Sustainable Manufacturing Research Articles

Investigation of the Effect of Al2O3 Nanoparticle-Added MQL Lubricant on Sustainable and Clean Manufacturing

In this study, in order to improve the characteristics of the vegetable-based cutting fluids used in the MQL technique and increase the machining performance of MQL and its positive effects on sustainable manufacturing, the effects of the MQL method with nano-Al2O3 additives on surface roughness (Ra) and cutting temperature (Ctt) were examined through turning experiments carried out by adding nano-Al2O3 to the vegetable-based cutting fluid. For this purpose, machining tests were carried out on hot work tool steel alloyed with Cr-Ni-Mo that has a delivery hardness of 45 HRC. In hard machining experiments, three techniques for cooling and lubricating (dry cutting, MQL, and nano-MQL), three cutting speeds (V) (100, 130, 160 m/min), three feed rates (f) (0.10, 0.125, and 0.15 mm/rev), and two different ceramic cutting tools (uncoated and TiN-coated with PVD methods) were used as control factors. For Ra, the nano-MQL method provided an average of 21.49% improvement compared to other cooling methods. For Ctt, this rate increased to 26.7%. In crater wear areas, the nano-MQL method again exhibited the lowest wear values, decreasing performance by approximately 50%. The results of this research showed that the tests conducted using the cooling of nano-MQL approach produced the best results for all output metrics (Ra, Ctt, and crater wear).

Comparison of machining forces, power consumption, and specific cutting energy in tools with grooved cutting edges for sustainable manufacturing

ABSTRACT The ease at which a material is cut or formed to the required shape is defined as machinability. Higher machinability, superior productivity, and sustainability are the three key parameters used to evaluate machining performance. The tools designed to support these performance parameters are intended to consume less power, generate lower forces, produce surfaces with lesser roughness, and provide a higher tool life. Hence, the purpose of the investigation is to compare the efficiency of milling inserts with grooves (serrations) on the cutting edges (also called porcupine edges) in machining AISI 304 austenitic stainless steel and AISI 4140 low-alloy, medium-carbon steel materials. The metal cutting test results show that the milling inserts with grooved cutting edges consumed 8% to 17% less power and specific cutting energy, and exhibited 7% to 16% lower resultant force in AISI 304 steel. Similarly, 9% to 15% less power consumption, specific cutting energy, and 10% to 14% lower resultant force than the tools with straight cutting edges were also observed in AISI 4140 steel. The reduction in cutting power, specific cutting energy, and forces is credited to the decreased contact length between the tool edge and workpiece, providing lesser resistance in the inserts with grooved cutting edges.

Investigating the role of brand love on brand advocacy in the local eco hijab fashion industry

Purpose The study analyzes brand love in local eco-hijab fashion (LEHF) by discussing the value of collectivism, fashion consciousness, environmental value, religiosity and brand advocacy. LEHF becomes the trend pursued by consumers, so this can create market opportunities to optimize marketing strategies. The focus on LEHF in a sustainable fashion would allow local businesses to develop local values-based companies. This study uses the value attitude-behavior model to analyze data. Design/methodology/approach This research uses a quantitative survey to obtain data. The questionnaire is spread to 300 respondents with a purposive sampling approach, especially respondents who have worn LEHF. Findings This study shows that collectivism values, fashion consciousness, environmental values and religiosity influence brand love, while brand love influences brand advocacy related to LEHF. On the other hand, consumers are the target market with a fashion consciousness to follow the trend of hijab clothes. This also shows they wear clothes to fulfill religious values while prioritizing the latest styles. Research limitations/implications Since this study focuses on LEHF, this product is only relevant to hijab fashion. This takes into account the potential of Muslim-dominated Indonesian society. The fashion category can be enlarged to include more local products in future studies. A large selection of goods may promote greater use of regional interests. Practical implications For business actors, particularly micro and medium firms that are just starting to grow to support the local hijab fashion industry company, this research has managerial implications. This presents a chance for business actors to improve the local economy and opens doors for establishing more employment possibilities. The growth of the regional hijab fashion market offers an opportunity to satisfy the demands of customers who favor regional goods. Brand love in LEHF may foster business revenue growth and help local firms compete favorably with international brands. Marketers for LEHF are anticipated to intensify their efforts to advance socialism, the environment and fashion sensibility. Additionally, LEHF marketers emphasize the importance of religiosity when promoting their products to the target population. Marketers are also aware that the study’s environment is Indonesia, which has 90% Muslim population. Marketers have an excellent opportunity to maximize this scenario. Social implications This study also had social implications. The goal of producing locally made eco-hijabs is to benefit nearby communities and the environment. This aligns with the more general objectives of ethical and sustainable fashion. Sustainable methods are used in production, such as using eco-friendly colors, water conservation and waste reduction. Sustainable manufacturing methods are designed to reduce their adverse effects on the environment and encourage ethical production. Empowerment and community engagement may be involved in the manufacturing of locally-made eco-hijabs. This can entail educating and hiring regional craftspeople or incorporating neighborhood residents in manufacturing. Originality/value The study focuses on religiosity and environmental value to further analyze its influence on LEHF. The context of the products analyzed in this study is LEHF, which prioritized local production and strengthened local wisdom through pro-environment. The study used the VAB (value, attitude, behavior) model to analyze the concept.

