Energy Conversion and Management最新文献

{"title":"From sewage sludge to Hydrogen: Life cycle Techno-Environment-Economic assessment of combined system with supercritical water Gasification, organic Rankine cycle and carbon capture and storage","authors":"Jingmin Deng ,&nbsp;Yuting Tang ,&nbsp;Jiehong Tang ,&nbsp;Hongyu Liu ,&nbsp;Weilong Chen ,&nbsp;Ziwei Sun ,&nbsp;Songbin Peng ,&nbsp;Xiaoqian Ma","doi":"10.1016/j.enconman.2024.119221","DOIUrl":"10.1016/j.enconman.2024.119221","url":null,"abstract":"<div><div>Supercritical water gasification (SCWG) technology has attracted significant attention due to its advantages in efficiently treating high-moisture materials and producing hydrogen-rich gas, offering an attractive option for sewage sludge (SS) treatment. This study develops an efficient hydrogen production system that integrates SCWG, Organic Rankine Cycle (ORC), and carbon capture and storage (CCS) technologies. A comprehensive life cycle techno-environmental-economic assessment of SS to hydrogen (SStH) process with SCWG technology is conducted. The results indicate that gasification temperature and moisture content are the primary factors affecting H₂ yield and system efficiency, while gasification pressure has a minor impact. The system demonstrates favorable exergy efficiency (30.93 %) and a certain advantage in overall environmental impact (66.99 mPE). Electricity and natural gas particularly contributed to the environmental impact indicators. Reducing energy consumption or seeking alternative low-emission renewable energy sources will further reduce its environmental impact. The economic feasibility of SStH is sensitive to energy prices, with the cost of natural gas and the selling price of H₂ being critical factors. Strategies such as reducing reliance on natural gas, increasing hydrogen sales prices, and leveraging carbon tax credits and sludge subsidies are vital for enhancing the economic viability of SStH with SCWG technology. Renewable energy utilization and co-gasification are expected to further reduce the operating costs of SCWG.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119221"},"PeriodicalIF":9.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142655904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Process optimisation and enviro-economic assessment of carbon-negative hydrogen production from biomass co-gasification","authors":"Pushpraj Patel ,&nbsp;Ioanna Dimitriou ,&nbsp;Prasenjit Mondal ,&nbsp;Omvir Singh ,&nbsp;Shubhi Gupta","doi":"10.1016/j.enconman.2024.119211","DOIUrl":"10.1016/j.enconman.2024.119211","url":null,"abstract":"<div><div>Biomass wastes are abundantly available, yet leveraging these resources for large-scale green energy production requires a comprehensive and strategic evaluation. In this study, an environmentally sustainable and economically viable gasification process for generating pure hydrogen gas from waste biomass was developed. Switchgrass was combined with two co-feeds: low-density polyethylene (LDPE) and high ash coal to improve hydrogen production efficiency. Two process configurations for biomass gasification/co-gasification were investigated: (1) baseline scenario without addition of key units towards sustainability, including carbon-capture (CC), waste heat recovery (WHR) and in-plant power &amp; steam generation (PSG), and (2) integrated scenario with the addition of CC, WHR and PSG. The integrated gasification scenario achieved over 99 % hydrogen purity and high carbon capture efficiency, leading to negative carbon emissions of –323.55, −465.84, and −68.28 kg CO₂ eq. for biomass, biomass-LDPE and biomass-coal gasification, respectively. Besides this, integrated scenarios also displayed negative emissions in most of the other impact categories like ecotoxicity, acidification, eutrophication and many more. The corresponding net present value (NPV) for biomass, biomass-LDPE and biomass-coal gasification integrated scenario was $69.7 million, $108 million, and $76.4 million, respectively. The results indicate that biomass co-fed with LDPE in integrated gasification scenario represents the most environmentally and economically sustainable case with the highest hydrogen production, lowest environmental emissions and highest economic returns. It was also shown that process energy requirements were the key driver of environmental emissions and production costs. This research provides a comprehensive evaluation framework for waste-to-hydrogen technologies by identifying critical process hotspots and necessary policy measures for large-scale implementation of sustainable hydrogen.