Rubber seed and Kusum oils are inedible feedstocks unveiling potential of bioenergy valorisation. Biodiesel via transesterification using lipases is industrially lucrative if process is optimized for economical utilization of feedstock and other resources. The inedible oils as feedstock in the present study, fulfils the global mission towards a resource rich and environment friendly circular economy. This research paper focuses on green energy production. The selected feedstocks, rubber seed oil and kusum oil were biotransesterified with methanol as acyl acceptor using lipases from Candida rugosa as catalyst. The interactive process parameters affecting the biodiesel yield are temperature, factor to methanol to oil ratio, percentage of lipase and buffer, pH, and the agitation speed. Since the process parameters are interactive, hence were statistically optimized using Design Expert®. The high specificity of lipases from C. rugosa has not been reported in literature for biotransesterification of rubber seed oil and kusum oil. The optimized process parameters for rubber seed oil and kusum oil produced biodiesel yields as 95.92 % and 94.70 %, respectively, using free lipases. The properties of produced biodiesel such as density, kinematic viscosity and gross calorific value also supported the set norms as per US standards, ASTM-D6751. The two step addition of acyl acceptor during biotransesterification of rubber seed oil and kusum oil, improved the biodiesel yield by 1.50 % and 3.14 %, respectively. It proved the adverse effect of methanol concentration on lipases activity can be mitigated. The present research on biodiesel aligns to United Nations-SDG7 ‘Green Energy Technology’ from unused/underutilised feedstocks.
{"title":"Design Expert® assisted process optimization of biodiesel production via biotransesterification from inedible oils using Candida rugosa lipases","authors":"Anil Kumar, Aradhana Srivastava, Vishwender Pratap Singh","doi":"10.1016/j.jfueco.2025.100154","DOIUrl":"10.1016/j.jfueco.2025.100154","url":null,"abstract":"<div><div>Rubber seed and Kusum oils are inedible feedstocks unveiling potential of bioenergy valorisation. Biodiesel via transesterification using lipases is industrially lucrative if process is optimized for economical utilization of feedstock and other resources. The inedible oils as feedstock in the present study, fulfils the global mission towards a resource rich and environment friendly circular economy. This research paper focuses on green energy production. The selected feedstocks, rubber seed oil and kusum oil were biotransesterified with methanol as acyl acceptor using lipases from <em>Candida rugosa</em> as catalyst. The interactive process parameters affecting the biodiesel yield are temperature, factor to methanol to oil ratio, percentage of lipase and buffer, pH, and the agitation speed. Since the process parameters are interactive, hence were statistically optimized using Design Expert®. The high specificity of lipases from <em>C. rugosa</em> has not been reported in literature for biotransesterification of rubber seed oil and kusum oil. The optimized process parameters for rubber seed oil and kusum oil produced biodiesel yields as 95.92 % and 94.70 %, respectively, using free lipases. The properties of produced biodiesel such as density, kinematic viscosity and gross calorific value also supported the set norms as per US standards, ASTM-D6751. The two step addition of acyl acceptor during biotransesterification of rubber seed oil and kusum oil, improved the biodiesel yield by 1.50 % and 3.14 %, respectively. It proved the adverse effect of methanol concentration on lipases activity can be mitigated. The present research on biodiesel aligns to United Nations-SDG7 ‘Green Energy Technology’ from unused/underutilised feedstocks.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"26 ","pages":"Article 100154"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-11-20DOI: 10.1016/j.jfueco.2025.100152
Abdullah Shahjalal, Roy Kalawsky, Demetrios Joannou, Faruk Ozdemir
Accurate prediction of acoustic energy absorption in gas turbine combustors is critical for enhancing performance, mitigating thermoacoustic instabilities, and reducing emissions. Traditional experimental and mathematical modeling approaches often struggle to capture the nonlinear and frequency-dependent behaviour of combustor liners, especially under varying operational conditions. This study presents a comprehensive evaluation of four machine learning (ML) models—Random Forest (RF), Extreme Gradient Boosting (XGB), Convolutional Neural Networks (CNN), and K-Nearest Neighbors (KNN)—against full-scale experimental measurements across six double-liner and three single-liner gas turbine configurations. A total of 615 operational records were used to train and validate model performance. In the double liner configuration, the RF and CNN models achieved the lowest average RMSE of 0.044, closely followed by XGB (0.045). However, XGB demonstrated the highest predictive accuracy (R² = 0.896), outperforming RF (0.891) and CNN (0.895), whose performance was partly constrained by limited dataset size. In the single liner configuration, XGB again delivered superior results (RMSE = 0.077, R² = 0.782) compared with RF (0.081, 0.580) and KNN (0.092, 0.470). The KNN model exhibited poor generalisation in the high-dimensional feature space, with R² dropping to 0.32 in certain tests. Overall, the machine learning framework reduced prediction error by approximately 31–56.2 % compared with conventional semi-empirical models (COS and COT), while requiring significantly lower computational effort to achieve comparable or superior accuracy. This is the first study to benchmark ML models against full-scale acoustic absorption data, introducing a validated data-driven framework with implications for combustor liner design, predictive maintenance, and real-time diagnostics. The integration of ML models into simulation workflows promises substantial reductions in experimental cost and improved design responsiveness. These findings offer a scalable, computationally efficient solution for aeroacoustic optimization—supporting the broader goal of cleaner, quieter, and more efficient gas turbine systems.
