This study presents the modeling, design, and simulation of a DC-DC power processing circuit for building-attached photovoltaic (BAPV) systems. With the growing integration of solar energy into urban infrastructure, efficient power conversion becomes essential for maximizing energy yield and ensuring reliable operation. The converter topology features maximum power point tracking (MPPT) using the incremental conductance (IC) algorithm combined with a proportional-integral (PI) controller. This design addresses the dynamic irradiance and partial shading conditions that are common in building-mounted PV modules. The comprehensive model integrates solar irradiance profiles, PV module characteristics, and converter control strategies and is implemented in MATLAB/Simulink for performance evaluation. Simulation results show that the system maintains a regulated output voltage of 48 ± 0.4 V across varying irradiance levels, with a voltage ripple limited to 1–3% of the output voltage. The findings demonstrate the circuit’s capability to enhance energy yield, improve operational reliability, and support the development of smart, sustainable urban energy systems.
{"title":"Modeling and simulation-based performance study of a DC-DC power processing circuit for building-attached photovoltaic systems","authors":"Swarna Jyoti Saharia , Asim Datta , Sadhan Mahapatra","doi":"10.1016/j.nxener.2025.100446","DOIUrl":"10.1016/j.nxener.2025.100446","url":null,"abstract":"<div><div>This study presents the modeling, design, and simulation of a DC-DC power processing circuit for building-attached photovoltaic (BAPV) systems. With the growing integration of solar energy into urban infrastructure, efficient power conversion becomes essential for maximizing energy yield and ensuring reliable operation. The converter topology features maximum power point tracking (MPPT) using the incremental conductance (IC) algorithm combined with a proportional-integral (PI) controller. This design addresses the dynamic irradiance and partial shading conditions that are common in building-mounted PV modules. The comprehensive model integrates solar irradiance profiles, PV module characteristics, and converter control strategies and is implemented in MATLAB/Simulink for performance evaluation. Simulation results show that the system maintains a regulated output voltage of 48 ± 0.4 V across varying irradiance levels, with a voltage ripple limited to 1–3% of the output voltage. The findings demonstrate the circuit’s capability to enhance energy yield, improve operational reliability, and support the development of smart, sustainable urban energy systems.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100446"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265008","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 : 2025-10-01Epub Date: 2025-10-15DOI: 10.1016/j.nxener.2025.100461
Cássio Almeida , Paloma Jackson , Rafael Vicentini , Eric L. Pereira , Erick Santos , Leonardo Morais Da Silva , Davi M. Soares , Hudson Zanin
Pursuing pseudocapacitive materials with higher energy densities for future electrochemical energy storage systems requires a comprehensive understanding of material and electrochemical properties. In addition to charge-storage mechanisms in the active material, the electrolyte medium plays an important role in energy density. Organic solvent electrolytes exhibit a wider operating voltage window in comparison to aqueous-based electrolytes, yet the investigation of pseudocapacitive active materials in supercapacitor electrodes remains underexplored. Here, we report a facile and scalable synthesis of the pseudocapacitive composite material NiO-activated carbon (AC) as a supercapacitor electrode. A comprehensive electrochemical study in the organic solvent medium is presented, elucidating the pseudocapacitive properties of NiO-AC, assessing the stable working voltage window in an organic solvent medium, and investigating ion dynamics during charge via operando Raman. Using electrochemical characterization techniques, such as single-step chronoamperometry (SSC), and the in-situ Raman results we showed that the synthesized material (NiO-AC) is stable for operation at 2.6 V. NiO-AC, presenting specific power of 23.7 kW kg−1 and specific energy of 21.4 W h kg−1, with a capacitance increase due to the contribution of the NiO species, highlighting the potential of the study of pseudocapacitive materials in organic electrolyte systems.