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119211"},"PeriodicalIF":9.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal operating strategy of hybrid heat pump − boiler systems with photovoltaics and battery storage","authors":"Francesco Nicoletti,&nbsp;Giuseppe Ramundo,&nbsp;Natale Arcuri","doi":"10.1016/j.enconman.2024.119233","DOIUrl":"10.1016/j.enconman.2024.119233","url":null,"abstract":"<div><div>The growing need to reduce energy consumption and greenhouse gas emissions is driving the search for more efficient heating solutions in buildings. Hybrid heating systems, which combine air-to-water heat pumps (AWHP) with traditional gas boilers, are a common solution after refurbishment investments. However, managing these systems effectively, particularly when integrated with photovoltaic (PV) panels and battery energy storage systems (BESS), remains a complex task. For instance, heat pumps perform poorly in very cold conditions, making boilers a more efficient option; however, it might be advantageous to use it to increase electricity self-consumption. Optimal management depends on multiple factors, including future forecast data. In this paper, a daily optimization program is developed by means of a brute-force approach using forecast data. The core innovation of this paper is the use of an artificial neural network (ANN) that, trained on predictive optimization results, can determine the optimal solution in real-time without the need for future forecasts. The ANN achieved a 99.16% accuracy in new scenarios, successfully optimizing costs, CO₂ emissions, and primary energy use. Results indicate up to 19% cost savings in colder cities, a 12% reduction in CO₂ emissions, and a 3% decrease in primary energy consumption. This approach holds significant potential for enhancing the integration of renewable energy sources, contributing to long-term sustainability goals.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119233"},"PeriodicalIF":9.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142655846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an optimized proton exchange membrane fuel cell model based on the artificial neural network","authors":"Ceyuan Chen ,&nbsp;Jingsi Wei ,&nbsp;Cong Yin ,&nbsp;Zemin Qiao ,&nbsp;Wenfeng Zhan","doi":"10.1016/j.enconman.2024.119215","DOIUrl":"10.1016/j.enconman.2024.119215","url":null,"abstract":"<div><div>Numerical studies have been considered as a vital method to optimize the system design and the control strategy of proton exchange membrane (PEM) fuel cells practically. Given that the engineering application of multi-dimensional physics-based simulations is very challenging in terms of efficiency, this presents a unique opportunity for modeling approaches based on the artificial neural network (ANN). As a supplement to traditional statistical methods, the ANN technique demonstrates advantages in dealing with arbitrary nonlinear relations between the independent and dependent variables. In the present study, an optimized model using a feed-forward back-propagation (BP) network has been developed. By integrating with the genetic algorithm, the risk of overfitting could be reduced. The automatic process of searching for the most suitable network structure algorithm has also been adopted. Moreover, to figure out appropriate input variables, a feature dimension reduction methodology has been implemented in the proposed input variable determination (IVD) sub-model during the pre-processing procedure. The data points required for training, validating, and testing are obtained from comprehensive sensitivity tests. The active area of the membrane electrode assembly (MEA) in the present experiment is around 220 cm² which is the same order of magnitude as commercial products. The optimized model has been thoroughly validated against experimental measurements, results show that simulations could accurately reproduce the effect of multiple operating parameters on the fuel cell performance. This new model is applicable to both interpolation and extrapolation. Furthermore, by activating the IVD sub-model, the maximum and average relative errors of extrapolation simulation results could be reduced up to 63 % and 37 %, respectively. In addition, by reasonably selecting the input variables in the order of priority, the mean relative error remains under 1 % with fewer input variables. The number of required training data points could be reduced up to 53 %.