Recycling of the Waste from Large-scale Pig Farms

The management mode, economic benefits and technology integration of large-scale pig breeding are superior to those of traditional pig breeding by scattered peasant households, and it has a significant agglomeration effect. However, the waste from large-scale pig farms are discharged in a concentrated manner, which aggravates environmental pollution and increases treatment difficulty, and improper disposal can lead to serious environmental problems. The main pollutants in the waste from large-scale pig farms are high-concentration organic pollutants, nitrogen and phosphorus. Meanwhile, they are also the main nutrients needed for the growth of plants, animals and microorganisms. By a series of key techniques, the waste from large-scale pig farms can be recycled as fertilizer, feed and energy.

Progress,challenges,and prospects of spent lithium-ion batteries recycling:A review

The recycling and reutilization of spent lithium-ion batteries(LIBs)have become an important measure to alleviate problems like resource scarcity and environmental pollution.Although some progress has been made,battery recycling technology still faces challenges in terms of efficiency,effectiveness and environmental sustainability.This review aims to systematically review and analyze the current status of spent LIB recycling,and conduct a detailed comparison and evaluation of different recycling processes.In addition,this review introduces emerging recycling techniques,including deep eutectic solvents,molten salt roasting,and direct regeneration,with the intent of enhancing recycling efficiency and diminishing environmental repercussions.Furthermore,to increase the added value of recycled materials,this review proposes the concept of upgrading recycled materials into high value-added functional materials,such as catalysts,adsorbents,and graphene.Through life cycle assessment,the paper also explores the economic and environmental impacts of current battery recycling and highlights the importance that future recycling technologies should achieve a balance between recycling efficiency,economics and environmental benefits.Finally,this review outlines the opportunities and challenges of recycling key materials for next-generation batteries,and proposes relevant policy recommendations to promote the green and sustainable development of batteries,circular economy,and ecological civilization.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Pyrometallurgical recycling of end-of-life lithium-ion batteries

The global importance of lithium-ion batteries(LIBs)has been increasingly underscored with the advancement of high-performance energy storage technologies.However,the end-of-life of these batteries poses significant challenges from environmental,economic,and resource management perspectives.This review paper focuses on the pyrometallurgy-based recycling process of lithium-ion batteries,exploring the fundamental understanding of this process and the importance of its optimization.Centering on the high energy consumption and emission gas issues of the pyrometallurgical recycling process,we systematically analyzed the capital-intensive nature of this process and the resulting technological characteristics.Furthermore,we conducted an in-depth discussion on the future research directions to overcome the existing technological barriers and limitations.This review will provide valuable insights for researchers and industry stakeholders in the battery recycling field.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Direct recycling of Li-ion batteries from cell to pack level:Challenges and prospects on technology,scalability,sustainability,and economics

Direct recycling is a novel approach to overcoming the drawbacks of conventional lithium-ion battery(LIB)recycling processes and has gained considerable attention from the academic and industrial sectors in recent years.The primary objective of directly recycling LIBs is to efficiently recover and restore the active electrode materials and other components in the solid phase while retaining electrochemical performance.This technology's advantages over traditional pyrometallurgy and hydrometallurgy are costeffectiveness,energy efficiency,and sustainability,and it preserves the material structure and morphology and can shorten the overall recycling path.This review extensively discusses the advancements in the direct recycling of LIBs,including battery sorting,pretreatment processes,separation of cathode and anode materials,and regeneration and quality enhancement of electrode materials.It encompasses various approaches to successfully regenerate high-value electrode materials and streamlining the recovery process without compromising their electrochemical properties.Furthermore,we highlight key challenges in direct recycling when scaled from lab to industries in four perspectives:(1)battery design,(2)disassembling,(3)electrode delamination,and(4)commercialization and sustainability.Based on these challenges and changing market trends,a few strategies are discussed to aid direct recycling efforts,such as binders,electrolyte selection,and alternative battery designs;and recent transitions and technological advancements in the battery industry are presented.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