为未来的电化学储能系统寻求具有更高能量密度的赝电容材料需要对材料和电化学特性有全面的了解。除了活性材料中的电荷存储机制外，电解质介质在能量密度中起着重要作用。与水基电解质相比，有机溶剂电解质具有更宽的工作电压窗口，但对超级电容器电极中假电容活性材料的研究仍未得到充分探索。在这里，我们报告了一种简单且可扩展的假电容复合材料nio -活性炭（AC）作为超级电容器电极的合成。在有机溶剂介质中进行了全面的电化学研究，阐明了NiO-AC的赝电容特性，评估了有机溶剂介质中的稳定工作电压窗，并通过operando Raman研究了充电过程中的离子动力学。利用电化学表征技术，如单步计时安培法（SSC）和原位拉曼结果，我们表明合成材料（NiO-AC）在2.6 V下稳定运行。NiO- ac的比功率为23.7 kW kg−1，比能量为21.4 W h kg−1，由于NiO物质的贡献，电容增加，突出了有机电解质体系中赝电容材料研究的潜力。
{"title":"Charge and energy storage properties of NiO-AC composites in organic electrolyte using operando Raman and distributed capacitance analyses in the time domain","authors":"Cássio Almeida , Paloma Jackson , Rafael Vicentini , Eric L. Pereira , Erick Santos , Leonardo Morais Da Silva , Davi M. Soares , Hudson Zanin","doi":"10.1016/j.nxener.2025.100461","DOIUrl":"10.1016/j.nxener.2025.100461","url":null,"abstract":"<div><div>Pursuing pseudocapacitive materials with higher energy densities for future electrochemical energy storage systems requires a comprehensive understanding of material and electrochemical properties. In addition to charge-storage mechanisms in the active material, the electrolyte medium plays an important role in energy density. Organic solvent electrolytes exhibit a wider operating voltage window in comparison to aqueous-based electrolytes, yet the investigation of pseudocapacitive active materials in supercapacitor electrodes remains underexplored. Here, we report a facile and scalable synthesis of the pseudocapacitive composite material NiO-activated carbon (AC) as a supercapacitor electrode. A comprehensive electrochemical study in the organic solvent medium is presented, elucidating the pseudocapacitive properties of NiO-AC, assessing the stable working voltage window in an organic solvent medium, and investigating ion dynamics during charge via operando Raman. Using electrochemical characterization techniques, such as single-step chronoamperometry (SSC), and the in-situ Raman results we showed that the synthesized material (NiO-AC) is stable for operation at 2.6 V. NiO-AC, presenting specific power of 23.7 kW kg<sup>−1</sup> and specific energy of 21.4 W h kg<sup>−1</sup>, with a capacitance increase due to the contribution of the NiO species, highlighting the potential of the study of pseudocapacitive materials in organic electrolyte systems.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100461"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332208","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 : 2025-10-01Epub Date: 2025-10-17DOI: 10.1016/j.nxener.2025.100465
Yong-Ming Dai , Yu-Chieh Ting , Chia Ming Chang , Chien-Tzu Huang
Lithium-ion batteries face critical thermal management challenges during fast-charging operations, where inadequate cooling can lead to thermal runaway and safety hazards. Current research is limited by expensive commercial computational fluid dynamic (CFD) software that restricts access to advanced thermal simulation capabilities, particularly hindering researchers in developing countries and educational institutions. This study addresses these challenges by employing the open-source FiPy platform to develop a comprehensive 3-dimensional thermal model for lithium-ion battery packs. The numerical analysis systematically investigates 3 cooling modes (natural, forced, and liquid convection with h = 10, 50, and 250 W/m²·K) and 3 thermal interface materials called TIMs (k = 0.026, 0.5, and 4.0 W/m·K). Results demonstrate that liquid convection achieves superior thermal control with temperature rises below 3.2 °C, while natural convection results in a significant temperature rise of 30.7 °C. TIMs significantly enhance heat dissipation, with moderate-conductivity TIM reducing temperature rises by 34%. Critical safety analysis reveals that 5 C fast charging under inadequate cooling results in catastrophic temperatures exceeding 200 °C. By utilizing the free FiPy framework and sharing all codes on GitHub, this research democratizes access to battery thermal simulation capabilities, enabling cost-effective analysis worldwide and accelerating innovation in thermal management systems.
