Pub Date : 2025-11-11DOI: 10.1016/j.clet.2025.101114
Hadi Kamfar , Abolfazl Shojaeian , Jaber Yousefi Seyf , Najmeh Hajialigol , Hadi Delavari
This study presents a comprehensive thermodynamic investigation based on energy, exergy, and economic (3 E) analysis of eight Organic Flash Cycle (OFC) configurations for waste heat recovery. The modified cycles were modeled in MATLAB with thermophysical properties obtained from REFPROP 9.0. The proposed configurations integrate advanced components such as two-phase expanders and ejectors to minimize throttling losses and improve overall system performance. Unlike the dual-ejector systems reported by Chen et al. (2019), one of the proposed configurations, namely Two-phase expander and single ejector OFC-II (TPSEOFC-II) eliminates the secondary flash separator, resulting in a 21.5 % reduction in total costs and a 37.25 % improvement in exergy efficiency. Multi-objective optimization using the Multi-Objective Grey Wolf Optimizer was employed to simultaneously maximize energy efficiency and exergy efficiency while minimizing the levelized cost of energy (LCOE). The TPSEOFC-II configuration achieved a net power output of 363.19 kW, an energy efficiency of 13.24 %, an exergy efficiency of 75.94 %, and the lowest LCOE of 0.0159 $/kWh, representing substantial improvements over the baseline OFC-I and OFC-II systems. These results highlight the potential of advanced OFC designs for cost-effective and sustainable waste heat recovery applications.
{"title":"Energy, exergy and economic analysis and optimization of various modified organic flash cycle configurations for enhanced waste heat recovery performance","authors":"Hadi Kamfar , Abolfazl Shojaeian , Jaber Yousefi Seyf , Najmeh Hajialigol , Hadi Delavari","doi":"10.1016/j.clet.2025.101114","DOIUrl":"10.1016/j.clet.2025.101114","url":null,"abstract":"<div><div>This study presents a comprehensive thermodynamic investigation based on energy, exergy, and economic (3 E) analysis of eight Organic Flash Cycle (OFC) configurations for waste heat recovery. The modified cycles were modeled in MATLAB with thermophysical properties obtained from REFPROP 9.0. The proposed configurations integrate advanced components such as two-phase expanders and ejectors to minimize throttling losses and improve overall system performance. Unlike the dual-ejector systems reported by Chen et al. (2019), one of the proposed configurations, namely Two-phase expander and single ejector OFC-II (TPSEOFC-II) eliminates the secondary flash separator, resulting in a 21.5 % reduction in total costs and a 37.25 % improvement in exergy efficiency. Multi-objective optimization using the Multi-Objective Grey Wolf Optimizer was employed to simultaneously maximize energy efficiency and exergy efficiency while minimizing the levelized cost of energy (LCOE). The TPSEOFC-II configuration achieved a net power output of 363.19 kW, an energy efficiency of 13.24 %, an exergy efficiency of 75.94 %, and the lowest LCOE of 0.0159 $/kWh, representing substantial improvements over the baseline OFC-I and OFC-II systems. These results highlight the potential of advanced OFC designs for cost-effective and sustainable waste heat recovery applications.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101114"},"PeriodicalIF":6.5,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519623","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 : 2025-11-10DOI: 10.1016/j.clet.2025.101115
Akram Sandvall , Sofia Klugman , Olga Lysenko , Karl Vilén , Nathalie Fransson
Although having access to renewable sources of energy, islands often face challenges of security of energy supply, climate change impacts and drawbacks of fossil fuel dependency. Utilization of renewable resources, increasing energy efficiency, and securing an affordable energy supply are key elements of the sustainable energy transition of islands. In this study, a dynamic energy system optimization model is developed using the TIMES modeling framework and is applied from the perspective of an island's energy system. Carbon neutral energy system scenarios are designed and integrated into the model to assess system impacts of various industrial development options in connection with investment in large-scale offshore wind power for the case of a Swedish island. The results show a transition in the power and heat sectors for all the scenarios. Ground-source heat pumps (HPs) and district heat (DH) replace electric boilers and ambient-air HPs. The abundancy of renewable electricity generation, either due to non-existence of an energy intensive industry on the island or investments in large-scale wind power plants, leads to lower marginal cost of electricity generation. Consequently, the use of renewable (seawater) and low-temperature excess heat (EH) sources in large-scale HPs and direct use of high-temperature EH in DH systems increase. In turn, the EH sources replace biomass combustion in heat-only boilers. The intermittent renewable power generation is balanced by electricity import from the mainland (if allowed), biodiesel gas turbines, DH production in new biogas combined heat and power plants and large-scale HPs, and an existing heat storage.