Increasing Threat of Scarcity Prompts Rise in Water Recycling

In January 2018,construction wrapped on Salesforce Tower(Fig.1),a 61-story office building that now dominates the skyline of San Francisco,CA,USA.In addition to being the tallest building in the city,Salesforce Tower is the largest structure in the world with an onsite water recycling system.Built by the Australian com-pany Aquacell(Milton,NSW,Australia),the system cleans 113 m^(3)of sewage,sink,shower,and other wastewater each day for use in irrigation and flushing toilets,saving an estimated 35000 m?of water anmually[1].The building is just one of dozens in San Fran-cisco outitted with their own water recycling systems,thanks to a city mandate enacted in 2015[1].

Erratum to: Pyrometallurgical recycling of end -of-life lithium-ion batteries

Erratum to:International Journal of Minerals,Metallurgy and Materials Volume 31,Number 7,July 2024,Page 1554 https://doi.org/10.1007/s12613-024-2907-7 In this article,affiliation 1 has been erroneously given as Department of Materials Science and Engineering,Seoul 03722,Korea.

An efficient and mild recycling of waste melamine formaldehyde foams by alkaline hydrolysis

Melamine formaldehyde foam(MFF)generates many poisonous chemicals through the traditional recycling methods for organic resin wastes.Herein,a high MFF degradation ratio of ca.97 wt.%was achieved under the mild conditions(160℃)in a NaOH–H2O system with ammelide and ammeline as the main degradation products.The alkaline solvent had an obvious corrosion effect for MFF,as indicated by scanning electron microscopy(SEM).The reaction process and products distribution were studied by Fourier-transform infrared spectroscopy(FTIR),X-ray photoelectron spectroscopy(XPS),and ^(13)C nuclear magnetic resonance(NMR).Besides,the MFF degradation products that have the similar chemical structures and bonding performances to those of melamine can be directly used as the raw material for synthesis of melamine urea-formaldehyde resins(MUFs).Moreover,the degradation system demonstrated here showed the high degradation efficiency after reusing for 7 times.The degradation process generated few harmful pollutants and no pre-or post-treatments were required,which proves its feasibility in the safe removal or recovery of waste MFF.

Large-scale model testing of high-pressure grouting reinforcement for bedding slope with rapid-setting polyurethane

Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.

Fuel recycling feedback control via real-time boron powder injection in EAST with full metal wall

A feedback control of fuel recycling via real-time boron powder injection,addressing the issue of continuously increasing recycling in long-pulse plasma discharges,has been successfully developed and implemented on EAST tokamak.The feedback control system includes four main parts:the impurity powder dropper(IPD),a diagnostic system measuring fuel recycling level represented by D_(α)emission,a plasma control system(PCS)implementing the Proportional Integral Derivative(PID)algorithm,and a signal converter connecting the IPD and PCS.Based on this control system,both active control and feedback control experiments have recently been performed on EAST with a full metal wall.The experimental results show that the fuel recycling can be gradually reduced to lower level as PCS control voltage increases.In the feedback control experiments,it is also observed that the D_(α)emission is reduced to the level below the target D_(α)value by adjusting boron injection flow rate,indicating successful implementation of the fuel recycling feedback control on EAST.This technique provides a new method for fuel recycling control of long pulse and high parameter plasma operations in future fusion devices.

Seismic behavior of large-scale FRP–recycled aggregate concrete–steel columns with shear connectors

The application of fi ber-reinforced polymer (FRP) composites for the development of high-performance composite structural systems has received signifi cant recent research attention. A composite of FRP–recycled aggregate concrete (RAC)–steel column (FRSC), consisting of an outer FRP tube, an inner steel tube and annular RAC fi lled between two tubes, is proposed herein to facilitate green disposal of demolished concrete and to improve the ductility of concrete columns for earthquake resistance. To better understand the seismic behavior of FRSCs, quasi-static tests of large-scale basalt FRSCs with shear connectors were conducted. The infl uence of the recycled coarse aggregate (RCA) replacement percentage, shear connectors and axial loading method on the lateral load and deformation capacity, energy dissipation and cumulative damage were analyzed to evaluate the seismic behavior of FRSCs. The test results show that FRSCs have good seismic behavior, which was evidenced by high lateral loads, excellent ductility and energy dissipation capacity, indicating RAC is applicable in FRSCs. Shear connectors can signifi cantly postpone the steel buckling and increase the lateral loads of FRSCs, but weaken the deformation capacity and energy dissipation performance.