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119215"},"PeriodicalIF":9.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatially-optimized photovoltaic site selection in Algeria: Assessing solar potential using high-resolution data, GIS, and multicriteria analysis","authors":"Y. Halimi ,&nbsp;S. Halimi ,&nbsp;Z. Bouzid ,&nbsp;N. Ghellai","doi":"10.1016/j.enconman.2024.119176","DOIUrl":"10.1016/j.enconman.2024.119176","url":null,"abstract":"<div><div>The identification of appropriate locations for photovoltaic (PV) solar power plants presents a multifaceted challenge that entails a complex interplay of diverse criteria. Algeria, which has a clear advantage in becoming a major player in the field of solar energy production, has in recent years intensified programs aimed at taking full advantage of this potential. Therefore, in order to provide the necessary assistance to the government and all the operators wishing to install photovoltaic systems in this country, this paper aims to present a research methodology that combines Geographic Information System (GIS) analysis, Multi-Criteria Decision-Making (MCDM) techniques, and off-site measurements to identify the most suitable sites for off-grid PV facilities installation across Algeria. However, before reaching the main objective, a refined digital elevation model (DEM) was developed. In addition, monthly mean values of global daily horizontal and tilted irradiance for a typical meteorological year were calculated, facilitating the mapping of these two quantities over the 12 months. Finally, the annual sum of photovoltaic energy produced by a PV power plant with a total installed capacity of <span><math><mrow><mn>1</mn><mspace></mspace><mi>MWp</mi></mrow></math></span> was calculated, ranging from <span><math><mrow><mn>1535</mn><mspace></mspace><mi>MWh</mi><mo>/</mo><mi>MWp</mi></mrow></math></span> to <span><math><mrow><mn>2051</mn><mspace></mspace><mi>MWh</mi><mo>/</mo><mi>MWp</mi></mrow></math></span> per year depending on geographic location. The Analytic Hierarchy Process (AHP) was used to evaluate multiple criteria and prioritize the most suitable areas, classifying Algeria into seven distinct grades: “Somewhat suitable”, covering 36.4030% of the total country, followed by “Moderately suitable” at 32.4613% and “Very suitable” at 11.2877%. “Marginally suitable” lands comprise 15.8632%, while “Highly suitable” and “Minimally suitable” areas account for 2.0042% and 1.7342%, respectively. The “Extremely suitable” sites cover the smallest area at 0.2463% and are located primarily in the Southeast and East–Southeast regions. The outcome of this research is an updated Solar Atlas of Algeria and a high-resolution suitability map showing the spatio-temporal variability of PV potential across the country.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119176"},"PeriodicalIF":9.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic online learning framework for short-term wind power forecasting using ensemble bagging regression model","authors":"Arun Kumar Nayak ,&nbsp;Kailash Chand Sharma ,&nbsp;Rohit Bhakar ,&nbsp;Harpal Tiwari","doi":"10.1016/j.enconman.2024.119142","DOIUrl":"10.1016/j.enconman.2024.119142","url":null,"abstract":"<div><div>The increasing penetration of renewable energy sources, with a notable focus on wind power, within modern electricity grids requires computationally efficient and burden-free short-term wind power forecasting models. Traditional models generating prediction intervals are trained offline and thus deployed for prediction purposes. However, this approach cannot obtain interval forecasts from the most recent wind power observations. In contrast, combining multiple regression models through ensemble learning is recognised as a successful method for improving forecasting performance. By utilising the most recent observations and exploiting the strengths of multiple regression models, this article investigates an Online Ensemble Bagging Regression (OEBR) model for generating prediction intervals. Online gradient descent based optimisation algorithms capable of adaptive-depth calculation from a stream of observations are used here to address the problems with traditional batch learning frameworks. The proposed online learning framework is evaluated against other online learning frameworks using publicly accessible datasets. The results show the proposed model competes with the compared models regarding probabilistic metrics and energy estimations and outperforms computational time requirements for the same number of observations.