{"title":"Benchmarking machine learning models against full-scale acoustic absorption measurements in gas turbine liners","authors":"Abdullah Shahjalal, Roy Kalawsky, Demetrios Joannou, Faruk Ozdemir","doi":"10.1016/j.jfueco.2025.100152","DOIUrl":"10.1016/j.jfueco.2025.100152","url":null,"abstract":"<div><div>Accurate prediction of acoustic energy absorption in gas turbine combustors is critical for enhancing performance, mitigating thermoacoustic instabilities, and reducing emissions. Traditional experimental and mathematical modeling approaches often struggle to capture the nonlinear and frequency-dependent behaviour of combustor liners, especially under varying operational conditions. This study presents a comprehensive evaluation of four machine learning (ML) models—Random Forest (RF), Extreme Gradient Boosting (XGB), Convolutional Neural Networks (CNN), and K-Nearest Neighbors (KNN)—against full-scale experimental measurements across six double-liner and three single-liner gas turbine configurations. A total of 615 operational records were used to train and validate model performance. In the double liner configuration, the RF and CNN models achieved the lowest average RMSE of 0.044, closely followed by XGB (0.045). However, XGB demonstrated the highest predictive accuracy (R² = 0.896), outperforming RF (0.891) and CNN (0.895), whose performance was partly constrained by limited dataset size. In the single liner configuration, XGB again delivered superior results (RMSE = 0.077, R² = 0.782) compared with RF (0.081, 0.580) and KNN (0.092, 0.470). The KNN model exhibited poor generalisation in the high-dimensional feature space, with R² dropping to 0.32 in certain tests. Overall, the machine learning framework reduced prediction error by approximately 31–56.2 % compared with conventional semi-empirical models (COS and COT), while requiring significantly lower computational effort to achieve comparable or superior accuracy. This is the first study to benchmark ML models against full-scale acoustic absorption data, introducing a validated data-driven framework with implications for combustor liner design, predictive maintenance, and real-time diagnostics. The integration of ML models into simulation workflows promises substantial reductions in experimental cost and improved design responsiveness. These findings offer a scalable, computationally efficient solution for aeroacoustic optimization—supporting the broader goal of cleaner, quieter, and more efficient gas turbine systems.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"26 ","pages":"Article 100152"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145659178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-17DOI: 10.1016/j.jfueco.2026.100156
Lijun Yang, Jun Xia, Min Xiang, Zhiqiang Shen, Fanzhen Zhang, Yunzhi Xi, Lifan Yu
During the long-term storage of RDX/HTPB propellants, slow aging frequently occurs, resulting in irreversible alterations such as internal structural distortion, diminished stability, impaired mechanical properties, and sudden changes in the burning rate. In extreme cases, unintended ignition or spontaneous combustion might occur, posing safety hazards during use. A deep understanding of the microscopic decomposition mechanisms of RDX/HTPB propellants is key to ensuring operational stability and reliability. Using the ReaxFF/lg reactive force field, molecular dynamics simulations of the RDX/HTPB propellant aging process at different temperatures were conducted. Changes in the potential energy, species evolution, reaction pathways, and product distribution patterns were analyzed. The MD results indicate that the lower the temperature is, the lower the aging rate. When the temperature exceeds 1000 K, the aging rate exponentially increases with increasing temperature. The aging process begins with the cleavage of N−NO2 bonds in RDX. The reaction products primarily consist of intermediates, final products, and some large carbon-containing clusters. The fitted activation energy was determined to be 85.59 kJ/mol, with a predicted storage life of 23.56 years at 20 °C. The storage life of the propellant is negatively correlated with temperature, indicating that low-temperature environments are beneficial for extending the storage duration of the propellant.