Computer big data technology in additive manufacturing and product design in sustainable manufacturing

Computer big data technology in additive manufacturing and product design in sustainable manufacturing

Digital twins for environmentally sustainable and circular manufacturing sector: visions from industry professionals

ABSTRACT Traditional make-use-dispose operations are no longer an option in the manufacturing sector – companies face mounting sustainability pressures and incentives to move towards circular economy (CE) operations. Accordingly, they must implement new technologies to maintain competitiveness in the transition. One potential tool in navigating the change is the digital twin (DT). Previous research on DTs has largely focused on technological prerequisites, devoting less attention to their business and sustainability aspects. To fill the gap, this qualitative research provides an overview of sustainability pressures in manufacturing sector and examines how DTs can promote environmentally sustainable business and circularity. The results indicate that external pressures, such as stakeholder expectations, competition, ongoing megatrends, and regulations, push companies towards better sustainability, accompanied by employee expectations and internal willingness. The results also reveal a vast potential for DTs with sustainability and CE, especially in product design, use, and operation and at the decommissioning and renewal stages.

Enhancing end-of-life product recyclability through modular design and social engineering optimiser

Amidst the thriving landscape of manufacturing, the vision of sustainability in Industry 5.0 is becoming increasingly significant. The implementation of recycling represents a crucial step in the pursuit of sustainability, particularly in light of the mounting challenge posed by the proliferation of end-of-life (EOL) products. Addressing this challenge, we propose a novel Design for Modular Recyclability (DFMR) approach aimed at facilitating the recycling of EOL products. Our study develops a multi-objective optimisation model with a focus on maximising green recyclability and independence while minimising aggregation. We introduce an innovative Social Engineering Optimiser (SEO) to simulate behavioural patterns in complex environments, aiding in identifying and implementing effective strategies for optimal or near-optimal results in diverse scenarios. The practical effectiveness of the proposed models and algorithms is demonstrated by applying them to a real-life case study in an internal combustion engine, followed by performance comparisons with existing well-established multi-objective optimisation algorithms. The findings of our study demonstrate the efficacy of the proposed DFMR model, offering a novel approach for decision-makers to undertake EOL product recovery. This contributes to the further exploration of complex and promising paths towards sustainable manufacturing and green production that are more in line with Industry 5.0.

Artificial Neural Network Modeling to Predict Electrical Conductivity and Moisture Content of Milk During Non-Thermal Pasteurization: New Application of Artificial Intelligence (AI) in Food Processing