{"title":"Carbon neutral island energy system transition - A model-based analysis of sector coupling between the electricity, industry and heat sectors","authors":"Akram Sandvall , Sofia Klugman , Olga Lysenko , Karl Vilén , Nathalie Fransson","doi":"10.1016/j.clet.2025.101115","DOIUrl":"10.1016/j.clet.2025.101115","url":null,"abstract":"<div><div>Although having access to renewable sources of energy, islands often face challenges of security of energy supply, climate change impacts and drawbacks of fossil fuel dependency. Utilization of renewable resources, increasing energy efficiency, and securing an affordable energy supply are key elements of the sustainable energy transition of islands. In this study, a dynamic energy system optimization model is developed using the TIMES modeling framework and is applied from the perspective of an island's energy system. Carbon neutral energy system scenarios are designed and integrated into the model to assess system impacts of various industrial development options in connection with investment in large-scale offshore wind power for the case of a Swedish island. The results show a transition in the power and heat sectors for all the scenarios. Ground-source heat pumps (HPs) and district heat (DH) replace electric boilers and ambient-air HPs. The abundancy of renewable electricity generation, either due to non-existence of an energy intensive industry on the island or investments in large-scale wind power plants, leads to lower marginal cost of electricity generation. Consequently, the use of renewable (seawater) and low-temperature excess heat (EH) sources in large-scale HPs and direct use of high-temperature EH in DH systems increase. In turn, the EH sources replace biomass combustion in heat-only boilers. The intermittent renewable power generation is balanced by electricity import from the mainland (if allowed), biodiesel gas turbines, DH production in new biogas combined heat and power plants and large-scale HPs, and an existing heat storage.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101115"},"PeriodicalIF":6.5,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519624","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 : 2025-11-07DOI: 10.1016/j.clet.2025.101084
Ihunanya Udodiri Ajakwe , Victor Ikenna Kanu , Simeon Okechukwu Ajakwe , Dong-Seong Kim
The Korean Emission Trading Scheme (K-ETS) is vital for reducing carbon emissions in South Korea. However, issues in transparency, security, and computational overhead limit its effectiveness. This work proposes an energy-efficient blockchain-based framework (eBCTC) to enhance the system with a decentralized blockchain architecture, Purechain. The framework leverages an improved consensus mechanism, the Proof of Authority and Association (PoA2). This is to address key challenges in the current K-ETS, such as centralization, lack of transparency, and high energy consumption. The PoA2 significantly reduces gas usage, with experimental results showing a 22 % reduction in gas consumption compared to traditional Proof of Work (PoW) and Proof of Authority (PoA) mechanisms. Also, PoA2 recorded a ×6 and ×2 reduction in gas price compared to PoW and PoA. The system also achieves faster transaction finality and lower computational costs, with transaction costs reduced by up to 83 % across the key K-ETS activities, including emissions reporting, credit allocation, and trading. Also, the system achieved moderate throughput, high latency, doubling scalability, high reliability, and a high success rate compared with DPoS and PBFT based on transaction stress validation tests. With an improved smart contract, intelligent automation of key functions, the system achieved a high energy gain for improved incentives. The proposed framework not only enhances the scalability and transparency of K-ETS but also aligns with South Korea's carbon neutrality goals by minimizing the environmental impact of blockchain operations. This study provides a solid foundation for sustainable carbon trading systems and an accountable carbon economy, contributing to global efforts to combat climate change in achieving the 2050 net-zero carbon emissions goal.
