Next Energy最新文献

{"title":"Lithium-ion battery recycling evolution: Could entire cell regeneration be the next step?","authors":"Ayesha Tariq ,&nbsp;Qing Ai ,&nbsp;Yifan Zhu ,&nbsp;Katlyn Schmeltzer ,&nbsp;Tianyou Xie ,&nbsp;Jun Lou","doi":"10.1016/j.nxener.2024.100234","DOIUrl":"10.1016/j.nxener.2024.100234","url":null,"abstract":"<div><div>Lithium-ion batteries (LIBs) have experienced significant growth across various industries over the past decades. However, the disposal of the spent LIBs, which contributes to a substantial amount of solid waste, has become a rapidly escalating global issue. While numerous recycling techniques focus on recovering individual components of the battery, these oftentimes energy-intensive methods, despite yielding notable results, pose a significant environmental threat due to the generation of toxic by-products. In this review, we investigate the currently practiced industry-scale battery-recycling techniques along with a few lab-scale techniques that hold the potential to be scalable whilst ensuring environmental preservation. After a careful analysis, we steer the readers in the direction of exploring a new green method that targets the convenient and complete regeneration of the LIB.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100234"},"PeriodicalIF":0.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced thermal management with heat pipes in lithium-ion battery systems: Innovations and AI-driven optimization","authors":"Mehwish Khan Mahek ,&nbsp;Mohamad Ramadan ,&nbsp;Mohammed Ghazal ,&nbsp;Fahid Riaz ,&nbsp;Daniel S. Choi ,&nbsp;Mohammad Alkhedher","doi":"10.1016/j.nxener.2024.100223","DOIUrl":"10.1016/j.nxener.2024.100223","url":null,"abstract":"<div><div>Heat pipes (HP) have been extensively used for thermal management in many sectors as a flexible potential heat transfer mechanism, including laptop computer CPUs, projectors, solar collectors, and battery thermal management systems (BTMSs). This study reviews and compiles the latest advancements in using HPs for efficient thermal management of high-performance lithium-ion battery systems. This review examines the most recent BTMS that are based on HPs, with a particular emphasis on the role of artificial intelligence (AI) in optimizing thermal performance. It also addresses significant distinctions from prior research, including AI-driven predictive models and hybrid cooling techniques. A classification is created using various wick topologies, working fluids within a lithium-ion BTMS's temperature range, and their appropriate envelope materials. The instances of each one's application in the BTMS or potential uses in the future have been presented. HPs are divided into several categories depending on their form (tubular, flat, loop, etc.) and each variety is given thorough explanations, illustrations, and data on how it performed in various trials. Furthermore, extensive literature research reveals AI's role in fine-tuning operational parameters, crafting algorithms to predict core temperatures in HP systems, and employing advanced optimization and deep learning techniques for efficient and safe management of HP-cooled reactors under stringent power limitations. Moreover, hybrid cooling strategies, including air-cooled, liquid-cooled, phase change material (PCM) cooled, and thermoelectrically cooled HPs, are also highlighted. Future research work recommendations have been provided for several studies on HPs to cool lithium-ion batteries.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100223"},"PeriodicalIF":0.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catalytic ammonia cracking: Future of material chemistry research for sustainable hydrogen energy economy","authors":"Rituraj Dubey ,&nbsp;Rajasekhar Bhimireddi ,&nbsp;Youngil Lee ,&nbsp;Laxman Singh","doi":"10.1016/j.nxener.2024.100227","DOIUrl":"10.1016/j.nxener.2024.100227","url":null,"abstract":"<div><div>To date, no one can imagine our sustainable growth without developing efficient energy storage, utilization of renewable energies sources, transportation, energy saving. In order to look into the alternatives of traditional fossil fuels to renewable energy sources, in recent times, significant development carried out towards sustainable hydrogen production. Moreover, its physio-chemical characteristics create its transport and storage one of the major obstacles for its commercial-scale applications. To resolve this issue, ammonia, a gas of having large hydrogen quantity and energy density, has proved itself as a promising zero-carbon energy transporter for mass energy storage. Catalytic ammonia cracking has been used for hydrogen regeneration due to non-production of NOx. Herein, we have discussed about its various protocols to conceptuealize <em>“hydrogen-energy economy”</em> which is an integrated development of hydrogen production protocols, storage methods, and followed by utilization as energy through fuel cells.