{"title":"Molecular dynamics simulation study on the aging process of RDX/HTPB propellants at different temperatures","authors":"Lijun Yang, Jun Xia, Min Xiang, Zhiqiang Shen, Fanzhen Zhang, Yunzhi Xi, Lifan Yu","doi":"10.1016/j.jfueco.2026.100156","DOIUrl":"10.1016/j.jfueco.2026.100156","url":null,"abstract":"<div><div>During the long-term storage of RDX/HTPB propellants, slow aging frequently occurs, resulting in irreversible alterations such as internal structural distortion, diminished stability, impaired mechanical properties, and sudden changes in the burning rate. In extreme cases, unintended ignition or spontaneous combustion might occur, posing safety hazards during use. A deep understanding of the microscopic decomposition mechanisms of RDX/HTPB propellants is key to ensuring operational stability and reliability. Using the ReaxFF/lg reactive force field, molecular dynamics simulations of the RDX/HTPB propellant aging process at different temperatures were conducted. Changes in the potential energy, species evolution, reaction pathways, and product distribution patterns were analyzed. The MD results indicate that the lower the temperature is, the lower the aging rate. When the temperature exceeds 1000 K, the aging rate exponentially increases with increasing temperature. The aging process begins with the cleavage of N−NO<sub>2</sub> bonds in RDX. The reaction products primarily consist of intermediates, final products, and some large carbon-containing clusters. The fitted activation energy was determined to be 85.59 kJ/mol, with a predicted storage life of 23.56 years at 20 °C. The storage life of the propellant is negatively correlated with temperature, indicating that low-temperature environments are beneficial for extending the storage duration of the propellant.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"26 ","pages":"Article 100156"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-26DOI: 10.1016/j.jfueco.2026.100155
Herman Heng , Hugo Keck , Christian Chauveau , Fabien Halter , Jeffrey Bergthorson
The combustion behaviour of single iron particles is experimentally investigated at a fixed oxygen concentration of 40%, diluted in 60% He, Ar, and Xe, using an electrostatic levitator with laser ignition. While the three gas mixtures have identical adiabatic flame temperature predictions using thermodynamic equilibrium calculations, the experiments reveal a noticeable difference in particle temperatures due to differences in Lewis number. This temperature variation is evident in particle luminosity and in nano-oxide formation, observed through the attenuation of white LED light. In the helium-diluted mixture, insignificant nano-oxide formation is observed due to lower particle temperatures, which subsequently reduces Fe evaporation and vapour-phase combustion. In contrast, xenon dilution enhances vapour-phase combustion, yielding pronounced nano-oxide formation, while argon shows intermediate behaviour. Despite large differences in oxygen mass diffusivity, measured combustion times, defined from melting onset to peak temperature, are comparable for helium- and argon-diluted mixtures, and only slightly longer for the xenon-diluted mixture. Using these combustion times, the discreteness parameter, , of iron flames is qualitatively compared: it is 1.71 times higher in 40%O–60%Ar than in 40%O–60%Xe, and 5.28 times higher in 40%O–60%He than in 40%O–60%Xe. The results indicate that discrete flame propagation is likely in argon-diluted mixtures but unlikely in helium-diluted mixtures. The present study highlights how the Lewis number influences the interplay of oxygen mass diffusivity and vapour-phase combustion in evaluating particle combustion time and flame discreteness, providing essential insights for designing future discrete flame microgravity experiments in different gas mixtures and advancing iron combustion models.