This study proposed applying artificial intelligence (AI) to predict the actual electrical conductivity (EC) of raw and pasteurized milk using moderate electric field (MEF) based on the electric field strength (EFS) and mass flow rate (MFR) along with modeling moisture content (MC) based on the EC. To this end, an artificial neural network (ANN) was implemented for conventionally (CP) and non-thermally (NP) pasteurized milk. The findings indicated no significant difference (p > 0.05) between the experimental and predicted data for EC and MC. The MFR and EFS affected the actual EC. The raw milk samples had an EC of 0.468812–0.46913 S/m and MC of 87.3218–87.35941%, while these values in NP pasteurized milk were 0.457441–0.638224 S/m and 87.33986–87.40851%. With correlation coefficients (R) of 0.736478106–0.951840323 and mean square errors (MSE) of 0.005539–0.0064, the ANN accurately predicted the raw and pasteurized milk MC based on the EC using the sixth-order polynomial model and the EC based on the EFS and MFR using a quadratic model. The EC of pasteurized milk by NP was significantly (p < 0.05) lower than that of CP and raw dairy by 15.44% and 11.30%, respectively. The results show that the EFS and MFR might be used for the online assessment of milk’s physical attributes (e.g., EC), followed by using the assessed parameter to determine other properties (e.g., MC) by developing AI approaches based on optimized models. These observations showcase the innovative use of ANN-based AI to predict milk’s EC and MC accurately. Integrating such AI platforms into non-thermal food processing could eventually develop more sustainable food production and enhance food security and quality through process innovation and sustainable manufacturing, contributing to the industrial revolution and sustainable development goals.

Sustainable Manufacturing Engineering: Enhancing Product Quality through Green Process Innovations

The imperative for sustainable practices within manufacturing has become increasingly critical, driven by environmental concerns, regulatory pressures, and the evolving expectations of eco-conscious consumers. This paper investigates the role of sustainable manufacturing engineering in enhancing product quality through the implementation of green process innovations. Specifically, the study explores how sustainable manufacturing methods, including energy-efficient systems, additive manufacturing, zero-waste production, and renewable energy integration, can drive quality improvements while reducing the environmental impact of production processes. The research is grounded in a comprehensive analysis of current green innovations in the manufacturing sector, drawing on case studies of companies that have successfully balanced quality and sustainability. The findings indicate that companies adopting sustainable practices not only reduce waste and lower emissions but also experience notable gains in product durability, customer satisfaction, and brand reputation. For instance, additive manufacturing is shown to improve precision and material efficiency, while zero-waste initiatives lead to a more efficient resource cycle, which in turn supports consistent quality standards. This paper further delves into the challenges of implementing green manufacturing processes without compromising product quality, examining factors such as initial costs, technological readiness, and market adaptation. Visual data in the form of tables and graphs are presented to compare different green process innovations and their respective impacts on quality and sustainability metrics. In addition, case study summaries provide real-world examples of how leading companies have enhanced product quality through sustainable engineering approaches. This study underscores the value of sustainable manufacturing engineering as a dual-benefit strategy that can drive environmental stewardship alongside quality enhancement. The paper recommends that future research focus on the development of new, cost-effective green technologies and the application of advanced data analytics for improved process control in sustainable manufacturing. Through these efforts, the manufacturing sector can continue advancing toward a more sustainable, high-quality production paradigm.

Optimizing Sustainable Manufacturing: An Integrated Approach of Green Information’s Systems and Knowledge-Based Decisions in Industry 4.0: A Comparative Analysis

Adopting green information technology (IT) systems has become crucial for improving the environmental sustainability of manufacturing firms. To drive the manufacturing process more appropriately, management and administrators recognize the importance of developing green IT systems aligned with knowledge management (KM) practices. To accomplish the study objective, experts were engaged in a study conducted in Henan manufacturing firms to share their knowledge on the factors that influence management’s intention to adopt green IT systems concerning KM. The study collected 324 valid responses from industrial experts in Henan manufacturing industries through survey questionnaires. Using structural equation modeling (SEM), the hypotheses were evaluated, and the significance of each factor in the model was determined. The SEM results revealed that the KM process interpretation significantly influences green IT systems to improve manufacturing process development. Furthermore, the study found that combining KM processes and green practices has a more substantial impact on improving the manufacturing process. This suggests that integrating knowledge management practices with green IT systems can lead to better environmental sustainability and overall performance in manufacturing firms. The findings of this study offer valuable insights for decision-makers and policymakers in formulating policies and programs to implement a green information system with green implementation processes effectively in the manufacturing sector. By adopting these strategies, manufacturing firms can contribute to environmental sustainability while simultaneously improving their overall performance.