{"title":"Thermal management analysis of fast-charging lithium-ion battery packs: Effects of cooling strategies","authors":"Yong-Ming Dai , Yu-Chieh Ting , Chia Ming Chang , Chien-Tzu Huang","doi":"10.1016/j.nxener.2025.100465","DOIUrl":"10.1016/j.nxener.2025.100465","url":null,"abstract":"<div><div>Lithium-ion batteries face critical thermal management challenges during fast-charging operations, where inadequate cooling can lead to thermal runaway and safety hazards. Current research is limited by expensive commercial computational fluid dynamic (CFD) software that restricts access to advanced thermal simulation capabilities, particularly hindering researchers in developing countries and educational institutions. This study addresses these challenges by employing the open-source FiPy platform to develop a comprehensive 3-dimensional thermal model for lithium-ion battery packs. The numerical analysis systematically investigates 3 cooling modes (natural, forced, and liquid convection with h = 10, 50, and 250 W/m²·K) and 3 thermal interface materials called TIMs (k = 0.026, 0.5, and 4.0 W/m·K). Results demonstrate that liquid convection achieves superior thermal control with temperature rises below 3.2 °C, while natural convection results in a significant temperature rise of 30.7 °C. TIMs significantly enhance heat dissipation, with moderate-conductivity TIM reducing temperature rises by 34%. Critical safety analysis reveals that 5 C fast charging under inadequate cooling results in catastrophic temperatures exceeding 200 °C. By utilizing the free FiPy framework and sharing all codes on GitHub, this research democratizes access to battery thermal simulation capabilities, enabling cost-effective analysis worldwide and accelerating innovation in thermal management systems.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100465"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332200","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 : 2025-10-01Epub Date: 2025-07-31DOI: 10.1016/j.nxener.2025.100383
Aditya Kolakoti
This study investigates experimental and artificial intelligence-based predictions of heterogeneous combustion performance in a diesel engine fueled with neat biodiesel. The combustion aspects, including cylinder pressures, heat energy developed and released, mass burnt fractions (MBF), mean gas temperatures (MGT), and the influence of combustion temperatures on NOx formation, are examined experimentally. The combustion results are trained in a feed-forward artificial neural network (ANN) algorithm for the predictions, and an error histogram with 20 bins helps identify the accuracy of the trained model. The prediction results of combustion parameters are recorded quite accurately for most instances, as the errors are centered around 0. The overall accuracy of the trained model is achieved with a high correlation coefficient (R = 0.99) and a low mean square error (MSE). In addition, the influence of combustion temperature on NOx emissions is highlighted, and a correlation is developed with errors of 2.22% and 1.96% at 75% and 100% loads, respectively. Finally, biodiesel exhibits controlled diffusion combustion, achieving more sustained combustion, with 6.19% and 6.18% lower NOx formation compared to diesel fuel at 75% and 100% loads.