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100227"},"PeriodicalIF":0.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles","authors":"Yalun Li ,&nbsp;Kun Wang ,&nbsp;Chaojie Xu ,&nbsp;Yu Wu ,&nbsp;Liguo Li ,&nbsp;Yuejiu Zheng ,&nbsp;Shichun Yang ,&nbsp;Hewu Wang ,&nbsp;Minggao Ouyang","doi":"10.1016/j.nxener.2024.100233","DOIUrl":"10.1016/j.nxener.2024.100233","url":null,"abstract":"<div><div>With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100233"},"PeriodicalIF":0.0,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constructing hierarchical hollow microspheres with Co9S8-modified CoS nanosheets for high-performance sodium storage","authors":"Yamei Wang ,&nbsp;Rui Wu ,&nbsp;Xiaobin Niu ,&nbsp;Hanchao Li ,&nbsp;Jun Song Chen ,&nbsp;Wei Li","doi":"10.1016/j.nxener.2024.100230","DOIUrl":"10.1016/j.nxener.2024.100230","url":null,"abstract":"<div><div>Transition metal sulfides have drawn increasing attention as anode materials for sodium-ion batteries (SIBs) due to their high theoretical capacities. However, their practical application is still hindered by the rapid decay of capacity and severe volume variation during cycling. Herein, we constructed a hollow microspheres material composed of Co₉S₈-modified CoS nanosheets with the heterostructured interface through a one-step solvothermal method. When applied as the anode for SIBs, CoS/Co₉S₈ exhibited a superior specific capacity of 600 mAh g⁻¹ after 100 cycles at 0.5 A g⁻¹, and a remarkable cycling performance of 456 mAh g⁻¹ after 1500 cycles at 5 A g⁻¹. The outstanding electrochemical performance can be owed to the unique three-dimensional hollow hierarchical structure, which can effectively alleviate volume expansion during cycling. Moreover, density functional theory calculation further verified the improved electronic conductivity and structural stability because of the CoS/Co₉S₈ heterostructure.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100230"},"PeriodicalIF":0.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Moringa oleifera biodiesel and ethanol blends: Impact on fuel properties and mathematical modeling","authors":"Unmesh U. Thorve,&nbsp;Mazharuddin A. Quazi,&nbsp;Atul H. Bari,&nbsp;Debashis Kundu","doi":"10.1016/j.nxener.2024.100231","DOIUrl":"10.1016/j.nxener.2024.100231","url":null,"abstract":"<div><div>This research explores the synthesis and characterization of biodiesel derived from <em>Moringa oleifera</em> oil, specifically focusing on the effects of ethanol blending on its fuel properties. Utilizing <em>M. oleifera</em>, known for its high fatty acid content and oxidative stability, this study evaluates the production of <em>M. oleifera</em> biodiesel (MB) and the physicochemical properties of <em>M. oleifera</em> biodiesel—blended ethanol. The methodology encompasses thorough experimental procedures, from oil extraction to biodiesel production, including treatment steps like degumming, neutralization, and transesterification. Advanced mathematical modeling techniques, such as the Jouyban–Acree model, are employed to analyze the impacts of ethanol blending on key properties like viscosity and density. Ethanol blending significantly modifies these properties, with improvements of approximately 10% in viscosity and 8% in density, potentially allowing the fuel to meet or exceed conventional diesel standards. Thereby supporting the adoption of MB blends in energy applications for reduced environmental impact.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100231"},"PeriodicalIF":0.0,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on sodium emissions during the combustion of blends of biomass and high-ash content coal in an oxyfuel environment","authors":"Sachin K. S ,&nbsp;R.V. Ravikrishna ,&nbsp;Pratikash Panda","doi":"10.1016/j.nxener.2024.100232","DOIUrl":"10.1016/j.nxener.2024.100232","url":null,"abstract":"<div><div>Biomass combustion power generation has received significant attention as it is a carbon-neutral fuel. Countries with coal as the primary resources for power generation are adopting means of co-firing locally available biomass with coal to reduce carbon emissions. Depending upon the source of biomass particles, there are unique challenges associated with the combustion of biomass particles. However, emissions of alkali metals, chlorine, and