{"title":"eBCTC: Energy-efficient hybrid blockchain architecture for smart and secured K-ETS","authors":"Ihunanya Udodiri Ajakwe , Victor Ikenna Kanu , Simeon Okechukwu Ajakwe , Dong-Seong Kim","doi":"10.1016/j.clet.2025.101084","DOIUrl":"10.1016/j.clet.2025.101084","url":null,"abstract":"<div><div>The Korean Emission Trading Scheme (K-ETS) is vital for reducing carbon emissions in South Korea. However, issues in transparency, security, and computational overhead limit its effectiveness. This work proposes an energy-efficient blockchain-based framework (eBCTC) to enhance the system with a decentralized blockchain architecture, Purechain. The framework leverages an improved consensus mechanism, the Proof of Authority and Association (PoA<sup>2</sup>). This is to address key challenges in the current K-ETS, such as centralization, lack of transparency, and high energy consumption. The PoA<sup>2</sup> significantly reduces gas usage, with experimental results showing a 22 % reduction in gas consumption compared to traditional Proof of Work (PoW) and Proof of Authority (PoA) mechanisms. Also, PoA<sup>2</sup> recorded a ×6 and ×2 reduction in gas price compared to PoW and PoA. The system also achieves faster transaction finality and lower computational costs, with transaction costs reduced by up to 83 % across the key K-ETS activities, including emissions reporting, credit allocation, and trading. Also, the system achieved moderate throughput, high latency, doubling scalability, high reliability, and a high success rate compared with DPoS and PBFT based on transaction stress validation tests. With an improved smart contract, intelligent automation of key functions, the system achieved a high energy gain for improved incentives. The proposed framework not only enhances the scalability and transparency of K-ETS but also aligns with South Korea's carbon neutrality goals by minimizing the environmental impact of blockchain operations. This study provides a solid foundation for sustainable carbon trading systems and an accountable carbon economy, contributing to global efforts to combat climate change in achieving the 2050 net-zero carbon emissions goal.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101084"},"PeriodicalIF":6.5,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519641","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 : 2025-11-04DOI: 10.1016/j.clet.2025.101113
Viktor Yankovych , Nataliya Korol
Charcoal briquettes often fracture during handling because their fine particles require a binder that is both strong and low in ash. This study presents the first integrated analysis that couples full-scale briquetting trials with molecular docking simulations to guide binder selection. Industrial hardwood-charcoal fines were blended with five organic binders—native starch, citric-acid-modified starch, lignosulfonate, polyvinyl acetate (PVA), and flour—at 2.5–25 wt %. Each formulation was compacted using either a 5 MN hydraulic press or an industrial roller press and evaluated by proximate analysis, drop-impact testing (Impact Resistance Index, IRI), and axial compression.
Mechanical testing showed that modified starch outperformed all other binders, achieving compressive strengths up to 7 MPa and IRI values exceeding 3600 at 15–20 wt % loading under hydraulic pressing. Lignosulfonate, despite its high calculated adsorption energy (−6.1 kcal/mol), yielded weaker briquettes due to moisture uptake and higher ash, whereas PVA displayed the weakest surface affinity (−1.8 kcal/mol) and lowest mechanical strength. Across all formulations, hydraulic pressing improved strength two-to four-fold compared with roller pressing. Docking simulations on an oxidised-graphite model surface revealed that polysaccharides form extensive hydrogen-bond networks with oxygenated carbon edges, explaining their superior adhesion. These findings confirm that binder molecular structure and densification pressure jointly govern briquette integrity. When normalised for cost, modified starch remains the most efficient and sustainable option. The combined mechanochemical–molecular framework thus provides a transferable, molecularly informed roadmap for selecting sustainable binders and optimising compaction in commercial charcoal-briquette manufacturing.
{"title":"Mechanochemical and molecular analysis of organic binders in charcoal briquetting for enhanced cold mechanical strength","authors":"Viktor Yankovych , Nataliya Korol","doi":"10.1016/j.clet.2025.101113","DOIUrl":"10.1016/j.clet.2025.101113","url":null,"abstract":"<div><div>Charcoal briquettes often fracture during handling because their fine particles require a binder that is both strong and low in ash. This study presents the first integrated analysis that couples full-scale briquetting trials with molecular docking simulations to guide binder selection. Industrial hardwood-charcoal fines were blended with five organic binders—native starch, citric-acid-modified starch, lignosulfonate, polyvinyl acetate (PVA), and flour—at 2.5–25 wt %. Each formulation was compacted using either a 5 MN hydraulic press or an industrial roller press and evaluated by proximate analysis, drop-impact testing (Impact Resistance Index, IRI), and axial compression.</div><div>Mechanical testing showed that modified starch outperformed all other binders, achieving compressive strengths up to 7 MPa and IRI values exceeding 3600 at 15–20 wt % loading under hydraulic pressing. Lignosulfonate, despite its high calculated adsorption energy (−6.1 kcal/mol), yielded weaker briquettes due to moisture uptake and higher ash, whereas PVA displayed the weakest surface affinity (−1.8 kcal/mol) and lowest mechanical strength. Across all formulations, hydraulic pressing improved strength two-to four-fold compared with roller pressing. Docking simulations on an oxidised-graphite model surface revealed that polysaccharides form extensive hydrogen-bond networks with oxygenated carbon edges, explaining their superior adhesion. These findings confirm that binder molecular structure and densification pressure jointly govern briquette integrity. When normalised for cost, modified starch remains the most efficient and sustainable option. The combined mechanochemical–molecular framework thus provides a transferable, molecularly informed roadmap for selecting sustainable binders and optimising compaction in commercial charcoal-briquette manufacturing.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101113"},"PeriodicalIF":6.5,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466096","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 : 2025-11-03DOI: 10.1016/j.clet.2025.101109