{"title":"Optimizing diesel engine heterogeneous combustion performance and NOx emissions: A next energy perspective with AI","authors":"Aditya Kolakoti","doi":"10.1016/j.nxener.2025.100383","DOIUrl":"10.1016/j.nxener.2025.100383","url":null,"abstract":"<div><div>This study investigates experimental and artificial intelligence-based predictions of heterogeneous combustion performance in a diesel engine fueled with neat biodiesel. The combustion aspects, including cylinder pressures, heat energy developed and released, mass burnt fractions (MBF), mean gas temperatures (MGT), and the influence of combustion temperatures on NOx formation, are examined experimentally. The combustion results are trained in a feed-forward artificial neural network (ANN) algorithm for the predictions, and an error histogram with 20 bins helps identify the accuracy of the trained model. The prediction results of combustion parameters are recorded quite accurately for most instances, as the errors are centered around 0. The overall accuracy of the trained model is achieved with a high correlation coefficient (R = 0.99) and a low mean square error (MSE). In addition, the influence of combustion temperature on NO<sub>x</sub> emissions is highlighted, and a correlation is developed with errors of 2.22% and 1.96% at 75% and 100% loads, respectively. Finally, biodiesel exhibits controlled diffusion combustion, achieving more sustained combustion, with 6.19% and 6.18% lower NO<sub>x</sub> formation compared to diesel fuel at 75% and 100% loads.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100383"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144737989","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 : 2025-10-01Epub Date: 2025-07-28DOI: 10.1016/j.nxener.2025.100380
Congyu Zhang, Jiaqi Ma, Yuting Wang, Kuifeng Hao
The investigation of microwave torrefaction for solid biofuel production is significant for biomass waste conversion and environmental sustainability. In this study, a comprehensive analysis of microwave torrefied biochar fuel property and life cycle assessment is employed. The Chinese medicine residue is selected as the feedstock for biochar preparation, and its fuel property and environmental impact are evaluated. The obtained results suggest that with the increasing torrefaction severity, the fuel performance gradually becomes better. Concerning the proximate analysis, the values of volatile matter, fixed carbon, moisture, and ash content are 57.93–81.23%, 13.77–35.59%, 1.65–2.36%, 2.64–4.83%, respectively. A severer torrefaction condition would arise a better decarbonization and deoxygenation effect. Good linear relationships are obtained between torrefaction severity index (TSI) and carbonization index and TSI and deoxygenation index, with the correlation coefficient of 0.8683 and 0.8600. The life cycle assessment (LCA) result indicates that microwave torrefaction process would arise the environmental impact on greenhouse gas (GHG) emission, human toxicity, ionizing radiation, land use, and water environment pollution. Specifically, over 20% improvement in heating value and reduction in GHG emissions are achieved via microwave torrefaction process. However, lab-scale microwave torrefaction (10 g/batch) with gate-to-gate LCA shows 20% GHG reduction but excludes full-scale impacts. Totally, the obtained results are helpful for the cognition of fuel property variation and environmental impact of the Chinese medicine residue conversion and solid biofuel production, and thus for better waste-to-energy process to achieve biowastes valorization.
{"title":"Microwave torrefaction of biomass waste: Fuel property evaluation and life cycle impact","authors":"Congyu Zhang, Jiaqi Ma, Yuting Wang, Kuifeng Hao","doi":"10.1016/j.nxener.2025.100380","DOIUrl":"10.1016/j.nxener.2025.100380","url":null,"abstract":"<div><div>The investigation of microwave torrefaction for solid biofuel production is significant for biomass waste conversion and environmental sustainability. In this study, a comprehensive analysis of microwave torrefied biochar fuel property and life cycle assessment is employed. The Chinese medicine residue is selected as the feedstock for biochar preparation, and its fuel property and environmental impact are evaluated. The obtained results suggest that with the increasing torrefaction severity, the fuel performance gradually becomes better. Concerning the proximate analysis, the values of volatile matter, fixed carbon, moisture, and ash content are 57.93–81.23%, 13.77–35.59%, 1.65–2.36%, 2.64–4.83%, respectively. A severer torrefaction