{"title":"Evaluation of iron flame discreteness in monoatomic gases based on single particle combustion behaviour","authors":"Herman Heng , Hugo Keck , Christian Chauveau , Fabien Halter , Jeffrey Bergthorson","doi":"10.1016/j.jfueco.2026.100155","DOIUrl":"10.1016/j.jfueco.2026.100155","url":null,"abstract":"<div><div>The combustion behaviour of single iron particles is experimentally investigated at a fixed oxygen concentration of 40%, diluted in 60% He, Ar, and Xe, using an electrostatic levitator with laser ignition. While the three gas mixtures have identical adiabatic flame temperature predictions using thermodynamic equilibrium calculations, the experiments reveal a noticeable difference in particle temperatures due to differences in Lewis number. This temperature variation is evident in particle luminosity and in nano-oxide formation, observed through the attenuation of white LED light. In the helium-diluted mixture, insignificant nano-oxide formation is observed due to lower particle temperatures, which subsequently reduces Fe evaporation and vapour-phase combustion. In contrast, xenon dilution enhances vapour-phase combustion, yielding pronounced nano-oxide formation, while argon shows intermediate behaviour. Despite large differences in oxygen mass diffusivity, measured combustion times, defined from melting onset to peak temperature, are comparable for helium- and argon-diluted mixtures, and only slightly longer for the xenon-diluted mixture. Using these combustion times, the discreteness parameter, <span><math><mi>χ</mi></math></span>, of iron flames is qualitatively compared: it is 1.71 times higher in 40%O<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>–60%Ar than in 40%O<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>–60%Xe, and 5.28 times higher in 40%O<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>–60%He than in 40%O<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>–60%Xe. The results indicate that discrete flame propagation is likely in argon-diluted mixtures but unlikely in helium-diluted mixtures. The present study highlights how the Lewis number influences the interplay of oxygen mass diffusivity and vapour-phase combustion in evaluating particle combustion time and flame discreteness, providing essential insights for designing future discrete flame microgravity experiments in different gas mixtures and advancing iron combustion models.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"26 ","pages":"Article 100155"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-26DOI: 10.1016/j.jfueco.2025.100150
Pascalin Tiam Kapen
<div><div>Coastal regions in Cameroon, including Douala, Kribi, Campo, Dibamba, and Limbe, faced persistent electricity challenges driven by grid instability, growing demand, and dependence on fossil fuels. Solar resource availability was high but intermittent, whereas tidal energy was predictable and energy-dense yet underused. This pilot delivers the first Cameroonian assessment of an off-grid tidal/PV/electrolyzer/hydrogen-storage/fuel-cell architecture, explicitly co-optimizing electricity service and green hydrogen production, and evaluating performance with a tri-metric economic lens (net present cost, levelized cost of electricity, and the levelized cost of hydrogen). The system was optimized to minimize net present cost (NPC), levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH) and three tidal-flow scenarios were analyzed to represent hydrokinetic variability. The design served households, small businesses, fishing activities, schools, and health facilities with a baseline demand of 389.50 kWh/day; surplus renewable power drove the electrolyzer to produce hydrogen for later reconversion in the fuel cell. Under the first scenario (1.25 m/s average speed), the optimal mix comprised 137 PV modules (600 W each), a 100 kW fuel cell, six 40 kW tidal turbines, six 10 kW electrolyzers, a 19.5 kW converter, and 41 hydrogen tanks (40 L each), yielding an NPC of US$ 2.16 million, an LCOE of US$ 0.782/kWh, and a LCOH of US$ 19.2/kg of hydrogen. The second scenario (1.47 m/s) required only 12 PV modules, one electrolyzer, and an 11.3 kW converter, lowering costs to an NPC of US$ 1.52 million, an LCOE of US$ 0.553/kWh, and a LCOH of US$ 15.4/kg of hydrogen. In the third scenario (1.61 m/s), the configuration shifted to 298 PV modules, three tidal turbines, eight electrolyzers, and a 39.6 kW converter, resulting in the highest NPC (US$ 2.47 million) and LCOE (US$ 0.901/kWh), with a LCOH of US$ 18.8/kg of hydrogen. The study also contributes a transparent, component-wise employment indicator linking installed capacities/energies to jobs; deployment is expected to create about seven local jobs during installation and early operation, tidal turbines (3), solar panels (1), electrolyzers (1), hydrogen tanks (1), and fuel cell (1), with additional minor operation and maintenance positions thereafter. Social analysis indicated improved energy access, support for local livelihoods, and job creation; environmental results confirmed clean operation with limited marine disturbance. A sensitivity study varying capital and replacement-cost multipliers showed robust performance across economic conditions. Taken together, these contributions provide a decision-ready blueprint for coastal communities: a first-of-its-kind Cameroonian hybrid that quantifies both electricity and hydrogen costs (including feasible LCOH) and demonstrates socio-economic co-benefits, offering a cost-effective pathway to strengthen energy security, foster local development,
