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Plant-microbial fuel cell for electrical generation through living plants: an internal resistance insight into the plant species used

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Clean Energy 2024年第5期8卷 45-53页

作者： Raymond Daniel Rodriguez Martinez department of Industrial production Faculty of EngineeringUniversidad Metropolitana1073 CaracasVenezuela

Climate change is a global threat,the presence of which has encouraged the development and implementation of renewable energies,including plant–microbial fuel cells,which could generate 6629568–33147840 MWh per year due to their large-scale *** of the main challenges associated with microbial cells is internal resistance—a parameter whose magnitude is influenced by sev-eral *** the case of plant–microbial fuel cells,adding a plant positively affects the mitigation of internal ***,the species employed is expected to play an important *** the present study,the objective was to determine as a general reference the internal resistance of cells using various plant species,among which were tomato(Solanum lycopersicum),black beans(Phaseolus vulgaris),aloe vera(Aloe vera),corn(Zea mays),and moss(Dicranidae).For this purpose,an experimental procedure was carried out to compare the manual voltage measurements with a free cell concerning the voltage obtained by adding an external resistor in *** internal resistance values were determined as a function of the measured voltage,obtaining 177,179,175,324,and 233 kΩfor aloe vera,corn,tomato,black beans,and moss,*** this,it was shown that the roots of the plants represent an essen-tial addition to the internal resistance of the cell in the short *** contrast,plants with a C4 photosynthetic metabolism are more favourable,while C3 plants can also benefit from internal resistance during a more extended period of rhizodeposition.

关键词： climate change energy microorganism renewable source voltage

An integrated framework for assessing renewable-energy supply chains using multicriteria decision-making:a study on Bangladesh

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Clean Energy 2024年第3期8卷 1-19页

作者： A.M.Almas Shahriyar Azad Zarin Tasnim Oishi Md.Ariful Haque Pronob Das Sabbir Ahmed Udoy Khaled Mohammad Shifullah Bhuiya department of Industrial&production engineering Rajshahi University of Engineering&TechnologyRajshahi-6204Bangladesh department of Mechanical engineering Rajshahi University of Engineering&TechnologyRajshahi-6204Bangladesh

The depletion in non-renewable energy sources and a fast-growing population in Bangladesh are exacerbating the already existing energy scarcity,highlighting the need for an efficient and robust renewable-energy supply *** primary goal of this study is to evaluate the most optimized renewable-energy supply chain based on natural resource availability and government policies of *** the present study,four renewable energy resources,including solar,biomass,wind and hydropower,are studied and nine subcriteria are defined under four primary criteria for each supply *** for Order Preference by Similarity to Ideal Solution(TOPSIS)and VIseKriterijumska Optimizacija I Kompromisno Resenje(VIKOR)are multicriteria decision-making approaches used in this study to compare and choose the best renewable-energy supply *** relative significance of four supply-chain criteria for primary renewable energy in this study,namely energy procurement,production,operations and maintenance costs,and social and environmental impact,is gathered via a *** results of this research,supported by a comprehensive sensitivity analysis,indicate that hydropower is the best renewable-energy supply chain,followed by wind as a compromise solution,biomass and *** study also demonstrates that no energy source can satisfy all supply-chain criteria alone;each resource is better for a specific criterion-solar is better for procurement,hydropower is significant for production and wind is remarkable for operations and social ***,to maximize output,renewable energy sources must be *** Bangladesh’s perspective,for the first time,by using TOPSIS and VIKOR together,this study offers significant insights to establish an efficient and sustainable renewable-energy supply chain for practitioners,academics and policymakers.