condition would arise a better decarbonization and deoxygenation effect. Good linear relationships are obtained between torrefaction severity index (TSI) and carbonization index and TSI and deoxygenation index, with the correlation coefficient of 0.8683 and 0.8600. The life cycle assessment (LCA) result indicates that microwave torrefaction process would arise the environmental impact on greenhouse gas (GHG) emission, human toxicity, ionizing radiation, land use, and water environment pollution. Specifically, over 20% improvement in heating value and reduction in GHG emissions are achieved via microwave torrefaction process. However, lab-scale microwave torrefaction (10 g/batch) with gate-to-gate LCA shows 20% GHG reduction but excludes full-scale impacts. Totally, the obtained results are helpful for the cognition of fuel property variation and environmental impact of the Chinese medicine residue conversion and solid biofuel production, and thus for better waste-to-energy process to achieve biowastes valorization.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100380"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721331","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 : 2025-10-01Epub Date: 2025-09-16DOI: 10.1016/j.nxener.2025.100428
Nour El Haq El Macouti , Mohamed El bouanounou , Abdelmajid Assila , El-Kebir Hlil , Yahia Boughaleb , Abdelowahed Hajjaji , Said Laasri
Next-generation lithium- and sodium-ion battery development relies on solid-state electrolytes, offering enhanced safety, thermal stability, and high energy density. This research uses molecular dynamics (MD) simulations and machine learning (ML) to study ion diffusion in LiFePO₄, Li₇La₃Zr₂O₁₂ (LLZO), and Na₃Zr₂Si₂PO₁₂ (NASICON). MD simulations calculated 300 K diffusion coefficients (D) of 9.18 × 10⁻¹¹ m²/s for LiFePO₄, 4.00 × 10⁻¹² m²/s for LLZO, and 6.77 × 10⁻¹¹ m²/s for NASICON, with activation energies of 0.34 eV, 0.35 eV, and 0.31 eV, aligning with experimental ranges, though validation is limited and less accurate for LLZO due to a 2-order magnitude deviation. The ML model, trained on OBELiX data with temperature augmentation, systematically underpredicts diffusion coefficients (e.g., 3.84 × 10⁻¹¹ m²/s for LiFePO₄ vs. 9.18 × 10⁻¹¹ m²/s MD), likely due to overestimated ion densities. Despite a high R² of 0.996, the model indicates opportunities for further refinement. Our comparative evaluation demonstrates that sodium ion movement through NASICON frameworks exhibits similar characteristics to lithium-ion mobility within both olivine and garnet crystal structures. Our research results expand the current understanding of ion mobility pathways and provide numerical reference points that can guide future material refinement approaches and data-driven computational design of advanced solid electrolyte battery technologies.
{"title":"Lithium and sodium ion diffusion in LiFePO₄, LLZO, and NASICON: A molecular dynamics and machine learning study","authors":"Nour El Haq El Macouti , Mohamed El bouanounou , Abdelmajid Assila , El-Kebir Hlil , Yahia Boughaleb , Abdelowahed Hajjaji , Said Laasri","doi":"10.1016/j.nxener.2025.100428","DOIUrl":"10.1016/j.nxener.2025.100428","url":null,"abstract":"<div><div>Next-generation lithium- and sodium-ion battery development relies on solid-state electrolytes, offering enhanced safety, thermal stability, and high energy density. This research uses molecular dynamics (MD) simulations and machine learning (ML) to study ion diffusion in LiFePO₄, Li₇La₃Zr₂O₁₂ (LLZO), and Na₃Zr₂Si₂PO₁₂ (NASICON). MD simulations calculated 300 K diffusion coefficients (D) of 9.18 × 10⁻¹¹ m²/s for LiFePO₄, 4.00 × 10⁻¹² m²/s for LLZO, and 6.77 × 10⁻¹¹ m²/s for NASICON, with activation energies of 0.34 eV, 0.35 eV, and 0.31 eV, aligning with experimental ranges, though validation is limited and less accurate for LLZO due to a 2-order magnitude deviation. The ML model, trained on OBELiX data with temperature augmentation, systematically underpredicts diffusion coefficients (e.g., 3.84 × 10⁻¹¹ m²/s for LiFePO₄ vs. 9.18 × 10⁻¹¹ m²/s MD), likely due to overestimated ion densities. Despite a high R² of 0.996, the model indicates opportunities for further refinement. Our comparative evaluation demonstrates that sodium ion movement through NASICON frameworks exhibits similar characteristics to lithium-ion mobility within both olivine and garnet crystal structures. Our research results expand the current understanding of ion mobility pathways and provide numerical reference points that can guide future material refinement approaches and data-driven computational design of advanced solid electrolyte battery technologies.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100428"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104905","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 : 2025-10-01Epub Date: 2025-09-17DOI: 10.1016/j.nxener.2025.100420