Zahraa Jwaida
The use of agricultural wastes in brick production is increasing due to their potential for sustainable construction and efficient waste utilization. Predicting the physical and mechanical properties of such bricks remains challenging because of complex interactions among process variables and waste materials. This study addresses this by developing predictive models using four machine learning (ML) algorithms, namely random forest regressor (RFR), extreme gradient boosting (XGBoost), artificial neural network (ANN), and ridge regression (RR), based on a dataset of 110 data points including bricks with agricultural wastes such as rice husk ash (RHA) and wheat husk (WH), along with the physical and processing parameters. The results indicate that all models show strong potential for predicting brick properties with optimized hyperparameters. RFR achieved the highest predictive performance (R2 = 0.879 for compressive strength, 0.901 for water absorption), followed by XGBoost and ANN, which showed moderate predictive ability but signs of overfitting; RR performed the least effectively. SHapley Additive exPlanations (SHAP), Partial Dependence Plots (PDP), and Individual Conditional Expectation (ICE) plots revealed that manufacturing parameters were the most influential features. Sensitivity analysis showed that soil content (RMSE↑ 7.90), firing temperature (RMSE↑ 5.40), and brick size (RMSE↑ 4.95) had the highest impact, whereas waste additives exhibited low sensitivity (RMSE↑ < 2.0), supporting their sustainable inclusion. This study introduces a holistic workflow integrating predictive modeling, interpretable ML tools, and sensitivity analysis, as a template for materials science, highlighting its potential to optimize waste-based fired bricks and provide a transferable methodology for sustainable construction applications.
{"title":"Utilizing agricultural wastes for fired bricks: A machine learning approach to compressive strength and water absorption predictions","authors":"Zahraa Jwaida","doi":"10.1016/j.clet.2025.101109","DOIUrl":"10.1016/j.clet.2025.101109","url":null,"abstract":"<div><div>The use of agricultural wastes in brick production is increasing due to their potential for sustainable construction and efficient waste utilization. Predicting the physical and mechanical properties of such bricks remains challenging because of complex interactions among process variables and waste materials. This study addresses this by developing predictive models using four machine learning (ML) algorithms, namely random forest regressor (RFR), extreme gradient boosting (XGBoost), artificial neural network (ANN), and ridge regression (RR), based on a dataset of 110 data points including bricks with agricultural wastes such as rice husk ash (RHA) and wheat husk (WH), along with the physical and processing parameters. The results indicate that all models show strong potential for predicting brick properties with optimized hyperparameters. RFR achieved the highest predictive performance (R<sup>2</sup> = 0.879 for compressive strength, 0.901 for water absorption), followed by XGBoost and ANN, which showed moderate predictive ability but signs of overfitting; RR performed the least effectively. SHapley Additive exPlanations (SHAP), Partial Dependence Plots (PDP), and Individual Conditional Expectation (ICE) plots revealed that manufacturing parameters were the most influential features. Sensitivity analysis showed that soil content (RMSE↑ 7.90), firing temperature (RMSE↑ 5.40), and brick size (RMSE↑ 4.95) had the highest impact, whereas waste additives exhibited low sensitivity (RMSE↑ < 2.0), supporting their sustainable inclusion. This study introduces a holistic workflow integrating predictive modeling, interpretable ML tools, and sensitivity analysis, as a template for materials science, highlighting its potential to optimize waste-based fired bricks and provide a transferable methodology for sustainable construction applications.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101109"},"PeriodicalIF":6.5,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466097","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}
A novel drop-on-demand (DoD) 3D printing system was developed to fabricate complex-shaped products using natural latex ink. The printing parameters were systematically optimized based on the roundness and deposition behavior of rubber droplets, with 75 % alcohol identified as the most effective medium among various acid coagulants. The latex, formulated with a viscosity of 800 cP, was tailored to ensure printability and structural integrity. Optimal conditions—including a 0.85 mm nozzle diameter, a deposition rate of 45 mm3/s, an alcohol bath height of 3 mm, and a nozzle tip height of 10 mm from the medium surface—enabled the successful fabrication of a custom-designed palm splint featuring intricate geometry within 70 min. Dimensional comparison between the digital model and the printed splint in the X-Z and Y-Z planes revealed a deviation of only 9.89 %, which is acceptable for personalized medical devices. The printed splint exhibited a porous structure that enhances breathability and conformed precisely to the user's hand. Mechanical testing showed that the deposited rubber achieved a tensile strength exceeding 4.5 MPa and an elongation at break greater than 950 %, with droplet roundness values approaching unity. This DoD 3D printing approach significantly reduces material preparation time and production costs, offering a promising pathway for the rapid, cost-effective manufacturing of customized rubber-based products.