{"title":"Techno-enviro-socio-economic assessment and sensitivity analysis of an off-grid Tidal/Fuel Cell/Electrolyzer/Photovoltaic hybrid system for hydrogen and electricity production in Cameroon coastal areas","authors":"Pascalin Tiam Kapen","doi":"10.1016/j.jfueco.2025.100150","DOIUrl":"10.1016/j.jfueco.2025.100150","url":null,"abstract":"<div><div>Coastal regions in Cameroon, including Douala, Kribi, Campo, Dibamba, and Limbe, faced persistent electricity challenges driven by grid instability, growing demand, and dependence on fossil fuels. Solar resource availability was high but intermittent, whereas tidal energy was predictable and energy-dense yet underused. This pilot delivers the first Cameroonian assessment of an off-grid tidal/PV/electrolyzer/hydrogen-storage/fuel-cell architecture, explicitly co-optimizing electricity service and green hydrogen production, and evaluating performance with a tri-metric economic lens (net present cost, levelized cost of electricity, and the levelized cost of hydrogen). The system was optimized to minimize net present cost (NPC), levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH) and three tidal-flow scenarios were analyzed to represent hydrokinetic variability. The design served households, small businesses, fishing activities, schools, and health facilities with a baseline demand of 389.50 kWh/day; surplus renewable power drove the electrolyzer to produce hydrogen for later reconversion in the fuel cell. Under the first scenario (1.25 m/s average speed), the optimal mix comprised 137 PV modules (600 W each), a 100 kW fuel cell, six 40 kW tidal turbines, six 10 kW electrolyzers, a 19.5 kW converter, and 41 hydrogen tanks (40 L each), yielding an NPC of US$ 2.16 million, an LCOE of US$ 0.782/kWh, and a LCOH of US$ 19.2/kg of hydrogen. The second scenario (1.47 m/s) required only 12 PV modules, one electrolyzer, and an 11.3 kW converter, lowering costs to an NPC of US$ 1.52 million, an LCOE of US$ 0.553/kWh, and a LCOH of US$ 15.4/kg of hydrogen. In the third scenario (1.61 m/s), the configuration shifted to 298 PV modules, three tidal turbines, eight electrolyzers, and a 39.6 kW converter, resulting in the highest NPC (US$ 2.47 million) and LCOE (US$ 0.901/kWh), with a LCOH of US$ 18.8/kg of hydrogen. The study also contributes a transparent, component-wise employment indicator linking installed capacities/energies to jobs; deployment is expected to create about seven local jobs during installation and early operation, tidal turbines (3), solar panels (1), electrolyzers (1), hydrogen tanks (1), and fuel cell (1), with additional minor operation and maintenance positions thereafter. Social analysis indicated improved energy access, support for local livelihoods, and job creation; environmental results confirmed clean operation with limited marine disturbance. A sensitivity study varying capital and replacement-cost multipliers showed robust performance across economic conditions. Taken together, these contributions provide a decision-ready blueprint for coastal communities: a first-of-its-kind Cameroonian hybrid that quantifies both electricity and hydrogen costs (including feasible LCOH) and demonstrates socio-economic co-benefits, offering a cost-effective pathway to strengthen energy security, foster local development,","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"25 ","pages":"Article 100150"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145474446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-09DOI: 10.1016/j.jfueco.2025.100148
Pascalin Tiam Kapen
In the pursuit of clean and efficient energy solutions tailored to Africa’s diverse environmental conditions, this study presents a multi-parameter simulation and comparative performance analysis of low-temperature proton exchange membrane fuel cells (PEMFC) across the main climatic zones of the African continent. The work addresses the critical challenge of how temperature and humidity variations, specific to different geographic regions, influence proton exchange membrane fuel cells behavior, efficiency, and water management. Using a robust mathematical model inspired by the COMSOL Multiphysics® fuel cell module, the study incorporates charge conservation, mass transport, species diffusion, electrochemical reaction kinetics, and water activity dynamics in the gas diffusion layers and polymer membrane. Key operating parameters, such as inlet relative humidity on both anode and cathode sides, as well as cell temperature, are varied to reflect the real-world climate data derived from NASA's global meteorological database. Ten representative African climate zones, including tropical rainforest, arid desert, temperate, and polar tundra, are mapped and parametrized based on long-term averages of temperature and humidity conditions. The simulations revealed notable performance disparities across climatic zones, with membrane hydration, water management efficiency, and voltage stability strongly influenced by ambient temperature and humidity. Hot and humid regions supported more favorable operating conditions, while arid and cold climates exhibited signs of membrane dehydration, uneven current distribution, and increased electrochemical losses. These results highlight the necessity of climate-specific design and operational strategies for proton exchange membrane fuel cells, especially in decentralized, off-grid applications across diverse African environments. By contextualizing PEMFC behavior within Africa’s climatic diversity, this study offers a robust framework for guiding the integration of hydrogen-based energy systems into the continent’s sustainable development agenda. It contributes to key objectives such as improving access to clean energy, enhancing system resilience, reducing greenhouse gas emissions, and supporting Sustainable Development Goal 7 (Affordable and Clean Energy). Moreover, the approach paves the way for climate-resilient fuel cell deployment, encouraging innovation in renewable energy solutions tailored to local environmental and socio-economic conditions.
