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This study aims to analyze the development of studies on the use of biomass as a renewable energy source to support national energy security using a bibliometric approach. Research data were obtained from the Scopus, Web of Science, and Google Scholar databases with a publication range of 2015-2025. The analysis was conducted using VOSviewer and Biblioshiny. The results show a significant increase in publication trends in the last decade, especially in the period 2016-2024, reflecting the increasing academic attention to biomass as a solution in the energy transition. Keyword visualization shows that biomass is closely related to concepts such as combustion, thermal efficiency, calorific value, and pelletizing. China is the country with the highest publication contribution, while Indonesia is strategically positioned due to its abundant biomass waste potential. Overall, biomass has great potential to support energy diversification, reduce dependence on fossil fuels, and strengthen national energy security in a sustainable manner.

The global energy crisis and climate change are driving the development of biodiesel as a renewable energy source. Graphite as an additive shows significant potential in improving the efficiency and reducing emissions of biodiesel. This study maps graphite-biodiesel research in Southeast Asia using a meta analysis of systematic reviews of 68 publications from Scopus, Web of Science, and ScienceDirect from 2015-2024. The results show that Malaysia leads in publication contributions (32%), followed by Thailand (28%) and Indonesia (18%). The optimal graphite concentration of 50 ppm increases brake thermal efficiency by 8.3% and reduces CO (15.7%), HC (12.4%), and smoke (18.9%) emissions, although there is an increase in NOx (6.8%). Palm oil methyl ester dominated the research (56%). Indonesia has strategic opportunities with abundant feedstock and graphite deposits, but faces challenges in research infrastructure, limited international collaboration, and the absence of an integrated national roadmap. Infrastructure investment, human resource strengthening, and industry academia collaboration are needed to accelerate national biodiesel research.

This study aims to analyze the temperature distribution in an LPG-fueled chili drying machine using Computational Fluid Dynamics (CFD) simulation. The simulation was performed using SolidWorks Flow Simulation 2022 to investigate the effect of inlet air temperature and velocity on temperature uniformity inside the drying chamber. Three inlet temperature variations were applied: 60°C, 70°C, and 80°C, combined with two air velocities of 10 m/s and 11 m/s. The results showed that these parameters significantly influence temperature distribution. The optimum condition was achieved at 70°C and 10 m/s with a temperature uniformity efficiency (

Energy efficiency in water heaters is a crucial factor in ship operational environments due to limited electricity resources that rely on generators. This study aims to design and build an IoT-based water heater monitoring system with an innovative heat storage medium in the form of a mixture of silica sand and paraffin wax to improve thermal efficiency. Although previous studies have developed temperature monitoring and control systems in IoT-based water heaters, this study specifically fills this gap by analyzing the performance of adding silica sand to overcome the low thermal conductivity of paraffin wax. Using the Research and Development (R&D) method, this system was built with an ESP32 microcontroller as the control center, a DS18B20 temperature sensor for accurate measurements, and the Blynk and Google Sheets platforms for real-time monitoring and data recording. Performance testing was conducted by comparing the water heating rate between pure paraffin wax media and the mixed media. The results showed that the monitoring system functioned reliably, and the main finding proved that the addition of silica sand to paraffin wax significantly increased heating efficiency. This was clearly seen from the reduction in time required to raise the water temperature to 40°C, from 2.5 hours to only 1 hour in the second heating cycle. The results of this study indicate that the integration of silica sand and paraffin wax media with IoT technology can increase the efficiency of water heaters and provide an innovative solution for energy-efficient and environmentally friendly temperature control.

This study aims to compare the thermal efficiency of two aluminum and iron-based pans in the water heating process. This research method uses a mixed approach that includes direct observation (qualitative) and quantitative analysis based on changes in water temperature after heating at two volume variations, namely 0.25 L and 0.5 L. Heating was carried out with two time differences, the total of each experiment was four experiments, with two experiments for five minutes and also two experiments for ten minutes. The results showed that iron pans produced heat of 66,150 J at a volume of 0.25 L and 151,200 J at a volume of 0.5 L. Meanwhile, an aluminum pan could produce heat of 53,550 J at a volume of 0.25 L and 67,200 J at a volume of 0.5 L. The difference in heat value was influenced by the thermal conductivity and physical characteristics of each material. This study provides an understanding of the thermal performance of both pot materials and can be considered in the selection of efficient cooking utensils in the household environment.