Nanocomposites in Tire Development – Benefits, Challenges, and the Role of Carbon Nanotubes and Graphene

In the rapidly evolving automotive industry, enhancing vehicle performance and sustainability through innovative materials is paramount. Nanocomposite materials, incorporating nanoparticles such as carbon nanotubes (CNTs), graphene, and silica, have emerged as key enablers in redefining tire technology with improved durability, efficiency, and environmental impact. This review discusses the integration of these nanocomposites into tire manufacturing, emphasizing their role in enhancing mechanical properties, wear resistance, and rolling efficiency while reducing environmental footprints. Challenges such as dispersion uniformity within the rubber matrix and economic considerations due to high material costs are examined, alongside future research directions aimed at scalability and cost reduction. The paper predicts a significant increase in the adoption of nanocomposite tires, driven by technological advances and the shift toward sustainable manufacturing practices. By detailing the synergistic effects of nanocomposites, this review highlights their potential to revolutionize tire performance and contribute to the next generation of green automotive technologies.

In-Situ HF Forming Agents for Sustainable Manufacturing of Iron-Based Oxygen Reduction Reaction Electrocatalysis Synthesized Through Sacrificial Support Method.

Fe-Nx-Cs being suitable to replace scarce and overpriced platinum group metals (PGMs) for cathodic oxygen reduction reaction (ORR) are gaining significant importance in the fuel cell arena. Although the typical sacrificial support method (SSM) ensures the superior electrocatalytic activity of derived Fe-Nx-C, removing silica hard templates always remains a great challenge due to the hazardous use of highly toxic and not environmentally friendly hydrofluoric acid. Herein, strategic insight was given to modified SSM by exploiting the in-situ formation of HF, deriving from the decomposition of NH4HF2 and NaF, to dissolve silica templates, thus avoiding the direct use of HF. First, the suitable molar ratio between the etching agent and the silica was analyzed, revealing that NH4HF2 efficiently dissolved silica even in a stoichiometric amount, whereas an excess of NaF was required. However, both etching agents exhibited conformal removal of silica while dispersed active moieties within the highly porous architecture of derived electrocatalysts were left behind. Moreover, NH4HF2-washed counterparts demonstrated relatively higher performance both in acidic and alkaline media. Notably, with NH4HF2-washed Fe-Nx-C electrocatalyst, a remarkable onset potential of 970 mV (vs RHE) was achieved with nearly tetra-electronic ORR as the peroxide yield remained less than 10 % in the alkaline medium.

Artificial Intelligence Techniques for Sustainable Reconfigurable Manufacturing Systems: An AI-Powered Decision-Making Application Using Large Language Models

Artificial intelligence (AI) offers a promising avenue for developing sustainable reconfigurable manufacturing systems. Although there has been significant progress in these research areas, there seem to be no studies devoted to exploring and evaluating AI techniques for such systems. To address this gap, the current study aims to present a deliberation on the subject matter, with a particular focus on assessing AI techniques. For this purpose, an AI-enabled methodological approach is developed in Python, integrating fuzzy logic to effectively navigate the uncertainties inherent in evaluating the performance of techniques. The incorporation of sensitivity analysis further enables a thorough evaluation of how input variations impact decision-making outcomes. To conduct the assessment, this study provides an AI-powered decision-making application using large language models in the field of natural language processing, which has emerged as an influential branch of artificial intelligence. The findings reveal that machine learning and big data analytics as well as fuzzy logic and programming stand out as the most promising AI techniques for sustainable reconfigurable manufacturing systems. The application confirms that using fuzzy logic programming in Python as the computational foundation significantly enhances precision, efficiency, and execution time, offering critical insights that enable more timely and informed decision-making in the field. Thus, this study not only addresses a critical gap in the literature but also offers an AI-driven approach to support complex decision-making processes.