{"title":"Multi-parameter simulation and comparative analysis of low-temperature proton exchange membrane fuel cell performance and electrode water management across different climatic zones in Africa","authors":"Pascalin Tiam Kapen","doi":"10.1016/j.jfueco.2025.100148","DOIUrl":"10.1016/j.jfueco.2025.100148","url":null,"abstract":"<div><div>In the pursuit of clean and efficient energy solutions tailored to Africa’s diverse environmental conditions, this study presents a multi-parameter simulation and comparative performance analysis of low-temperature proton exchange membrane fuel cells (PEMFC) across the main climatic zones of the African continent. The work addresses the critical challenge of how temperature and humidity variations, specific to different geographic regions, influence proton exchange membrane fuel cells behavior, efficiency, and water management. Using a robust mathematical model inspired by the COMSOL Multiphysics® fuel cell module, the study incorporates charge conservation, mass transport, species diffusion, electrochemical reaction kinetics, and water activity dynamics in the gas diffusion layers and polymer membrane. Key operating parameters, such as inlet relative humidity on both anode and cathode sides, as well as cell temperature, are varied to reflect the real-world climate data derived from NASA's global meteorological database. Ten representative African climate zones, including tropical rainforest, arid desert, temperate, and polar tundra, are mapped and parametrized based on long-term averages of temperature and humidity conditions. The simulations revealed notable performance disparities across climatic zones, with membrane hydration, water management efficiency, and voltage stability strongly influenced by ambient temperature and humidity. Hot and humid regions supported more favorable operating conditions, while arid and cold climates exhibited signs of membrane dehydration, uneven current distribution, and increased electrochemical losses. These results highlight the necessity of climate-specific design and operational strategies for proton exchange membrane fuel cells, especially in decentralized, off-grid applications across diverse African environments. By contextualizing PEMFC behavior within Africa’s climatic diversity, this study offers a robust framework for guiding the integration of hydrogen-based energy systems into the continent’s sustainable development agenda. It contributes to key objectives such as improving access to clean energy, enhancing system resilience, reducing greenhouse gas emissions, and supporting Sustainable Development Goal 7 (Affordable and Clean Energy). Moreover, the approach paves the way for climate-resilient fuel cell deployment, encouraging innovation in renewable energy solutions tailored to local environmental and socio-economic conditions.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"25 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To systematically rank fuel cells (FCs) based on their performance, this study utilizes the Analytic Hierarchy Process (AHP), a commonly used approach for multi-criteria decision-making. To assess the pros and cons of eight different FC types, we analyzed 21 parameters that affect FC functionality. With global weights of 0.155, 0.133, and 0.114, metal efficiency, durability/cycle life, and cost were the most important factors. According to the assessment, Proton Exchange Membrane Fuel Cells (PEMFCs) were the most promising, with a global weight of 0.186. The study further examined five different PEMFC options, employing a multi-index evaluation model that considered fifteen important factors. The most important factors here were Proton Conductivity, Activity, Water Management, and Fuel/Oxidant Purity, which were weighted at 0.186, 0.156, 0.129, and 0.106, respectively. According to the combined assessment, low-temperature PEMFCs (LT-PEMFCs) showed the best performance, with a total score of 0.298. These results emphasize that fuel cell performance could be improved by increasing utilization, and research into LT-PEMFCs appears to be a good way to achieve optimization.