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119142"},"PeriodicalIF":9.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142655898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient framework for energy management of microgrid installed in Aljouf region considering renewable energy and electric vehicles","authors":"Ahmed Fathy","doi":"10.1016/j.enconman.2024.119212","DOIUrl":"10.1016/j.enconman.2024.119212","url":null,"abstract":"<div><div>This paper proposes an efficient one-to-one-based optimizer as a new energy management method for a grid-connected microgrid in order to address both environmental and economic concerns. The suggested approach is distinguished by its robust exploration capabilities that allow the technique to reach the global solution and avoid local ones, along with its ease of deployment. The microgrid under consideration consists of conventional resources, microturbine, fuel cell, storage batteries, and electric vehicles, as well as renewable energy sources like photovoltaic and wind turbine. Real-time 24-hour solar irradiance, wind speed, and air temperature data of Sakaka, Aljouf region in Saudi Arabia located at 29° 58′ 15.13″N latitude and 40° 12′ 18.03″E longitude are utilized while the stochastic natures of renewable resources have been modeled using Beta and Weibull probability distribution functions. Various scenarios of renewable resources’ generations as well as electric vehicle’s charging states are analyzed. A thorough comparison is made with the published krill herd optimizer, in addition to other programmed algorithms such as grey wolf optimizer, Runge Kutta optimization, salp swarm algorithm, hippopotamus optimization algorithm, and Newton Raphson based optimizer. Also, the suggested approach is validated statistically through the use of Kruskal Wallis, Friedman, ANOVA, and Wilcoxon rank tests. With renewable resources working normally, the recommended strategy outperformed the published krill herd optimizer in terms of operating cost savings and emission reductions, which were 53.85 % and 46.62 %, respectively. While during the rated operation of renewable resources, the net savings and emission reductions were 10.14 % and 38.91 %, respectively. Additionally, the greatest cost savings during connecting electric vehicles at smart charging mode was 55.69 % as compared to the published approach. The suggested strategy can be recommended as an effective method for managing microgrid energy.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119212"},"PeriodicalIF":9.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cutting-edge biomass gasification technologies for renewable energy generation and achieving net zero emissions","authors":"Farooq Sher ,&nbsp;Saman Hameed ,&nbsp;Narcisa Smječanin Omerbegović ,&nbsp;Alexander Chupin ,&nbsp;Irfan Ul Hai ,&nbsp;Bohong Wang ,&nbsp;Yew Heng Teoh ,&nbsp;Magdalena Joka Yildiz","doi":"10.1016/j.enconman.2024.119213","DOIUrl":"10.1016/j.enconman.2024.119213","url":null,"abstract":"<div><div>Biomass gasification is a significant technology for the production of bioenergy. A deeper understanding of biomass gasification is crucial, especially regarding its role in bioenergy carbon capture and storage and its contribution to achieving net-zero emissions. This novel review encompasses gasification processes, novel design technologies, advanced syngas cleaning strategies, scalability challenges, techno-economic analysis, societal and environmental aspects of biomass gasification for achieving net-zero emissions. Biomass gasification typically occurs within temperatures (500 to 1000 °C), pressures (0.98 to 2.94 atm), S/B (0.3–1), residence time (few minutes), moisture content (below 35%) and with or without the presence of a catalyst. It is found that optimizing the gasification key parameters significantly reduces impurities content. Gasifier design affects tar content significantly: updraft gasifiers produce the most tar (about 100 g/Nm³), downdraft gasifiers the least (around 1 g/Nm³) and fluidized-bed gasifiers have intermediate levels (around 10 g/Nm³). Physical-mechanical methods achieve 99% efficiency but reduce energy conversion and generate hazardous waste. Thermal and catalytic cracking methods offer up to 98–100% efficiency, with nickel-based catalysts being highly effective. Biomass gasification has attained a Technology Readiness Level (TRL) of 8–9, demonstrating its feasibility for large-scale implementation. However, it incurs a 15% cost increase and requires additional advancements to address technical and economic challenges. Furthermore, converting syngas into valuable products is vital for achieving negative GHG emissions. Continued research is essential to enhance the overall efficacy of the gasification process. Developing innovative approaches that efficiently valorize all gasification by-products is crucial for enabling widespread adoption in the global market.