关键词： renewable-energy supply chain Bangladesh multicriteria decision-making TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) VIKOR(VIseKriterijumska Optimizacija I Kompromisno Resenje)

A novel low-cost visual ear tag based identification system for precision beef cattle livestock farming

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Information Processing in Agriculture 2024年第1期11卷 117-126页

作者： Andrea Pretto Gianpaolo Savio Flaviana Gottardo Francesca Uccheddu Gianmaria Concheri department of Civil Environmental and Architectural EngineeringUniversity of PaduaItaly department of Animal Medicine Production and HealthUniversity of PadovaItaly department of Industrial engineering University of PadovaItaly

The precision livestock farming(PLF)has the objective to maximize each animal's performance while reducing the environmental impact and maintaining the quality and safety of meat *** the PLF techniques,the personalised management of each individual animal based on sensors systems,represents a viable *** is worth noting that the implementation of an effective PLF approach can be still expensive,especially for small and medium-sized farms;for this reason,to guarantee the sustainability of a customized livestock management system and encourage its use,plug and play and cost-effective systems are *** this context,we present a novel low-cost method for identifying beef cattle and recognizing their basic activities by a single surveillance *** leveraging the current state-of-the-art methods for real-time object detection,(i.e.,YOLOv3)cattle's face areas,we propose a novel mechanism able to detect the ear tag as well as the water ingestion state when the cattle is close to the *** cow IDs are read by an Optical Character Recognition(OCR)algorithm for which,an ad hoc error correction algorithm is here presented to avoid numbers misreading and correctly match the IDs to only actually present *** to the detection of the tag position,the OCR algorithm can be applied only to a specific region of interest reducing the computational cost and the time *** times for the areas are outputted as cattle activity recognition *** results demonstrate the effectiveness of our proposed method,showing a mAP@0.50 of 89%.

关键词： Precision livestock farming Deep learning Cattlei dentification Low-cost sensors Computer vision

From ore to MOF: A case of MIL-100(Fe) production from iron ore concentrates

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Progress in Natural Science:Materials International 2024年第1期34卷 66-73页

作者： Miao Chang Chiyao Tang Chong-Chen Wang Chen Zhao Beijing Key Laboratory of Functional Materials for Building Structure and environment Remediation School of Environment and Energy Engineering Beijing University of Civil Engineering and Architecture

Within this work, iron ore concentrates instead of elemental iron Fe0and iron salts like Fe（NO3）3and FeCl3were selected as iron source to prepare MIL-100（Fe）(labeled as MIL-100（Fe）-ore). The corresponding synthesis cost is reduced to half of the MIL-100（Fe） produced from elemental iron and iron salts. As well, the unreacted iron ore concentrates can be easily separated from the as-prepared MIL-100（Fe）-ore by magnetic to facilitate the purification process, free of the strong acids to wash the residual iron. The as-obtained MIL-100（Fe）-ore with Langmuir surface area up to 2281.6 m2g-1displayed long-term chemical stability. Furthermore, the sorption capacity of MIL-100（Fe）-ore towards malachite green（MG） is up to 522.3 mg g-1at 25℃ and initial pH = 3.2, higher than that of MIL-100（Fe） yielded by conventional hydrothermal process. Finally, the production cost and life cycle assessment of MIL-100（Fe）-ore were compared with other traditional production procedures. The results revealed that our work greatly reduced the synthesis cost and enhanced the environmental sustainability.

关键词： Metal-organic framework Iron ore concentrates Adsorption Life cycle assessment

Sn-doped cobalt containing perovskite as the air electrode for highly active and durable reversible protonic ceramic electrochemical cells

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Journal of Advanced Ceramics 2024年第1期13卷 63-72页

作者： Min Fu Wenjing Hu Hua Tong Xin Ling Linggui Tan Fanglin Chen Zetian Tao School of Resources Environment and Safety EngineeringUniversity of South ChinaHengyang 421001China department of Mechanical engineering University of South CarolinaColumbia 29208USA

One potential solution to the problems of energy storage and conversion is the use of reversible protonic ceramic electrochemical cells(R-PCEC),which are based on the solid oxide fuel cell(SOFC)technology and offer a flexible route to the generation of renewable ***,the R-PCEC development faces a range of significant challenges,including slow oxygen reaction kinetics,inadequate durability,and poor round-trip efficiency resulting from the inadequacy of an air *** address these issues,we report novel B-sites doped Pr_(0.5)Ba_(0.5)Co_(0.7)Fe_(0.3)O_(3−δ)(PBCF)with varying amounts of Sn as the air electrode for R-PCEC to further enhance electrochemical performance at lower *** 600℃,R-PCEC with an air electrode consisting of Pr_(0.5)Ba_(0.5)Co_(0.7)Fe_(0.25)Sn_(0.05)O_(3+δ)has achieved peak power density of 1.12 W∙cm^(−2) in the fuel cell mode and current density of 1.79 A∙cm^(−2) in the electrolysis mode at a voltage of 1.3 ***,R-PCECs have shown good stability in the electrolysis mode of 100 *** study presents a practical method for developing durable high-performance air electrodes for R-PCECs.

