated, single-cylinder, four-stroke, direct-injection, air-cooled model. Optimization studies revealed that the optimal biodiesel yield was achieved using 2g of KOH, at a temperature of 60oC, and within a reaction time of 90 minutes. Emission testing demonstrated a decrease in exhaust gas temperature (EGT) with reduced biodiesel blend ratios and an increase with engine speed across all blends. Carbon monoxide (CO) emissions diminished with lower biodiesel concentrations, whereas carbon dioxide (CO2) and nitrogen oxides (NOx) emissions escalated. Total hydrocarbons (THCs) emissions increased with reduced biodiesel content, and smoke opacity escalated with lower biodiesel blend ratios. This investigation methodically examines the emissions from various biodiesel blends, underscoring their potential as a cleaner, more sustainable option for the transportation sector.

Open Access
Research article
Investigating the Impact of Ignition Timing Variations on Single-Cylinder Otto Engine Performance with E50 Fuel Blend
rendy adhi rachmanto ,
rizqi husain alfathan ,
wibawa endra juwana ,
zainal arifin ,
eko prasetya budiana ,
singgih dwi prasetyo
Available online: 09-29-2023


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The exponential growth in motorized vehicle usage presents myriad challenges, encompassing environmental pollution and sustained energy shortages. To address these challenges, the exploration of sustainable energy alternatives is imperative, with ethanol-based fuels emerging as a viable option. This investigation delves into the performance of a single-cylinder Otto engine, with a focus on the effects of ignition timing variations using a 50% ethanol and 50% pertalite blend, denoted as E50. The ignition timing was systematically varied to standard, +2°, +4°, and -2°. The results demonstrated that the +4° ignition timing, in conjunction with E50, delivered superior performance, culminating in a maximum torque of 8.02 Nm at 4000 rpm and a peak power output of 4.15 kW at 8000 rpm. Concurrently, optimal engine efficiency was achieved, with the Brake Specific Fuel Consumption (BSFC) reaching its lowest value of 0.307 Kg/kW.h at 5000 rpm and Brake Thermal Efficiency (BTE) peaking at 36.10% at the same rotational speed. When contrasted with alternative fuels, the E50 blend resulted in an average torque reduction of 13.27% and a 14.46% decrease in power output. Despite this, significant enhancements in engine efficiency were observed. A 25.05% improvement in BSFC was noted, albeit with a reduction in fuel efficiency, while BTE experienced a 5.02% increase, indicative of augmented engine efficiency, particularly at the +4° ignition timing. This study underscores the potential of E50 and altered ignition timing in reducing reliance on fossil fuels, thus contributing to the transition towards sustainable energy solutions in the automotive sector.

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