{"title":"Optimizing fuel cell selection: An AHP-driven multi-criteria framework","authors":"Seyed Taher Kermani Alghorayshi , Ali Rezapouranghahfarokhi , Erfan Abolhasani , Masoud Dorfeshan , Milad Imandoust , Samaneh Ayoubi , Rahim Zahedi","doi":"10.1016/j.jfueco.2025.100153","DOIUrl":"10.1016/j.jfueco.2025.100153","url":null,"abstract":"<div><div>To systematically rank fuel cells (FCs) based on their performance, this study utilizes the Analytic Hierarchy Process (AHP), a commonly used approach for multi-criteria decision-making. To assess the pros and cons of eight different FC types, we analyzed 21 parameters that affect FC functionality. With global weights of 0.155, 0.133, and 0.114, metal efficiency, durability/cycle life, and cost were the most important factors. According to the assessment, Proton Exchange Membrane Fuel Cells (PEMFCs) were the most promising, with a global weight of 0.186. The study further examined five different PEMFC options, employing a multi-index evaluation model that considered fifteen important factors. The most important factors here were Proton Conductivity, Activity, Water Management, and Fuel/Oxidant Purity, which were weighted at 0.186, 0.156, 0.129, and 0.106, respectively. According to the combined assessment, low-temperature PEMFCs (LT-PEMFCs) showed the best performance, with a total score of 0.298. These results emphasize that fuel cell performance could be improved by increasing utilization, and research into LT-PEMFCs appears to be a good way to achieve optimization.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"25 ","pages":"Article 100153"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-09DOI: 10.1016/j.jfueco.2025.100149
Lhiam Paton , Sandra Kiesel , Jörg Feldmann
In the event of decommissioned oil and gas infrastructure being left in place the operators will have to guarantee that contaminant concentrations are as low as reasonably practicable. To achieve this for a persistent contaminant like mercury (Hg), there are several aspects which must be well understood. Including concentrations of Hg present on infrastructure like pipelines, the species present, how to assess the risk associated with each compound and which analytical methods are available to achieve these knowledge targets. The work displayed in this article aims to shed light on the first two points, specifically, when pipelines have been kept free of corrosion and when exposed to hydrogen sulphide (H2S) over a long term. Here, it was identified that the kinetics of Hg uptake onto carbon steel resulted in high Hg accumulation on the timescale of months and years with total Hg levels being as high as 0.8 g Hg∙m-2 after 36 months of exposure to elemental mercury (Hg0). Across a 5-month period the impact of H2S on Hg species was investigated finding that the presence of H2S reduced the fraction of labile Hg species which were most likely to enter the marine environment. Nevertheless, even after co-exposure of Hg0 and H2S, 15 % of Hg was mobilised with seawater and was, therefore, potentially bioavailable. This study holds critical information for future risk assessments, particularly of dry gas pipelines, by showing that Hg will accumulate on polished steel surfaces and that a significant fraction of the total may be available to local marine environments.
如果退役的石油和天然气基础设施被留在原地，运营商必须保证污染物浓度尽可能低。要对汞（Hg）这样的持久性污染物实现这一目标，必须充分了解几个方面。包括管道等基础设施中汞的浓度，汞的种类，如何评估每种化合物的风险以及有哪些分析方法可以实现这些知识目标。本文展示的工作旨在阐明前两点，特别是当管道处于无腐蚀状态以及长期暴露于硫化氢（H2S）中时。本研究发现，在数月和数年的时间尺度上，碳钢对汞的吸收动力学导致汞的高积累，暴露于单质汞（Hg0） 36个月后，总汞水平高达0.8 g Hg∙m-2。在5个月的时间里，研究人员对H2S对汞物种的影响进行了研究，发现H2S的存在减少了最有可能进入海洋环境的不稳定汞物种的比例。然而，即使在Hg0和H2S共同暴露后，仍有15%的汞被海水调动，因此具有潜在的生物可利用性。这项研究为未来的风险评估提供了关键信息，特别是对干气管道的风险评估，因为它表明汞会积聚在抛光的钢铁表面上，而且总量的很大一部分可能会进入当地的海洋环境。
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Pub Date : 2025-12-01Epub Date: 2025-11-27DOI: 10.1016/j.jfueco.2025.100151
Eva-Maria Schomakers, Wiktoria Wilkowska, Martina Ziefle
This study examines public information needs and the role of information and perceived knowledge in shaping the acceptance of solar fuels produced through artificial photosynthesis. Using a mixed-method approach that includes qualitative interviews and a quasi-experimental online survey, we identify specific information needs and assess the influence of information on solar fuel acceptance using structural equation modeling. Our findings reveal that richer informational content significantly enhances perceived knowledge. In turn, this fosters more positive affective and cognitive evaluations. Although information shows no direct effect on societal perceptions and acceptance, its significant indirect effect through perceived knowledge on perceptions and acceptance underscores its importance. Our findings contribute to an understanding of which information is prioritized regarding solar fuels by the public and how feelings of knowledgeability enhance positive perceptions. These insights provide clear recommendations for tailored communication strategies for solar fuels and related sustainable innovations.
