Search Results (375)

This study investigates the sustainable production of NdFeB permanent magnets using powder extrusion molding (PEM) with in situ magnetic alignment, utilizing recycled powder from an end-of-life (Eol) wind turbine magnet obtained via hydrogen processing of magnetic scrap (HPMS). Finite Element Method (FEM) simulations were conducted to design and optimize alignment tool geometries and magnetic field parameters. A key challenge in the PEM process is achieving effective particle alignment while the continuous strand moves through the magnetic field during extrusion. To address this, extrusion experiments were performed using three different alignment tool geometries and varying magnetic field strengths to determine the optimal configuration for particle alignment. The experimental results demonstrate a high degree of alignment (B_r/J_s = 0.95), exceeding the values obtained with PEM without an external magnetic field (0.78). The study confirms that optimizing the alignment tool geometry and applying sufficiently strong magnetic fields during extrusion enable the production of anisotropic NdFeB permanent magnets without post-machining, providing a scalable route for permanent magnet recycling and manufacturing. Moreover, PEM with in situ magnetic particle alignment allows for the continuous fabrication of near-net-shape strands with customizable cross-sections, making it a scalable approach for permanent magnet recycling and industrial manufacturing. Full article

Reducing gear noise in electric vehicle (EV) drivetrains is crucial due to the absence of internal combustion engine noise, making even minor acoustic disturbances noticeable. Manufacturing parameters significantly influence gear-generated noise, yet traditional analytical methods often fail to predict these complex relationships accurately. This research addresses this gap by introducing a data-driven approach using machine learning (ML) to predict gear noise levels from manufacturing and sensor-derived data. The presented methodology encompasses systematic data collection from various production stages—including soft and hard machining, heat treatment, honing, rolling tests, and end-of-line (EOL) acoustic measurements. Predictive models employing Random Forest, Gradient Boosting (XGBoost), and Neural Network algorithms were developed and compared to traditional statistical approaches. The analysis identified critical manufacturing parameters, such as surface waviness, profile errors, and tooth geometry deviations, significantly influencing noise generation. Advanced ML models, specifically Random Forest, XGBoost, and deep neural networks, demonstrated superior prediction accuracy, providing early-stage identification of gear units likely to exceed acceptable noise thresholds. Integrating these data-driven models into manufacturing processes enables early detection of potential noise issues, reduces quality assurance costs, and supports sustainable manufacturing by minimizing prototype production and resource consumption. This research enhances the understanding of gear noise formation and offers practical solutions for real-time quality assurance. Full article

High-quality end-of-life care (EoLC) is a critical yet often underemphasised component of oncology care. Several shortcomings in the delivery of EoLC for oncology patients in our centre during the COVID-19 pandemic were identified in our initial 2021 audit. In 2022, we introduced a care of dying patients proforma, an EoLC quality checklist, targeted education and training for staff, and an expanded end-of-life (EoL) committee. This re-audit aimed to review how these changes impacted on the care received by patients in a tertiary cancer centre. A second retrospective re-audit of patients who died between 11 July 2022 and 30 April 2023 was performed to assess quality of EoLC using the Oxford Quality indicators. A total of 72 deaths occurred over the audit period. Quality of EoLC improved significantly when compared to the initial audit (χ² (3, n = 138) = 9.75, p = 0.021). Exploration of patients’ wishes was documented in 48.8% and referral to pastoral care was documented in 68.3%, from 24.2% and 10.6%, respectively. The proportion of patients receiving poor EoLC reduced from 21.2% to 8.3%. Our study demonstrates the benefits of simple interventions, the importance of re-audit, and the role of ongoing interdisciplinary commitment to improving EoLC for our patients. Full article

The concept of the circular economy aims to develop systems for reusing, recovering, and recycling products and services, pursuing both economic growth and sustainability. In many countries, legislation has been enacted to create frameworks ensuring environmental protection and fostering initiatives to implement the circular economy across various sectors. The wind energy industry is no exception, with industries and institutions adopting strategies to address the forthcoming challenge of repowering or dismantling a significant quantity of wind turbines in the coming years reaching a total of global wind power capacity by 2024. This also involves managing the resulting waste, which includes materials with high economic value as well as others that have considerable environmental impacts but that can be reused, recycled, or converted. In parallel, the research activity in this field has increased significantly in response to this challenge, leading to a vast body of work in the literature, especially in the last three years. The aim of this paper is to conduct a bibliometric study to provide a global perspective on the current literature in the field, covering the period from 2009 to 2024. A total of 670 publications were retrieved from Web of Science and Scopus, with 57% of them published in the last three years, highlighting the growing interest in the field. This study analyzes the research product, the most relevant journal, the most cited authors and institutions, their collaborative patterns, emerging trends, and gaps in the literature. This contribution will provide an up-to-date analysis of the field, fostering better understanding of the direction of the research and establishing a solid foundation for future studies Full article