关键词： triple conducting oxide dual-element doping protonic ceramic electrochemical cells(PCECs) catalytic

Machine learning-based multi-objective optimization and thermal assessment of supercritical CO_(2) Rankine cycles for gas turbine waste heat recovery

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Energy and AI 2024年第2期16卷 363-384页

作者： Asif Iqbal Turja Ishtiak Ahmed Khan Sabbir Rahman Ashraf Mustakim Mohammad Ishraq Hossain M Monjurul Ehsan Yasin Khan department of Mechanical and production engineering(MPE) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

Technologies for utilizing waste heat for power generation have attracted significant attention in recent years due to their potential to enhance energy efficiency and reduce greenhouse gas *** research focuses on the comparative and optimization analysis of three supercritical carbon dioxide(sCO_(2))Rankine cycles(simple,cascade,and split)for gas turbine waste heat *** study begins with parametric analysis,investigating the significant effects of key variables,including turbine inlet temperature,condenser inlet temperature,and pinch point temperature,on the thermal performance of advanced sCO_(2) power *** identify the most efficient cycle configuration,a multi-objective optimization approach is *** approach combines a Genetic Algorithm with machine learning regression models(Random Forest,XGBoost,Artificial Neural Network,Ridge Regression,and K-Nearest Neighbors)to predict cycle performance using a dataset extracted from cycle *** decision-making process for determining the optimal cycle configuration is facilitated by the TOPSIS(technique for order of preference by similarity to the ideal solution)*** study's major findings reveal that the split cycle outperforms the simple and cascade configurations in terms of power generation across various operating *** optimized split cycle not only demonstrates superior power output but also exhibits enhanced net power output,heat recovery,system and exergy efficiency of 7.99 MW,76.17%,26.86%and 57.96%,respectively,making it a promising choice for waste heat recovery *** research has the potential to contribute to the advancement and widespread adoption of waste heat recovery in energy technologies boosting system efficiency and economic *** provides a new perspective for future research,contributing to the improvement of energy generation infrastructure.

关键词： Supercritical co2 Rankine cycle Waste heat recovery Gas turbine Thermodynamic analysis Machine Learning Optimization

Multi-objective performance optimization&thermodynamic analysis of solar powered supercritical CO_(2)power cycles using machine learning methods&genetic algorithm

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Energy and AI 2024年第1期15卷 193-216页

作者： Asif Iqbal Turja Md Mahmudul Hasan M.Monjurul Ehsan Yasin Khan department of Mechanical and production engineering(MPE) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

The present study is focused on multi-objective performance optimization&thermodynamic analysis from the perspectives of energy and exergy for Recompression,Partial Cooling&Main Compression Intercooling supercritical CO_(2)(sCO_(2))Brayton cycles for concentrated solar power(CSP)applications using machine learning *** novelty of this work lies in the integration of artificial neural networks(ANN)and genetic algorithms(GA)for optimizing the performance of advanced sCO_(2)power cycles considering climatic variation,which has significant implications for both the scientific community and engineering applications in the renewable energy *** methodology employed includes thermodynamic analysis based on energy,exergy&environmental factors including system performance *** system is modelled for net power production of 15 MW thermal output utilizing equations for the energy and exergy balance for each ***,thermodynamic model extracted dataset used for prediction&evaluation of Random Forest,XGBoost,KNN,AdaBoost,ANN and LightGBM ***,considering climate conditions,multi-objective optimization is carried out for the CSP integrated sCO_(2)Power cycle for optimal power output,exergy destruction,thermal and exergetic *** algorithm and TOPSIS(technique for order of preference by similarity to ideal solution),multi-objective decision-making tool,were used to determine the optimum operating *** major findings of this work reveal significant improvements in the performance of the advanced sCO_(2)cycle by 1.68%and 7.87%compared to conventional recompression and partial cooling cycle,*** research could advance renewable energy technologies,particularly concentrated solar power,by improving power cycle designs to increase system efficiency and economic *** advanced supercritical CO_(2)power cycles in concentrated solar power plants might increase renewable energy use