Special Issue on Design and Manufacturing for Environmental Sustainability

This is the seventh special issue on Design and Manufacturing for Environmental Sustainability. As the first special issue on the topic was issued in 2009, the topic has a fifteen-year history in this journal. Environmental sustainability was recognized as important for manufacturing even at that time, which is why the special issue was started in this journal. The seriousness of this topic has been increasing not only in Europe but also in Japan and other countries. A recent critical trend has been the way in which companies’ attitudes toward this issue, including their positions on carbon neutrality, a circular economy, and biodiversity, determine their value. Furthermore, particularly striking trend is the promotion of various policies to realize a circular economy, including the adoption of international standards for a circular economy and new eco-design regulations in Europe. These movements indicate the need to transform production and consumption in society as a whole beyond the boundaries of individual companies and industries. The seventh special issue contains seven well-written papers. The papers cover the following topics: - Circular economy - Life cycle design and management - Environmentally conscious design of products and services - Low-energy and low-emission manufacturing - Closed-loop supply chain management - Sustainable consumption and production From the fifteen-year history of this special issue, we have been able to learn viewpoints specific to the series in this journal. Most of the papers, revised and enhanced in response to the editor’s invitation, were originally presented at EcoDesign 2023, the 13th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, held in Nara, Japan. The editor sincerely thanks the authors and reviewers for their contributions in making this special issue possible. We hope that these articles encourage further research on design and manufacturing for environmental sustainability.

Valorization of soybean by-products for sustainable waste processing with health benefits.

Soybean is a rapidly growing agricultural crop, fueled by the rising global demand for animal feed, plant-based proteins and essential nutrients for human consumption. Soybeans contain a wide range of essential nutrients that are vital for health and may play a significant role in disease prevention. Their nutritious composition has led to a diverse range of soy-based foods and derivatives available on the market. A substantial amount of soybeans is allocated to the animal feed sector, human consumption, nutraceuticals and other industrial applications. Soybean has superior protein quality and digestibility compared to other legumes. It also contains abundant amounts of isoflavones, phytosterols and minerals that augment its nutritional value as a constituent of the human diet. Many different by-products are produced during the processing of soy. Due to a lack of sustainable food manufacturing practices, a sustainable amount of these by-products is discarded as waste, posing environmental challenges. Developing an effective waste management system for soybean by-products can help address public health concerns and provide a cost-efficient way to repurpose valuable components of soy, such as soy meal, okara and soy whey. Such valorization can mitigate the environmental impact of waste and contribute to malnutrition. This study aims to evaluate the sustainable use of soy by-products to help preserve biodiversity and reduce food insecurity. This article thoroughly examines the fundamental components of soybean use in the fields of health and soybean by-product processing. It provides a summary of cost-efficient, feasible and ideal processing technologies. © 2024 Society of Chemical Industry.

Current recycling innovations to utilize e-waste in sustainable green metal manufacturing.

The ever-increasing market demand and the rapid uptake of the technologies of electronics create an unavoidable generation of high-volume electronic waste (e-waste). E-waste is embedded with valuable metals, alloys, precious metals and rare earth elements. A substantial portion of e-waste ends up in landfills and is incinerated due to its complex multi-material structure, creating loss of resources and often leading to environmental contamination from the release of landfill leachates and combustion gases. Conversely, due to the ongoing demand for valuable metals, global industrial and manufacturing supply chains are experiencing enormous pressure. To address this issue, researchers have put multifaceted efforts into developing viable technologies and emphasized right-scaling for e-waste reclamation. Several conventional and emerging recycling technologies have been recognized to be efficient in recovering metal alloys, precious and rare earth metals from e-waste. The recovery of valuable metals from e-waste will create an alternative source of value-added raw materials, which could become part of supply chains for manufacturing. This review discusses the urgency of metal recycling from e-waste for sustainability and economic benefit, up-to-date recycling technologies with an emphasis on their potential role in creating a circular economy in e-waste management.This article is part of the discussion meeting issue 'Sustainable metals: science and systems'.