Julie Baruah , Upasana Medhi , Bikash K. Nath , Ramesh C. Deka , Eeshan Kalita
The HMF or 5-hydroxymethylfurural is a crucial platform chemical classified as a "drop-in biofuel." HMF synthesis procedures have experienced notable advancements in recent years, including the shift from homogeneous to heterogeneous catalysts, the substitution of aqueous solutions with organic phases, and the adoption of biphasic systems to mitigate limitations caused by side reactions, among other innovations. Nonetheless, achieving a balance among selectivity, cost, energy consumption, and environmental impact in the production of HMF from economical glucose-derived substrates presents a formidable challenge. Various strategies have been developed over the past decade to address these issues. This review provides a current overview of recent advancements in solvent types and heterogeneous catalysts, including zeolites, metal oxides, carbonaceous and silica-based materials, heteropolyacids, and polymer-based systems. In addition, the reaction mechanisms of established solid catalysts employed to enhance HMF production are detailed.
{"title":"Enhancements in the production of 5-HMF from glucose: A review on recent advances in heterogeneous catalysts and solvent effects","authors":"Julie Baruah , Upasana Medhi , Bikash K. Nath , Ramesh C. Deka , Eeshan Kalita","doi":"10.1016/j.nxener.2025.100420","DOIUrl":"10.1016/j.nxener.2025.100420","url":null,"abstract":"<div><div>The HMF or 5-hydroxymethylfurural is a crucial platform chemical classified as a \"drop-in biofuel.\" HMF synthesis procedures have experienced notable advancements in recent years, including the shift from homogeneous to heterogeneous catalysts, the substitution of aqueous solutions with organic phases, and the adoption of biphasic systems to mitigate limitations caused by side reactions, among other innovations. Nonetheless, achieving a balance among selectivity, cost, energy consumption, and environmental impact in the production of HMF from economical glucose-derived substrates presents a formidable challenge. Various strategies have been developed over the past decade to address these issues. This review provides a current overview of recent advancements in solvent types and heterogeneous catalysts, including zeolites, metal oxides, carbonaceous and silica-based materials, heteropolyacids, and polymer-based systems. In addition, the reaction mechanisms of established solid catalysts employed to enhance HMF production are detailed.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100420"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104909","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 : 2025-10-01Epub Date: 2025-09-25DOI: 10.1016/j.nxener.2025.100430
Toyese Oyegoke , Abdullahi Jibrin
As the demand for alternative and renewable energy solutions increases, particularly in developing nations facing unreliable power supply, optimizing biomass gasification processes for power generation has become a critical challenge. Syngas, composed primarily of carbon monoxide (CO), hydrogen (H₂), and carbon dioxide (CO₂), plays a pivotal role in driving gas turbine power generation. However, the impact of varying feedstock types, thermodynamic conditions, and syngas quality on power output is still not well understood. This study addresses this knowledge gap by investigating the effects of feedstock composition (C1 to C4 alkanes), temperature, and pressure on syngas production and gas turbine efficiency. Using process simulations with DWSim and optimization techniques such as response surface methodology (RSM), we identify optimal syngas compositions for maximizing gas turbine duty (GTD). The results demonstrate that a balanced syngas mixture (CO = 4 kmol/h, H₂ = 4 kmol/h, CO₂ = 4 kmol/h) yields a GTD of 48.2 kW, significantly enhancing power generation efficiency. Our findings underscore the critical role of CO₂ in stabilizing combustion, improving thermal efficiency, and ensuring stable turbine operation, while CO and H₂ contribute directly to the energy conversion process. This research provides valuable insights for optimizing bioenergy systems, offering predictive models that can guide the development of more efficient and sustainable biomass-based power generation technologies.