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119213"},"PeriodicalIF":9.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating fuel cell power systems for coastal and inland waterway vessels: Technical and economic perspectives","authors":"Zhe Wang ,&nbsp;Haobo Tang ,&nbsp;Zhenhang Wu ,&nbsp;Yulong Ji ,&nbsp;Fenghui Han","doi":"10.1016/j.enconman.2024.119200","DOIUrl":"10.1016/j.enconman.2024.119200","url":null,"abstract":"<div><div>With the growing demand for sustainable shipping solutions, alternative energy sources and environmental protection technologies have become key areas of research. This study investigates the techno-economic feasibility of using hydrogen and ammonia fuels in fuel cell power systems for coastal and inland waterway vessels. Three system boundary frameworks were developed: one powered by a proton exchange membrane fuel cell using hydrogen, another by a solid oxide fuel cell using ammonia, and a comparative system using a traditional two-stroke diesel engine. A model of a fuel cell power system for coastal and inland waterway routes was developed for the “Han Hai V” container mother ship, considering operational conditions such as docking times, cargo space loss, and load variations on different routes. The model testing was set between Dalian Port and Yantai Port for coastal routes, and between Wuhan Port and Shanghai Port for inland routes. A comprehensive quantitative analysis of fuel consumption, greenhouse gas emissions, and economic benefits over the vessel’s lifespan was conducted. The results indicate that the new power system cases can reduce emissions by a maximum of 51.6 million tons on coastal routes and 116 million tons on inland routes. While hydrogen and diesel-powered systems show greater economic benefits in shorter routes, the economic gap between ammonia and these fuels narrows with increasing distances, highlighting ammonia’s potential for long-haul applications.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119200"},"PeriodicalIF":9.9,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomimetic low carbonization efficient solar-driven thermochemical energy storage reactor design inspired by the diatoms’ superior photosynthesis capacity","authors":"Jintao Song ,&nbsp;Yaping Fan ,&nbsp;Ziming Cheng ,&nbsp;Fuqiang Wang ,&nbsp;Xuhang Shi ,&nbsp;Jie Xu ,&nbsp;Jingyu Zhang ,&nbsp;Hongliang Yi ,&nbsp;Yong Shuai ,&nbsp;Hao Zhang","doi":"10.1016/j.enconman.2024.119224","DOIUrl":"10.1016/j.enconman.2024.119224","url":null,"abstract":"<div><div>Photon is the energy source that drives solar thermochemistry. Photon-based radiative transfer in the reactor space is an essential mode of energy transfer. However, there often exists mismatch between the radiative and chemical fields in direct solar thermochemical processes, which can lead to ultra-high temperature gradients and high carbonization rates. While, the vicious cycle that exists between high temperature gradients and higher carbonization rates could severely limit the thermochemical efficiency. To improve the efficiency and reduce the temperature gradient and carbonization, inspired by the superior performance of diatom photosynthesis, a biomimetic radiation-regulated reactor is proposed. The paper establishes multi-field model of steam methane reforming, and analyzes the energy conversion processes at pore-scale. In numerical analyses, compared to the conventional reactor, the biomimetic reactor enhances the light forward scattering in fore-end and the backward scattering in rear-end, which increases the light absorption efficiency by 6.8% and reduces the temperature gradient by 41.3%. In experimental investigation, the methane conversion and the solar-fuel efficiency of the biomimetic reactor is 48.6% and 44.0%, which is increased by 11.5% and 10.7% respectively. It also demonstrates high efficiency and stability under long operating conditions. The biomimetic reactor provides a new strategy for industrial solar-driven methane conversion.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119224"},"PeriodicalIF":9.9,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}