Lithium-ion batteries (LiBs) are utilized in numerous applications due to advancements in technology, and the recovery of end-of-life (EoL) LiBs is imperative for environmental and economic reasons. Pyrometallurgical and hydrometallurgical methods have been used in the recovery of metals such as Li, Co, and Ni in the EoL LiBs. Hydrometallurgical methods, which have been demonstrated to exhibit higher recovery efficiency and reduced energy consumption, have garnered increased attention in recent research. Inorganic acids, including HCl, HNO₃, and H₂SO₄, as well as organic acids such as acetic acid and citric acid, are employed in the hydrometallurgical recovery of these metals. It is imperative to acknowledge the environmental hazards posed by these acids. Consequently, solvometallurgical processes, which involve the use of organic solvents with minimal or no water, are gaining increasing attention as alternative or complementary techniques to conventional hydrometallurgical processes. In the context of solvent systems that have been examined for a range of solvometallurgical methods, deep eutectic solvents (DESs) have garnered particular interest due to their low toxicity, biodegradable nature, tunable properties, and efficient metal recovery potential. In this study, the leaching process of black mass containing graphite, LCO, NMC, and LMO was carried out in a short time using the ternary DES system. The ternary DES system consists of choline chloride (ChCl), glycolic acid (GLY), and ascorbic acid (AA). As a result of the leaching process of cathode powders in the black mass without any pre-enrichment process, Li, Co, Ni, and Mn elements passed into solution with an efficiency of over 95% at 60 °C and within 1 h. Moreover, the kinetics of the leaching process was investigated, and Density Functional Theory (DFT) calculations were used to explain the leaching mechanism. Full article

This study analyses the greenhouse gas reduction potential of different end-of-life (EoL) strategies based on a case study of light electric vehicles (LEVs). Using a shared electric moped scooter as a reference, four EoL scenarios are evaluated in a comparative life cycle assessment (LCA). The modelling of the scenarios combines different R-strategies (e.g., recycling, reusing, and repurposing) regarding both the vehicle itself and the battery. German and EU regulations for vehicle and battery disposal are incorporated, as well as EU directives such as the Battery Product Pass. The global warming potential (GWP₁₀₀) of the production and EoL life cycle stages ranges from 644 to 1025 kg CO₂ eq among the four analysed scenarios. Landfill treatment led to the highest GWP₁₀₀, with 1.47 times higher emissions than those of the base scenario (status quo treatment following EU directives), while increasing component reuse and repurposing the battery cells achieved GWP₁₀₀ reductions of 2.8% and 7.8%, respectively. Overall, the importance of implementing sustainable EoL strategies for LEVs is apparent. To achieve this, a product design that facilitates EoL material and component separation is essential as well as the development of political and economic frameworks. This paper promotes enhancing the circularity of LEVs by combining the LCA of EoL strategies with eco-design considerations. Full article

This study presents a novel approach to the end-of-line (EoL) quality inspection of brushless DC (BLDC) motors by implementing a deep learning model that combines MEL diagrams, convolutional neural networks (CNNs) and bidirectional gated recurrent units (BiGRUs). The suggested system utilizes raw vibration and sound signals, recorded during the EoL quality inspection process at the end of an industrial manufacturing line. Recorded signals are transformed directly into Mel-frequency spectrograms (MFS) without pre-processing. To remove non-informative frequency bands and increase data relevance, a six-step data reduction procedure was implemented. Furthermore, to improve fault characterization, a reference spectrogram was generated from healthy motors. The neural network was trained on a highly imbalanced dataset, using oversampling and Bayesian hyperparameter optimization. The final classification algorithm achieved classification metrics with high accuracy (99%). Traditional EoL inspection methods often rely on threshold-based criteria and expert analysis, which can be inconsistent, time-consuming, and poorly scalable. These methods struggle to detect complex or subtle patterns associated with early-stage faults. The proposed approach addresses these issues by learning discriminative patterns directly from raw sensor data and automating the classification process. The results confirm that this approach can reduce the need for human expert engagement during commissioning, eliminate redundant inspection steps, and improve fault detection consistency, offering significant production efficiency gains. Full article