{"title":"Optimization of drop-on-demand 3D printing of natural latex ink for the fabrication of customized medical splints","authors":"Chakrit Suvanjumrat , Kanchanabhorn Chansoda , Machimontorn Promtong , Panithi Wiroonpochit , Thongsak Kaewprakob , Watcharapong Chookaew","doi":"10.1016/j.clet.2025.101112","DOIUrl":"10.1016/j.clet.2025.101112","url":null,"abstract":"<div><div>A novel drop-on-demand (DoD) 3D printing system was developed to fabricate complex-shaped products using natural latex ink. The printing parameters were systematically optimized based on the roundness and deposition behavior of rubber droplets, with 75 % alcohol identified as the most effective medium among various acid coagulants. The latex, formulated with a viscosity of 800 cP, was tailored to ensure printability and structural integrity. Optimal conditions—including a 0.85 mm nozzle diameter, a deposition rate of 45 mm<sup>3</sup>/s, an alcohol bath height of 3 mm, and a nozzle tip height of 10 mm from the medium surface—enabled the successful fabrication of a custom-designed palm splint featuring intricate geometry within 70 min. Dimensional comparison between the digital model and the printed splint in the X-Z and Y-Z planes revealed a deviation of only 9.89 %, which is acceptable for personalized medical devices. The printed splint exhibited a porous structure that enhances breathability and conformed precisely to the user's hand. Mechanical testing showed that the deposited rubber achieved a tensile strength exceeding 4.5 MPa and an elongation at break greater than 950 %, with droplet roundness values approaching unity. This DoD 3D printing approach significantly reduces material preparation time and production costs, offering a promising pathway for the rapid, cost-effective manufacturing of customized rubber-based products.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101112"},"PeriodicalIF":6.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466216","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 : 2025-10-31DOI: 10.1016/j.clet.2025.101104
Hajar H. Alshehhi , Ammar Hummieda , Ahmad Musamih , Assia Chadly , Khaled Salah , Ahmad Mayyas
As hydrogen gains prominence in energy systems, its adoption as an energy source for fuel cell electric vehicles (FCEVs) necessitates the establishment of hydrogen refueling stations (HRS). These stations contain critical compo-nents, including nozzles, storage tanks, heat exchangers, and compressors, which must be certified by regulatory agen-cies to ensure safety and public trust. Current certification processes are fragmented and manually intensive, creating inefficiencies and limiting transparency across the infrastructure lifecycle. In this paper, we propose a blockchain-based solution that creates a secure and auditable network for certifying key HRS components. The system integrates an EVM-compatible blockchain, decentralized storage, and a modular suite of smart contracts (SCs) that formalize registration, bidding, accreditation, certification, and governance. Each contract encodes a distinct actor-driven work-flow, enabling traceable and role-specific operations. A Decentralized Application (DApp) interface supports real-time and role-based interaction across the ecosystem. We present and evaluate the SCs and their underlying algorithms us-ing gas usage analysis, load testing, and security auditing. Load testing across the certification lifecycle shows stable transaction throughput and predictable cost profiles under increasing actor activity. A static security analysis con-firms resilience against common vulnerabilities. Our cost analysis indicates that while the framework is technically deployable on public blockchains, the execution costs of certain functions make it more cost-effective for private blockchains or Layer 2 networks. We also compare our framework with existing systems to highlight its novelty and technical advantages. Our SCs, DApp interface, and load testing scripts are publicly available on GitHub.