关键词： Supercritical CO_(2) Concentrated solar power Thermodynamic analysis Machine learning Artificial neural network Multi-objective optimization

Eigenfrequency analysis of bridges using a smartphone and a novel low-cost accelerometer prototype

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Frontiers of Structural and Civil engineering 2024年第2期18卷 202-215页

作者： Seyedmilad KOMARIZADEHASL Ye XIA Mahyad KOMARY Fidel LOZANO department of Civil and environment engineering Universitat Politècnica de CatalunyaBarcelona 08034Spain department of Bridge engineering Tongji UniversityShanghai 200092China department of Civil engineering Universidad de Castilla-La ManchaCiudad Real 13071Spain

Researchers are paying increasing attention to the development of low-cost and microcontroller-based accelerometers,in order to make structural health monitoring feasible for conventional bridges with limited monitoring *** with the low-cost sensor development,the use of the embedded accelerometers of smartphones for eigenfrequency analysis of bridges is becoming popular in the civil engineering *** paper,for the first time in the literature,studies these two promising technologies by comparing the noise density and eigenfrequency analysis of a self-developed,validated and calibrated low-cost Internet of things based accelerometer LARA(low cost adaptable reliable accelerometer)with those of a state of the art smartphone(iPhone XR).The eigenfrequency analysis of a footbridge in San Sebastian,Spain,showed that the embedded accelerometer of the iPhone XR can measure the natural frequencies of the under study bridge.

关键词： smartphone modal analysis eigenfrequency analysis low-cost accelerometers Arduino Raspberry Internet of things

The underappreciated role of fugitive VOCs in ozone formation and health risk assessment emitted from seven typical industries in China

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Journal of environmental Sciences 2024年第2期136卷 647-657页

作者： Zhiling Liang Yunjiang Yu Bingbing Sun Qian Yao Xihua Lin Yongsheng Wang Jianping Zhang Yingzi Li Xuefeng Wang Zhengzheng Tang Shexia Ma College of environmental and Chemical engineering Shanghai University of Electric PowerShanghai 200090China State environmental Protection Key Laboratory of environmental Protection Health Risk Assessment South China Institute of Environmental SciencesMinistry of Ecology and EnvironmentGuangzhou 510535China Henan Jiyuan Ecological environment Testing Center Jiyuan 454650China Ecological environment Bureau of Jiyuan production City Integration Demonstration Zone Jiyuan 454650China

Fugitive emission from industrial sources may result in ozone formation and health risk,while the exact contribution of this source remains incompletely *** this study,emission characteristics,ozone formation potential(OFP)and health risk of fugitive VOCs in7 representative industries were *** material industry was the dominant contributor to VOCs of fugitive emission in comparison with other *** OFP of VOCs from fugitive emission was in the range of 1.45×10^(3)-3.98×10^(5)μg/m^(3),with a higher value than that of organized emission in seven industries except for the coking industry and the chemical material industry,suggesting that fugitive VOCs should be taken into account while developing control ***,m,p-xylene,n-nonane,ethylene,vinyl chloridethe and other high OFP-contributing species were the major reactive species that should be *** risk assessment investigated non-cancer and cancer risks of fugitive VOCs in 7 industries were all above safe level(HR>1 and LCR>1×10^(-4)),posing remarkable health threats to human *** were the main contributor to non-cancer risk,while halohydrocarbons and aromatics contributed most to cancer risks,posing remarkable health threat on human *** findings highlighted the contribution of fugitive VOCs on ozone formation and health risk was underestimated,indicating which should be considered in emission control strategies of industrial sources.

关键词： Industrial sources Volatile organic compounds Fugitive emission Ozone formation potential Health risk assessment