As sensitive parts of the water treatment process, reverse osmosis (RO) membranes are the most important for desalination and wastewater treatment. But the performance of RO membranes deteriorates over time due to fouling, necessitating frequent replacements. One of the environmental challenges is the disposal of End-of-Life (EoL) RO membranes, which are made of non-biodegradable polymers. The reuse of EoL membranes as a sustainable approach for waste saving and resource efficiency has recently attracted considerable attention. The present work provides a comprehensive overview of the strategies for reusing EoL RO membranes as sustainable alternatives to conventional disposal methods. Furthermore, the fundamental principles of RO technology, the primary types and impacts of membrane fouling, and advanced cleaning and regeneration techniques are discussed. The conversion of EoL membranes into nanofiltration (NF), ultrafiltration (UF), and forward osmosis (FO) membranes is also covered in this review, as well as their uses in brackish water desalination, dye/salt separation, groundwater treatment, and household wastewater reuse. Environmental and economic benefits, as well as technical, social, and regulatory challenges, are also discussed. Finally, the review highlights innovative approaches and future directions for incorporating EoL membrane reuse into circular economy models, outlining its potential to improve sustainability and reduce operational costs in water treatment systems. Full article

Italy strives to meet its renewable energy targets for 2030 and 2050, with photovoltaic (PV) technology playing a central role. However, the push for increased solar adoption, spurred by past incentive schemes such as “Conto Energia” and “Superbonus 110%”, raises long-term challenges related to PV waste management. In this study, we present a multi-scale approach to forecast End-of-Life (EoL) PV waste across Italy’s 20 regions, aiming to support national circular economy strategies. Historical installation data (2008–2024) were collected and combined with socio-economic and energy-related indicators to train a Backpropagation Neural Network (BPNN) for regional PV capacity forecasting up to 2050. Each model was optimised and validated using R² and RMSE metrics. The projections indicate that current trends fall short of meeting Italy’s decarbonisation targets. Subsequently, by applying a Weibull reliability function under two distinct scenarios (Early-loss and Regular-loss), we estimated the annual and regional distribution of PV panels reaching their EoL. This analysis provides spatially explicit insights into future PV waste flows, essential for planning regional recycling infrastructures and ensuring sustainable energy transitions. Full article

The rapid growth of the wind energy sector has led to a rising number of retired wind turbine blades (RWTBs) globally, posing significant environmental and logistical challenges for sustainable waste management. Handling enormous RWTBs at their end of life (EoL) has a significant negative impact on resource conservation and the environment. Conventional disposal methods, such as landfilling and incineration, raise environmental concerns due to the non-recyclable composite material used in blade manufacturing. This study explores the upcycling potential of RWTBs as innovative construction materials, addressing both waste reduction and resource efficiency in the construction industry. By exploring recent advancements in recycling techniques, this research highlights applications such as structural components, lightweight aggregates for concrete, and reinforcement elements in asphalt pavements. The key findings demonstrate that repurposing blade-derived materials not only reduces landfill dependency but also lowers carbon emissions associated with conventional construction practices. However, challenges including material compatibility, economic feasibility, and standardization require further investigation. This study concludes that upcycling wind turbine blades into construction materials offers a promising pathway toward circular economy goals. To improve technical methods and policy support for large-scale implementation, it recommends collaboration among different fields, such as those related to cementitious and asphalt materials. Full article

EU accession countries, including the Republic of Serbia, are under growing pressure to align their plastic waste management systems with EU environmental directives. Despite this, significant challenges remain, including inadequate infrastructure, a limited recycling capacity, and weak enforcement mechanisms. This study employs life cycle assessment (LCA) to evaluate the environmental impacts of polyethylene terephthalate (PET) packaging waste in Serbia, focusing on three end-of-life scenarios (EoL): landfilling, recycling, and incineration. Using GaBi Professional v6.0 software and the ReCiPe 2016 methodology, the results indicate that mismanaged PET waste contributes notably to terrestrial ecotoxicity (3.69 kg 1.4-DB eq.) and human toxicity (non-cancer) (2.36 kg 1.4-DB eq.). In 2023, 14,967.8 tons of PET were collected by authorized operators; however, unreported quantities likely end up in landfills or the natural environment. Beyond the quantified LCA results, this study highlights microplastic pollution as an emerging environmental concern. It advocates for the development of Serbia-specific characterization factors (CFs) for PET microplastics, incorporating localized fate, exposure, and effect data. Tailored CFs would enhance the precision of impact assessments for Serbian terrestrial ecosystems, contributing to more effective, evidence-based environmental policies. These insights are crucial for supporting Serbia’s transition to sustainable waste management and for meeting EU environmental standards. Full article