{"title":"Information needs and the effect of information on the social acceptance of innovative solar fuels","authors":"Eva-Maria Schomakers, Wiktoria Wilkowska, Martina Ziefle","doi":"10.1016/j.jfueco.2025.100151","DOIUrl":"10.1016/j.jfueco.2025.100151","url":null,"abstract":"<div><div>This study examines public information needs and the role of information and perceived knowledge in shaping the acceptance of solar fuels produced through artificial photosynthesis. Using a mixed-method approach that includes qualitative interviews and a quasi-experimental online survey, we identify specific information needs and assess the influence of information on solar fuel acceptance using structural equation modeling. Our findings reveal that richer informational content significantly enhances perceived knowledge. In turn, this fosters more positive affective and cognitive evaluations. Although information shows no direct effect on societal perceptions and acceptance, its significant indirect effect through perceived knowledge on perceptions and acceptance underscores its importance. Our findings contribute to an understanding of which information is prioritized regarding solar fuels by the public and how feelings of knowledgeability enhance positive perceptions. These insights provide clear recommendations for tailored communication strategies for solar fuels and related sustainable innovations.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"25 ","pages":"Article 100151"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-06-23DOI: 10.1016/j.jfueco.2025.100144
Mohammad Hossein Gholizadeh, Hossein Yousefi, Ahmad Hajinezhad, Mahmood Abdoos
The present research work is related to the optimization of a hybrid renewable energy system, combining Waste-to-Energy (WTE) and Photovoltaic (PV) technologies for hydrogen production by means of water electrolysis in both on-grid and off-grid operation modes. A WTE plant of 3 MW rated capacity is combined with a PV array of capacity varying from 0.5 to 3 MW. The Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Gradient Descent, and Newton's Method algorithms were used to minimize Levelized Cost of Hydrogen (LCOH) while ensuring energy reliability. In the on-grid scenario, the minimum LCOH of around -399.215 $/kg was achieved by PSO, GA, and SA, which indicates cost-effectiveness with the help of grid exportation and importation. Whereas, in the off-grid case, LCOH values are higher: the minimum value of LCOH by PSO, GA, and SA was 34.81 $/kg, while the highest was obtained from Gradient Descent with 42.85 $/kg. The main problems that the configuration faced in an off-grid setting were related to not being able to satisfy energy demand and increased curtailment rates. These findings evidence the economic advantages of on-grid systems and underline the necessity for additional measures in off-grid setups, such as energy storage, to reach higher performance and reliability.
{"title":"Optimization of the economic-technical model for hydrogen production with an approach to utilizing solar power plants and waste-to-energy conversion","authors":"Mohammad Hossein Gholizadeh, Hossein Yousefi, Ahmad Hajinezhad, Mahmood Abdoos","doi":"10.1016/j.jfueco.2025.100144","DOIUrl":"10.1016/j.jfueco.2025.100144","url":null,"abstract":"<div><div>The present research work is related to the optimization of a hybrid renewable energy system, combining Waste-to-Energy (WTE) and Photovoltaic (PV) technologies for hydrogen production by means of water electrolysis in both on-grid and off-grid operation modes. A WTE plant of 3 MW rated capacity is combined with a PV array of capacity varying from 0.5 to 3 MW. The Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Gradient Descent, and Newton's Method algorithms were used to minimize Levelized Cost of Hydrogen (LCOH) while ensuring energy reliability. In the on-grid scenario, the minimum LCOH of around -399.215 $/kg was achieved by PSO, GA, and SA, which indicates cost-effectiveness with the help of grid exportation and importation. Whereas, in the off-grid case, LCOH values are higher: the minimum value of LCOH by PSO, GA, and SA was 34.81 $/kg, while the highest was obtained from Gradient Descent with 42.85 $/kg. The main problems that the configuration faced in an off-grid setting were related to not being able to satisfy energy demand and increased curtailment rates. These findings evidence the economic advantages of on-grid systems and underline the necessity for additional measures in off-grid setups, such as energy storage, to reach higher performance and reliability.</div></div>","PeriodicalId":100556,"journal":{"name":"Fuel Communications","volume":"24 ","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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