{"title":"Blockchain-based traceability and certifications of hydrogen refueling station components","authors":"Hajar H. Alshehhi , Ammar Hummieda , Ahmad Musamih , Assia Chadly , Khaled Salah , Ahmad Mayyas","doi":"10.1016/j.clet.2025.101104","DOIUrl":"10.1016/j.clet.2025.101104","url":null,"abstract":"<div><div>As hydrogen gains prominence in energy systems, its adoption as an energy source for fuel cell electric vehicles (FCEVs) necessitates the establishment of hydrogen refueling stations (HRS). These stations contain critical compo-nents, including nozzles, storage tanks, heat exchangers, and compressors, which must be certified by regulatory agen-cies to ensure safety and public trust. Current certification processes are fragmented and manually intensive, creating inefficiencies and limiting transparency across the infrastructure lifecycle. In this paper, we propose a blockchain-based solution that creates a secure and auditable network for certifying key HRS components. The system integrates an EVM-compatible blockchain, decentralized storage, and a modular suite of smart contracts (SCs) that formalize registration, bidding, accreditation, certification, and governance. Each contract encodes a distinct actor-driven work-flow, enabling traceable and role-specific operations. A Decentralized Application (DApp) interface supports real-time and role-based interaction across the ecosystem. We present and evaluate the SCs and their underlying algorithms us-ing gas usage analysis, load testing, and security auditing. Load testing across the certification lifecycle shows stable transaction throughput and predictable cost profiles under increasing actor activity. A static security analysis con-firms resilience against common vulnerabilities. Our cost analysis indicates that while the framework is technically deployable on public blockchains, the execution costs of certain functions make it more cost-effective for private blockchains or Layer 2 networks. We also compare our framework with existing systems to highlight its novelty and technical advantages. Our SCs, DApp interface, and load testing scripts are publicly available on GitHub.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101104"},"PeriodicalIF":6.5,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466095","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 : 2025-10-31DOI: 10.1016/j.clet.2025.101111
Ubolluk Rattanasak , Yusuf Chisti , Sarawut Jitpinit , Kamchai Nuithitikul
Levulinic acid (LA; 4-oxopentanoic acid, C5H8O3) is a useful platform chemical for making diverse other commercial products. This work developed a novel catalytic system for efficient production of LA from oil palm empty fruit bunch (EFB), a widely available lignocellulosic waste. First, the EFB was pretreated with tetrahydrofuran to obtain a cellulose-rich solid substrate that was subsequently converted to LA in a stirred batch reactor using solid acid catalysts. The catalysts were sulfated tin oxide (SO42−/SnO2) and a newly developed iron-doped variant, sulfated iron–tin oxide (SO42−/Fe–SnO2). Iron doping significantly increased both the specific surface area (from 145.9 to 168.7 m2 g−1) and the number of acid sites. The effects of reaction temperature (180–220 °C), reaction time (1–6 h), and the catalyst loading (0–4 % w w−1) on the yield of LA and the other useful byproducts are reported. The sulfated iron-tin oxide catalyst was more active than the sulfated tin oxide under certain reaction conditions. Notably, it achieved a maximum LA yield of 31.2 % w w−1 based on the pretreated EFB, or 39.9 % w w−1 based on available cellulose, surpassing many metal oxide catalysts reported in the literature. The optimum reaction conditions were 200 °C, 1 h, and a SO42−/Fe-SnO2 catalyst loading of 2 % w w−1. The promising heterogeneous catalytic approach used here for upgrading lignocellulosic waste to higher value chemicals offers environmental and economic benefits.