{"title":"Optimizing syngas production for enhanced gas turbine power generation: A thermodynamic and feedstock analysis","authors":"Toyese Oyegoke , Abdullahi Jibrin","doi":"10.1016/j.nxener.2025.100430","DOIUrl":"10.1016/j.nxener.2025.100430","url":null,"abstract":"<div><div>As the demand for alternative and renewable energy solutions increases, particularly in developing nations facing unreliable power supply, optimizing biomass gasification processes for power generation has become a critical challenge. Syngas, composed primarily of carbon monoxide (CO), hydrogen (H₂), and carbon dioxide (CO₂), plays a pivotal role in driving gas turbine power generation. However, the impact of varying feedstock types, thermodynamic conditions, and syngas quality on power output is still not well understood. This study addresses this knowledge gap by investigating the effects of feedstock composition (C1 to C4 alkanes), temperature, and pressure on syngas production and gas turbine efficiency. Using process simulations with DWSim and optimization techniques such as response surface methodology (RSM), we identify optimal syngas compositions for maximizing gas turbine duty (GTD). The results demonstrate that a balanced syngas mixture (CO = 4 kmol/h, H₂ = 4 kmol/h, CO₂ = 4 kmol/h) yields a GTD of 48.2 kW, significantly enhancing power generation efficiency. Our findings underscore the critical role of CO₂ in stabilizing combustion, improving thermal efficiency, and ensuring stable turbine operation, while CO and H₂ contribute directly to the energy conversion process. This research provides valuable insights for optimizing bioenergy systems, offering predictive models that can guide the development of more efficient and sustainable biomass-based power generation technologies.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100430"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157975","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 : 2025-10-01Epub Date: 2025-09-16DOI: 10.1016/j.nxener.2025.100419
Rima Mesaud, Fatima Boui, Peter Dannenmann, Birgit Scheppat, Edeltraud Gehrig
Modeling and prediction of fuel cell dynamics is a challenging task and has recently gained importance. However, the underlying physical processes are often complex, and the dynamics is determined by a large number of parameters that are not completely known. We present results of a model based on dynamic mode decomposition (DMD) for proton exchange membrane fuel cells (PEMFC). Our simulation results show that the proposed prognostic strategy on the basis of DMD allows both confirmation of experimental observations and prediction of future behavior. In particular, the transition to a regime characterized by degradation can be monitored and recognized in advance.