sulfur-based gases during biomass combustion poses serious challenges in terms of the operability of power plants. In this work experimental investigations have been carried out to study the effect of co-firing different blends of high-ash content coal with biomass on sodium (Na) emissions in oxyfuel and non-oxyfuel environments. Two types of biomass have been studied: beechwood, a woody type of biomass, and paddy straw, an agro-residue-based biomass. Experiments on pellets composed of different blends of biomass and high-ash content coal have been conducted in an environment maintained at approximately 1110 K and 30% O₂/N₂/H₂O or 30% O₂/CO₂/H₂O. Temporal emission of Na has been measured quantitatively using the laser-induced breakdown spectroscopy technique. The effect of blending high-ash content coal with biomass, along with the impact of an oxyfuel environment in reducing Na emissions has been studied. A profound reduction in emissions of Na was found by blending high-ash content coal with biomass. High ash content coal was more effective in reducing Na emissions from coal-beechwood blends when compared with coal-paddy straw blends. Additionally, replacing N₂ with CO₂ in the combustion environment further reduces Na emissions from the coal–biomass blend pellets. As the concentration of high ash coal increased in the blend, the effective reduction in Na emissions due to CO₂ was observed to decrease. The effect of grain size used to make the fuel pellets of different blending ratios of paddy straw and high-ash content coal has also been explored. A finer grain size of paddy straw in the blend was more effective in reducing Na emissions. A mathematical model has been developed to identify the dependence of peak Na emission on different parameters during the combustion of coal–biomass blended pellets of different blending ratios of biomass and high-ash content coal.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100232"},"PeriodicalIF":0.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An efficient p-n type based (NiO/CeO2) hybrid composite photocatalyst and its performance for cationic dye degradation: Probable degradation pathways, optimization activities, and depth mechanism insights","authors":"Manoj Kumar,&nbsp;Atikur Rahman,&nbsp;Vijay Pratap Singh","doi":"10.1016/j.nxener.2024.100228","DOIUrl":"10.1016/j.nxener.2024.100228","url":null,"abstract":"<div><div>In this work, NiO, CeO₂, and NiO/CeO₂ nanoparticles were prepared by stepwise a simple co-precipitation method and subsequently hybridized with various ratios (1:1, 1:2, and 1:3) a facile mixing method. The prepared NiO/CeO₂ composite samples at diverse ratios were analyzed using various analytical techniques, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), UV–visible diffuse reflectance spectroscopy (UV-DRS), Field emission scanning electron microscopy (FE-SEM), X-ray photoelectron spectroscopy (XPS), photoluminescence (PL), and Raman spectroscopy. These methods were employed to investigate the chemical composition, morphological features, and optical characteristics of the composites, providing a comprehensive understanding of their properties and potential characteristics. The photocatalytic degradation of methylene blue (MB) was investigated by the prepared NiO/CeO₂ composite samples with changing parameters, such as pH, catalyst dose, initial dye concentration, and agitation time under UV and solar light irradiation. Kinetic investigations revealed that the photodegradation of MB followed a pseudo-first-order kinetic model. Amongst the tested catalysts NiO/CeO₂ (1:2) exhibited the highest photo-degradation of MB dye (97%) at pH around 10 in 60 min compared to 45% for neat NiO and 67% for pure CeO₂ respectively. Similarly, under natural solar conditions, it takes time but degrades 94% Of MB at 210 min. The radical detection test was carried out with trapping agents ethylene diamine tetra acetic acid (EDTA), isopropyl alcohol (IPA), and benzoquinone (BQ) to establish the vital role of hydroxyl radicals (OH•) in the photodegradation of dyes. Eventually, the high stability and recyclability of the NiO/CeO₂ (1:2) photocatalyst was confirmed after five consecutive runs. The mechanistic pathway of the dye degradation was explained by the scheme model based on p-n hetero-junction. Overall the study demonstrates the effectiveness of NiO/CeO₂ (1:2) heterojunctions in photocatalytic applications, for the removal of dye contaminants from wastewater using UV and visible light conditions.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100228"},"PeriodicalIF":0.