乙酰丙酸（LA； 4-氧戊酸，C5H8O3）是制造各种其他商业产品的有用平台化学品。本研究开发了一种新的催化系统，用于从广泛利用的木质纤维素废弃物油棕榈空果束（EFB）中高效生产LA。首先，用四氢呋喃预处理EFB，得到富含纤维素的固体底物，随后在搅拌间歇式反应器中使用固体酸催化剂将其转化为LA。催化剂为硫酸氧化锡（SO42−/SnO2）和一种新开发的铁掺杂型硫酸氧化铁（SO42−/ Fe-SnO2）。铁的掺杂显著增加了比表面积（从145.9增加到168.7 m2 g−1）和酸位的数量。报道了反应温度（180 ~ 220℃）、反应时间（1 ~ 6 h）和催化剂用量（0 ~ 4% w w−1）对LA和其他有用副产物产率的影响。在一定的反应条件下，硫化铁锡氧化物催化剂的活性高于硫化锡氧化物催化剂。值得注意的是，在预处理EFB的基础上，LA的最大产率为31.2%，在现有纤维素的基础上，LA的最大产率为39.9%，超过了文献中报道的许多金属氧化物催化剂。最佳反应温度为200℃，反应时间为1 h， SO42−/Fe-SnO2催化剂负载为2% w w−1。这里使用的有前途的多相催化方法将木质纤维素废物转化为高价值的化学品，具有环境和经济效益。
{"title":"Production of levulinic acid from oil palm empty fruit bunch fiber using novel tin oxide catalysts","authors":"Ubolluk Rattanasak , Yusuf Chisti , Sarawut Jitpinit , Kamchai Nuithitikul","doi":"10.1016/j.clet.2025.101111","DOIUrl":"10.1016/j.clet.2025.101111","url":null,"abstract":"<div><div>Levulinic acid (LA; 4-oxopentanoic acid, C<sub>5</sub>H<sub>8</sub>O<sub>3</sub>) is a useful platform chemical for making diverse other commercial products. This work developed a novel catalytic system for efficient production of LA from oil palm empty fruit bunch (EFB), a widely available lignocellulosic waste. First, the EFB was pretreated with tetrahydrofuran to obtain a cellulose-rich solid substrate that was subsequently converted to LA in a stirred batch reactor using solid acid catalysts. The catalysts were sulfated tin oxide (SO<sub>4</sub><sup>2−</sup>/SnO<sub>2</sub>) and a newly developed iron-doped variant, sulfated iron–tin oxide (SO<sub>4</sub><sup>2−</sup>/Fe–SnO<sub>2</sub>). Iron doping significantly increased both the specific surface area (from 145.9 to 168.7 m<sup>2</sup> g<sup>−1</sup>) and the number of acid sites. The effects of reaction temperature (180–220 °C), reaction time (1–6 h), and the catalyst loading (0–4 % w w<sup>−1</sup>) on the yield of LA and the other useful byproducts are reported. The sulfated iron-tin oxide catalyst was more active than the sulfated tin oxide under certain reaction conditions. Notably, it achieved a maximum LA yield of 31.2 % w w<sup>−1</sup> based on the pretreated EFB, or 39.9 % w w<sup>−1</sup> based on available cellulose, surpassing many metal oxide catalysts reported in the literature. The optimum reaction conditions were 200 °C, 1 h, and a SO<sub>4</sub><sup>2−</sup>/Fe-SnO<sub>2</sub> catalyst loading of 2 % w w<sup>−1</sup>. The promising heterogeneous catalytic approach used here for upgrading lignocellulosic waste to higher value chemicals offers environmental and economic benefits.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101111"},"PeriodicalIF":6.5,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466214","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}
The size of nanoparticles synthesized by the liquid phase reduction method depends on the concentration of metal ions. Thus, it is difficult to synthesize fine nanoparticles with high concentration. However, by using solid raw materials and by controlling both solubility and nucleation, the synthesis of nanoparticles at high concentrations can be realized. The instantaneous high degree of nucleation would not necessitate the addition of dispersants. Cu nanoparticles were synthesized by reduction with N2H4·H2O using CuO as a raw material whose dissolution was promoted with the addition of CH3COOH. Varying concentrations of CH3COOH, N2H4·H2O, and CuO were used to investigate their effects. The synthesized material was characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Cu nanoparticles (raw material concentration of 4 M) were synthesized by a 10 min reduction. This concentration is 20 times higher than that of conventional chemical reduction methods. At a raw material concentration of 4 M, Cu nanoparticles were synthesized with a high yield (99.69 %). The average particle size of the synthesized sample was 121.9 nm, half the size of nanoparticles synthesized at 1 M concentration. Furthermore, this process suppresses the generation of harmful waste liquids and does not require further cleaning. The rate-determining step of the reaction in the solid-liquid reaction field was the dissolution process of the raw material particle surface, and due to the instantaneous high nucleation rate, it is a Waste-Reducing synthesis method that does not require a dispersant.