{"title":"Dynamic mode decomposition for modeling the UI dependence in fuel cells","authors":"Rima Mesaud, Fatima Boui, Peter Dannenmann, Birgit Scheppat, Edeltraud Gehrig","doi":"10.1016/j.nxener.2025.100419","DOIUrl":"10.1016/j.nxener.2025.100419","url":null,"abstract":"<div><div>Modeling and prediction of fuel cell dynamics is a challenging task and has recently gained importance. However, the underlying physical processes are often complex, and the dynamics is determined by a large number of parameters that are not completely known. We present results of a model based on dynamic mode decomposition (DMD) for proton exchange membrane fuel cells (PEMFC). Our simulation results show that the proposed prognostic strategy on the basis of DMD allows both confirmation of experimental observations and prediction of future behavior. In particular, the transition to a regime characterized by degradation can be monitored and recognized in advance.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100419"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104906","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 : 2025-10-01Epub Date: 2025-10-15DOI: 10.1016/j.nxener.2025.100455
A. Hakim, S.P. Chew, T. Azfar, L.S. Supian, A.S. Mokhtar
Photovoltaic (PV) panels are widely used to harvest and convert sunlight (light energy) into electricity and provide electrical energy for a variety of electric applications. A lot of research has been done on these PV solar panels to ensure their maximum electricity generation in an ecofriendly way. Excessive heat buildup can lead to a drop in PV panel efficiency, which results in loss of power output and performance. Traditional cooling techniques, like air and water cooling, are not practical, sustainable, and efficient. In particular, the effectiveness of BIO-PCMs on PV efficiency still needs clarification. This study minimizes that limitation through PVB, which is employed for the thermal management of PV panels in the form of plant-based phase change material (PCM). The Co-PCM is an amalgamation of Cocos nucifera oil and paraffin wax; the thermal conductivity property was evaluated using KD2 Pro thermal analyzer. The main purpose was to evaluate how the CO-PCM affects temperature variations on the PV panel. Results showed that incorporation of the Co-PCM yielded a significant temperature reduction of around 11.4 ℃ on the back side of the PV panel at a 5 mm PCM thickness. Moreover, the experiments showed that the average power density output of the PV panel increased by 51.21 mW/℃ and the overall power efficiency of the PV panel also improved by 12.82% compared to the PV panel without PCM.
光伏（PV）板被广泛用于收集太阳光（光能）并将其转化为电能，为各种电气应用提供电能。人们对这些光伏太阳能电池板进行了大量的研究，以确保它们以一种环保的方式最大限度地发电。过多的热量积累会导致光伏面板效率下降，从而导致功率输出和性能的损失。传统的冷却技术，如空气和水冷却，是不实用的，可持续的，高效的。特别是，BIO-PCMs对光伏效率的影响仍有待澄清。本研究通过PVB最大限度地减少了这一限制，PVB以植物基相变材料（PCM）的形式用于光伏板的热管理。Co-PCM是椰子油和石蜡的混合物；采用KD2 Pro热分析仪对其导热性能进行评价。主要目的是评估CO-PCM如何影响PV面板上的温度变化。结果表明，Co-PCM的掺入使PV板背面在5 mm PCM厚度处的温度显著降低了11.4℃左右。实验结果表明，与未加PCM的光伏板相比，光伏板的平均功率密度输出提高了51.21 mW/℃，整体功率效率提高了12.82%。
{"title":"Experimental investigation to enhance photovoltaic efficiency using coconut oil-infused phase change material as heat sink","authors":"A. Hakim, S.P. Chew, T. Azfar, L.S. Supian, A.S. Mokhtar","doi":"10.1016/j.nxener.2025.100455","DOIUrl":"10.1016/j.nxener.2025.100455","url":null,"abstract":"<div><div>Photovoltaic (PV) panels are widely used to harvest and convert sunlight (light energy) into electricity and provide electrical energy for a variety of electric applications. A lot of research has been done on these PV solar panels to ensure their maximum electricity generation in an ecofriendly way. Excessive heat buildup can lead to a drop in PV panel efficiency, which results in loss of power output and performance. Traditional cooling techniques, like air and water cooling, are not practical, sustainable, and efficient. In particular, the effectiveness of BIO-PCMs on PV efficiency still needs clarification. This study minimizes that limitation through PVB, which is employed for the thermal management of PV panels in the form of plant-based phase change material (PCM). The Co-PCM is an amalgamation of Cocos nucifera oil and paraffin wax; the thermal conductivity property was evaluated using KD2 Pro thermal analyzer. The main purpose was to evaluate how the CO-PCM affects temperature variations on the PV panel. Results showed that incorporation of the Co-PCM yielded a significant temperature reduction of around 11.4<!--> <!-->℃ on the back side of the PV panel at a 5 mm PCM thickness. Moreover, the experiments showed that the average power density output of the PV panel increased by 51.21 mW/℃ and the overall power efficiency of the PV panel also improved by 12.82% compared to the PV panel without PCM.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100455"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332205","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号