Research on smartphone lifespan is of high interest nowadays due to the growing number of smartphone users and the environmental impact associated with device turnover. Although the concept of smartphone lifespan varies in the literature, research defines the in-use lifespan as the period during which the user finds the device useful, i.e., until it becomes obsolete. Smartphone obsolescence is primarily influenced by both technological and psychological factors, making them the key determinants of the device’s lifespan. For this reason, it is essential to dedicate more research efforts to understanding smartphone lifespan and to developing clear guidelines and policies that can shift users’ perceptions, thereby improving lifespan estimation and encouraging prolonged use. This review synthesizes EU regulations and scientific literature, gathering comprehensive knowledge on key segments and events that affect the in-use lifespan of smartphones. Based on the data, several statistics were generated to provide a better understanding of the term “lifespan,” its multiple estimations, obsolescence issues, and factors affecting the estimated length of the in-use lifespan. Additionally, the research material was used to design a smartphone lifecycle model within the business process management software ARIS and to identify the End of Life (EoL) phase accordingly. Full article

Background/Objectives: End-of-life (EOL) HIV cure research, which studies HIV persistence through pre- and post-mortem tissue collection, has focused primarily on people living with HIV (PLWH) with a prognosis of six months or less. However, the perspectives of long-term survivors (LTS) diagnosed before the advent of effective antiretroviral treatment (ART) remain underexplored. Understanding their motivations and concerns about EOL cure research is essential for creating inclusive and ethical research frameworks. Methods: Between 2023 and 2024, we conducted in-depth qualitative interviews with 16 PLWH aged 60 and older from diverse backgrounds across the United States, recruited through community-based organizations and HIV networks. We used inductive thematic analysis to explore LTS’ perspectives on EOL HIV research. Results: Participants included cisgender men (56.25%) and women (43.75%) with diverse racial identities. While participants supported EOL HIV cure research, their willingness to participate varied, influenced by awareness, logistics, and ethical concerns. Altruism-motivated participation, but misconceptions about procedures and concerns over bodily integrity represented potential barriers. Some viewed blood draws and leukaphereses as routine, while others expressed hesitancy with biopsies and post-mortem tissue retrieval. HIV stigma, historical mistrust, and cultural beliefs also played a role in willingness to participate. LTS emphasized the need for decentralized research sites, travel support, and financial safeguards. Conclusions: To include LTS in EOL HIV cure research, a community-driven approach is needed, focusing on clear communication, ethical considerations, logistical support, and linkages to EOL care. Addressing misconceptions and building trust, particularly within groups traditionally underrepresented in research, is essential to expanding participation. Full article

The transportation sector is considered the number one consumer of tires worldwide. At present, 1.1 billion vehicles relying on this industry, although this number is increasing significantly following supply chain demands and the rapid economic growth. Among the main selection standards for fleet-operating enterprises are the quality, durability, and sustainability of tires, in efforts to ensure efficiency and safety for continuous operations. Lifecycle assessments (LCAs) are the optimal solution to optimize tire usage for extended performance and increased lifespan. In this paper, we developed a prediction model aiming at managing tires during the middle-of-life phase (use phase) while minimizing the negative environmental impact. Full article

Introduction: Racial and ethnic disparities in end-of-life (EOL) cancer care persist, leading to lower rates of advance care planning (ACP), reduced access to palliative care, and poorer patient outcomes for minority populations. While previous research has documented these inequities, less is known about the specific interventions developed to address them, necessitating a comprehensive review of existing strategies aimed at improving EOL care for racial and ethnic populations. The objective of this scoping review is to examine the extent and characteristics of interventions and their outcomes designed to address racial and ethnic disparities in EOL cancer care in the United States. Methods: A comprehensive search of EOL cancer care interventions for minority populations was conducted in Ovid MEDLINE, CINAHL with Full Text (EBSCOhost), and Scopus (Elsevier) in September 2024. Two independent reviewers screened titles, abstracts, and full texts following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, with inclusion limited to studies conducted in the US and published in English. Results: Of 3104 screened studies, 10 met the inclusion criteria. Participants enrolled were only from Latino (n = 6 studies) or Black (n = 4 studies) populations. We identified four types of interventions, including communication skills for patients, caregivers, researchers, and clinicians (n = 2), education programs for patients (n = 1), navigation and support programs for patients and caregivers (n = 3), and training programs for health workers and community leaders (n = 4). The most effective interventions were those that addressed linguistic barriers, integrated cultural values, and involved trusted community figures. Faith-based models were particularly successful among African American patients, while bilingual navigation and family-centered ACP interventions had the greatest impact in Latino populations. Conclusions: This review highlights (1) the importance of culturally tailored interventions for specific minority populations and (2) the limited number of such interventions, which primarily target only the largest minority groups. Full article