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive modeling of hydrogen production and methane conversion from biomass-derived methane using machine learning and optimisation techniques","authors":"Adegboyega Bolu Ehinmowo,&nbsp;Bright Ikechukwu Nwaneri,&nbsp;Joseph Oluwatobi Olaide","doi":"10.1016/j.nxener.2024.100229","DOIUrl":"10.1016/j.nxener.2024.100229","url":null,"abstract":"<div><div>The growing demand for cleaner and more efficient energy solutions has necessitated the development of biomass conversion techniques for hydrogen production. Thermocatalytic methane decomposition produces hydrogen and solid carbon directly from methane without CO₂ emission. However, there is the need to optimise this process for better efficiency and improved hydrogen production from biomass sources. In this study, the integration of various machine learning algorithms with Bayesian optimisation, firefly algorithm, Levenberg-Marquardt, and differential evolution techniques were investigated for hydrogen production via thermocatalytic methane decomposition. The key process parameters studied include calcination temperature (450–600<!--> <!-->°C), time of calcination (3–8 h), specific surface area (5.4–249 m²/g), and pore volume (0.03–0.48 cm³/g); reduction temperature (500–700<!--> <!-->°C), time of reduction (1–5 h), and catalyst weight (0.05–1.00 g). The Bayesian-optimized CatBoost regressor model, with an R² of 96.3% and an RMSE of 0.064 showed the best performance. For the prediction of methane conversion, the Support Vector Regressor (SVR) model optimised with Firefly showed the best performance among other models with an R² value of 95.5% and root mean squared error (RMSE) of 0.070. CatBoost regressor predicted hydrogen yield of 87% close to the actual yield of 86%. The predicted methane conversion using the firefly-optimized support vector machine regressor was 72%, with the actual conversion being 68%. Model-to-feature relationship studies showed that catalyst weight and calcination time were the strongest predictors of hydrogen yield and methane conversion volume. The study hence established the great opportunity of integration of machine learning models with optimisation techniques in attempts to improve the prediction of hydrogen yield and methane conversion in processes for hydrogen production.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100229"},"PeriodicalIF":0.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A secure routing protocol for improving the energy efficiency in wireless sensor network applications for industrial manufacturing","authors":"Edeh Michael Onyema ,&nbsp;S. Kanimozhi Suguna ,&nbsp;B. Sundaravadivazhagan ,&nbsp;Rutvij H. Jhaveri ,&nbsp;Ugwuja Nnenna Esther ,&nbsp;Edeh Chinecherem Deborah ,&nbsp;K. Shantha Kumari","doi":"10.1016/j.nxener.2024.100219","DOIUrl":"10.1016/j.nxener.2024.100219","url":null,"abstract":"<div><div>Wireless sensor networks (WSNs) are critical in manufacturing contexts because they provide continuous tracking, digitization, and data collection. However, they frequently come under threat to security concerns and have limited energy resources due to the growing number of devices and data in Industrial manufacturing, thereby affecting the quality of data transfer. Consequently, previous works have concentrated on predicting novel methods and processes to offer security in WSNs but the threat persists. This study has significance because it solves two major issues in WSNs: security and energy efficiency. This study aims to improve network lifetime, save operational costs, and increase the security and reliability of industrial monitoring systems by proposing a secure and energy-efficient routing protocol. The study suggested a Machine Learning-based Secure Routing Protocol (MLSRP) for WSN to obtain better energy efficiency and overall performance to deliver an efficient tightened security for WSN in comparison to the existing approaches along with reduced data loss. According to a Multi-Criteria-based Decision Making (MCDM) paradigm, the MLSRP performs clustering, cluster head election, and data routing while analyzing certain network elements that affect the node, route, and data quality. The proposed framework was implemented and simulated using the NS2 simulator tool, and the outcomes are compared with the existing system for performance analysis. The proposed approach for secured and accurate data transfer achieves 98.78%. The study could have practical consequences for industries desiring efficient, secure, and long-lasting IoT solutions.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100219"},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}