Multi-Component Resource Recycling from Waste Light-Emitting Diode Under Hydrothermal Condition:Plastic Package Degradation,Speciation of Nano-TiO_(2),and Environmental Impact Assessment

Light emitting diodes(LEDs)have accounted for most of the lighting market as the technology matures and costs continue to reduce.As a new type of e-waste,LED is a double-edged sword,as it contains not only precious and rare metals but also organic packaging materials.In previous studies,LED recycling focused on recovering precious and strategic metals while ignoring harmful substances such as organic packaging materials.Unlike crushing and other traditional methods,hydrothermal treatment can provide an environment-friendly process for decomposing packaging materials.This work developed a closed reaction vessel,where the degradation rate of plastic polyphthalamide(PPA)was close to 100%,with nano-TiO_(2)encapsulated in plastic PPA being efficiently recovered,while metals contained in LED were also recycled efficiently.Besides,the role of water in plastic PPA degradation that has been overlooked in current studies was explored and speculated in detail in this work.Environmental impact assessment revealed that the proposed recycling route for waste LED could significantly reduce the overall environmental impact compared to the currently published processes.Especially the developed method could reduce more than half the impact of global warming.Furthermore,this research provides a theoretical basis and a promising method for recycling other plastic-packaged e-waste devices,such as integrated circuits.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Simultaneous purification of minor components in natural products using twin-column recycling chromatography with a step solvent gradient

The isolation of minor components from complex natural product matrices presents a significant challenge in the field of purification science due to their low concentrations and the presence of structurally similar compounds.This study introduces an optimized twin-column recycling chromatography method for the efficient and simultaneous purification of these elusive constituents.By introducing water at a small flowing rate between the twin columns,a step solvent gradient is created,by which the leading edge of concentration band would migrate at a slower rate than the trailing edge as it flowing from the upstream to downstream column.Hence,the band broadening is counterbalanced,resulting in an enrichment effect for those minor components in separation process.Herein,two target substances,which showed similar peak position in high performance liquid chromatography(HPLC)and did not exceed 1.8%in crude paclitaxel were selected as target compounds for separation.By using the twin-column recycling chromatography with a step solvent gradient,a successful purification was achieved in getting the two with the purity almost 100%.We suggest this method is suitable for the separation of most components in natural produces,which shows higher precision and recovery rate compared with the common lab-operated separation ways for natural products(thin-layer chromatography and prep-HPLC).

Development of sustainable and efficient recycling technology for spent Li-ion batteries: Traditional and transformation go hand in hand

Clean and efficient recycling of spent lithium-ion batteries(LIBs)has become an urgent need to promote sustainable and rapid development of human society.Therefore,we provide a critical and comprehensive overview of the various technologies for recycling spent LIBs,starting with lithium-ion power batteries.Recent research on raw material collection,metallurgical recovery,separation and purification is highlighted,particularly in terms of all aspects of economic efficiency,energy consumption,technology transformation and policy management.Mechanisms and pathways for transformative full-component recovery of spent LIBs are explored,revealing a clean and efficient closed-loop recovery mechanism.Optimization methods are proposed for future recycling technologies,with a focus on how future research directions can be industrialized.Ultimately,based on life-cycle assessment,the challenges of future recycling are revealed from the LIBs supply chain and stability of the supply chain of the new energy battery industry to provide an outlook on clean and efficient short process recycling technologies.This work is designed to support the sustainable development of the new energy power industry,to help meet the needs of global decarbonization strategies and to respond to the major needs of industrialized recycling.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.