Background: The global energy transition requires low-carbon solutions that can be integrated into existing thermal systems without drastic infrastructure changes. Hydrogen blending in conventional combustion systems has emerged as a promising pathway to reduce carbon emissions while maintaining operational flexibility. Objective: This study aims to experimentally evaluate the effect of hydrogen blending ratios (0–100% by volume) on thermal efficiency, CO₂ emissions, and NOx emissions, and to determine the optimal blending range based on technical and economic feasibility. Methods: An experimental thermal system prototype was developed and tested under controlled conditions with three repetitions per operating point. Performance parameters included combustion temperature, fuel consumption rate, and thermal efficiency, while emissions of CO₂ and NOx were measured using a calibrated gas analyzer. Data were analyzed using descriptive statistics, one-way ANOVA at a 0.05 significance level, confidence interval estimation, and linear regression to examine the relationship between hydrogen fraction and emission reduction. Results: The findings indicate that increasing hydrogen fraction significantly improves thermal efficiency, reaching 87.5% at 100% hydrogen, while CO₂ emissions decrease linearly to zero. However, NOx emissions increase with higher hydrogen content due to elevated combustion temperatures. Statistical analysis confirms that hydrogen ratio has a significant effect on efficiency and emissions, with a strong linear correlation between hydrogen fraction and CO₂ reduction. A blending range of 40–60% hydrogen provides the most balanced performance in terms of efficiency improvement, emission reduction, and cost feasibility.

This study explores the integration of Artificial Intelligence (AI) with thermal optimization in Waste-to-Energy (WtE) systems to enhance both energy recovery and emission control. Introduction: The growing need for sustainable urban waste management has highlighted the importance of optimizing WtE systems. AI technologies, including machine learning and deep learning, have shown potential in improving the efficiency of WtE processes, especially in reducing emissions and enhancing energy recovery. Literature Review: Previous research indicates that AI has been successfully applied to various WtE technologies such as pyrolysis, gasification, and incineration, yet the integration of AI specifically for thermal optimization remains underexplored. Most studies focus on predictive models for emission reduction rather than real time thermal optimization. Materials and Method: The study proposes the development of an AI-driven framework that integrates real time data collection from IoT sensors, predictive modeling, and real time control algorithms. The system optimizes key parameters such as combustion temperature and fuel flow to enhance energy recovery and minimize emissions. The method includes data collection from operational WtE plants, followed by model development using machine learning algorithms. Results and Discussion: Initial simulations and pilot testing showed significant improvements in energy efficiency and emission reduction. AI-driven systems outperformed conventional WtE systems by optimizing operational parameters in real time. The study identifies gaps in AI integration for thermal optimization and suggests future research directions, including the integration of AI with smart grids and carbon credit systems for more sustainable WtE operations.

The rapid development of technology demands solutions to optimise heat management for electronic components. Through this study, the researchers evaluated the effectiveness of various types of coolants in a liquid cooling system for electrical equipment, especially CPUs. Using design simulations conducted through SolidWorks software, this research aims to optimise the flow rate and selection of coolant type to achieve maximum thermal efficiency and reduce production and operational costs. The simulation results show that water is the most efficient coolant with significant temperature reduction compared to Ethylene Glycol (EG), Propylene Glycol (PG), and silicone oil. Water shows a temperature drop of 11.76°C, while EG and PG show a temperature drop of 8.82°C and 7.35°C respectively and silicone oil shows a temperature drop of 4.9°C. It can be seen from the simulation that water shows the most effective temperature reduction compared to EG, PG, and Silicone Oil.      

This study explores the use of graphene-based nanofluids in enhancing the performance of solar-powered desalination systems. A laboratory-scale desalination system was developed to simulate the evaporation process, powered by solar energy, with the integration of graphene-based nanofluids to improve thermal efficiency. The experimental setup measured evaporation rates, energy consumption, and temperature profiles under varying solar radiation conditions (400–800 W/m²). Results revealed that the system with nanofluids demonstrated up to a 35% increase in evaporation rates compared to the baseline system without nanofluids, indicating enhanced heat transfer properties. Moreover, energy consumption was reduced by up to 20%, highlighting the improved energy efficiency of the system with nanofluids. The system with nanofluids exhibited higher temperatures in the evaporator, confirming more effective thermal utilization. Statistical analyses, including t-tests and regression analysis, confirmed the significant impact of nanofluids on both evaporation rates and energy consumption. This study demonstrates that graphene-based nanofluids offer a sustainable and energy-efficient solution for solar-powered desalination, particularly in areas with abundant solar radiation. The integration of nanofluids not only enhances the efficiency of the desalination process but also reduces operational costs, making it a promising alternative for addressing water scarcity in a sustainable manner. Further research is needed to optimize nanofluid formulations and assess their long-term feasibility for large-scale applications.