{"title":"High-throughput and waste-reducing synthesis of dispersant-free Cu nanoparticles via CuO reduction","authors":"Gosuke Takano, Yamato Hayashi, Yuto Ishida, Hirotsugu Takizawa","doi":"10.1016/j.clet.2025.101108","DOIUrl":"10.1016/j.clet.2025.101108","url":null,"abstract":"<div><div>The size of nanoparticles synthesized by the liquid phase reduction method depends on the concentration of metal ions. Thus, it is difficult to synthesize fine nanoparticles with high concentration. However, by using solid raw materials and by controlling both solubility and nucleation, the synthesis of nanoparticles at high concentrations can be realized. The instantaneous high degree of nucleation would not necessitate the addition of dispersants. Cu nanoparticles were synthesized by reduction with N<sub>2</sub>H<sub>4</sub>·H<sub>2</sub>O using CuO as a raw material whose dissolution was promoted with the addition of CH<sub>3</sub>COOH. Varying concentrations of CH<sub>3</sub>COOH, N<sub>2</sub>H<sub>4</sub>·H<sub>2</sub>O, and CuO were used to investigate their effects. The synthesized material was characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Cu nanoparticles (raw material concentration of 4 M) were synthesized by a 10 min reduction. This concentration is 20 times higher than that of conventional chemical reduction methods. At a raw material concentration of 4 M, Cu nanoparticles were synthesized with a high yield (99.69 %). The average particle size of the synthesized sample was 121.9 nm, half the size of nanoparticles synthesized at 1 M concentration. Furthermore, this process suppresses the generation of harmful waste liquids and does not require further cleaning. The rate-determining step of the reaction in the solid-liquid reaction field was the dissolution process of the raw material particle surface, and due to the instantaneous high nucleation rate, it is a Waste-Reducing synthesis method that does not require a dispersant.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101108"},"PeriodicalIF":6.5,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145417117","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 : 2025-10-30DOI: 10.1016/j.clet.2025.101107
Mehrdad Maghsoudi , Navid Mohammadi , Seyed Mohammed Ali mousavi Roudsari
The urgency to transition from linear to circular economic models has spurred growing interest in technologies that enable sustainability. However, prior studies leveraging patent data to track circular economy (CE) innovation have remained fragmented, limited by sectoral silos, regional focus, or reliance on secondary sources. This study addresses these gaps by presenting a comprehensive, cross-sectoral technology roadmap grounded in large-scale patent analytics. The research employs a seven-phase methodology including data mining from 39,145 CE patents, semantic embedding via transformer models, BERTopic-based clustering, logistic lifecycle modeling, and expert panel validation to identify 42 distinct technology clusters. These clusters are positioned across defined innovation lifecycle stages (emergent, growth, mature, saturated) and linked to associated products and market applications. Key findings reveal substantial heterogeneity in CE innovation maturity: while clusters like printer cartridge remanufacturing and valve refurbishment are commercially saturated, others such as power-to-hydrogen and wind-turbine blade circularity remain in early development. The resulting multi-layered roadmap connects technologies to product systems and market sectors across short-, mid-, and long-term horizons. Implications span strategic investment targeting, R&D prioritization, and evidence-based policy design, enabling stakeholders to navigate the complex technological ecosystem of the circular economy more effectively. By offering a scalable, empirically grounded framework that explicitly bridges technology, product, and market layers, this research advances methodological standards for innovation mapping and supports decision-making aligned with circularity and sustainability transitions.
{"title":"A multi-layered patent analytics framework for technology roadmapping in the circular economy","authors":"Mehrdad Maghsoudi , Navid Mohammadi , Seyed Mohammed Ali mousavi Roudsari","doi":"10.1016/j.clet.2025.101107","DOIUrl":"10.1016/j.clet.2025.101107","url":null,"abstract":"<div><div>The urgency to transition from linear to circular economic models has spurred growing interest in technologies that enable sustainability. However, prior studies leveraging patent data to track circular economy (CE) innovation have remained fragmented, limited by sectoral silos, regional focus, or reliance on secondary sources. This study addresses these gaps by presenting a comprehensive, cross-sectoral technology roadmap grounded in large-scale patent analytics. The research employs a seven-phase methodology including data mining from 39,145 CE patents, semantic embedding via transformer models, BERTopic-based clustering, logistic lifecycle modeling, and expert panel validation to identify 42 distinct technology clusters. These clusters are positioned across defined innovation lifecycle stages (emergent, growth, mature, saturated) and linked to associated products and market applications. Key findings reveal substantial heterogeneity in CE innovation maturity: while clusters like printer cartridge remanufacturing and valve refurbishment are commercially saturated, others such as power-to-hydrogen and wind-turbine blade circularity remain in early development. The resulting multi-layered roadmap connects technologies to product systems and market sectors across short-, mid-, and long-term horizons. Implications span strategic investment targeting, R&D prioritization, and evidence-based policy design, enabling stakeholders to navigate the complex technological ecosystem of the circular economy more effectively. By offering a scalable, empirically grounded framework that explicitly bridges technology, product, and market layers, this research advances methodological standards for innovation mapping and supports decision-making aligned with circularity and sustainability transitions.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101107"},"PeriodicalIF":6.5,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145576310","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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