Industry 4.0 factors affecting SMEs towards sustainable manufacturing

Industry 4.0 (I4.0) is one of the essential topics that has been researched extensively in the research domain. In the same way, there are also several research available to check the connections between I4.0 and sustainable manufacturing. It is because of the increasing concern of stakeholders over environmental challenges that manufacturing units are often blamed. It is also true that a major part of manufacturing is done by SMEs in almost every developed or developing economy of the world including India. Therefore, the present research work took place to identify the factors that are essential for sustainable manufacturing using I4.0 in Indian SMEs. In the present study, a total of six factors were identified from the previous studies, which are technological factors (TF), organizational factors (OF), environmental factors (ENF), societal factors (SF), economic factors (ECF), and external stakeholders' factors (ESF) considering the triple bottom line (TBL) approach of the sustainability model. Each factor consists of a few sub-factors, and a total of thirty-five factors were developed. The best-worst method (BWM) and Hierarchical Decision Model (HDM) were applied to bring the results. The result suggests that OF and TF are ranked number one and two respectively. ECF and ENF ranked at three and four whereas, ESF and SF ranked at five and six respectively. The study helps firm managers revolutionize their organizations’ approach to the sustainability model by looking at the Industry 4.0 factors affecting SMEs toward sustainable manufacturing. When managers and practitioners try to convert their business digitally, this study also enables them to prioritize the many I4.0 factors that are most important to their organization. The model was validated by a regional application in Saudi Arabia.

Energy transition policy, technology innovation and sustainable manufacturing

This study examines the impact of China's New Energy Pilot City Policy (REPCP) on green development in the manufacturing sector, focusing on the role of technological innovation. Using a Difference-in-Differences (DID) approach with firm-level data from 30 Chinese provinces and cities (2000-2021), the research analyzes how the policy affects firms' adoption of sustainable manufacturing practices. The findings reveal that the REPCP significantly promotes green development, particularly in regions with moderate levels of industrial development. Moreover, technological innovation amplifies the policy's positive impact, indicating a synergistic relationship. The analysis also finds that state-owned enterprises are more responsive to the policy than non-SOEs. This study contributes to the understanding of energy transition policies by providing empirical evidence of their efficacy in China's manufacturing sector, highlighting the importance of technological innovation, regional variations, and ownership structures in achieving sustainable manufacturing.

Proximal Policy Optimization with Population-based Variable Neighborhood Search Algorithm for Coordinating Photo-Etching and Acid-Etching Processes in Sustainable Storage Chip Manufacturing

In the complex process of manufacturing storage chips, the photo-etching and acid-etching stages play a crucial role, significantly affecting energy consumption and environmental impact. This paper introduces a novel Bi-Level Programming Model for Storage Chip Manufacturing (BLPM-SCM) aimed at optimizing the coordination between these two stages. The upper-level model focuses on minimizing the time it takes to complete wafer production, while the lower-level model seeks to reduce the number of acid-etching tanks used, thereby balancing production efficiency with resource utilization. To address the inherent complexity of the bi-level model, we present a hybrid meta-heuristic algorithm that combines Proximal Policy Optimization (PPO) with a Population-based Variable Neighborhood Search (PVNS) method. The PPO-PVNS algorithm enhances the intensification phase by adaptively selecting shaking and local search strategies, while PVNS supports the diversification phase, ensuring comprehensive exploration of the search space through iterative updates of the solution population. Extensive numerical experiments demonstrate the algorithm's superior performance and generalization capabilities in optimizing the manufacturing process. It significantly improves the coordination between the photo-etching and acid-etching stages, achieving dual optimization of energy consumption and environmental benefits. Furthermore, this study provides valuable insights and decision-making tools for industry practitioners, offering innovative solutions for scheduling optimization in the semiconductor sector and promoting more sustainable and efficient production practices.

Rapid production of high-performance unilaterally surface-densified wood through integrating mechanical compression and thermochemical modification

Enhancing the mechanical performance and dimensional stability of fast-growing wood in an efficient and eco-friendly manner remains a challenge. This study introduces a straightforward and highly efficient technique for fabricating unilaterally surface-densified (USD) wood from fast-growing poplar wood. This process involves a pre-drying treatment, high-temperature compression at 250 ℃, and subsequent cooling, all completed within a total compression time of 300s. The produced USD wood exhibits outstanding physical and mechanical properties, along with excellent dimensional stability. Notably, the USD wood achieved a hardness of 4.3 kN, a modulus of rupture of 117.0MPa, and a modulus of elasticity of 12.2GPa, representing increases of 104.7%, 72.0%, and 38.6%, respectively, compared to untreated wood, aligning with the properties of several premium hardwoods. Furthermore, the USD wood showed superior impact resistance and bending stiffness, alongside minimal irreversible thickness swelling (2.29%) under humid and high-temperature conditions, evidencing its robust mechanical and dimensional stability. These improved performances are attributed to the formation of a densified layer with an intact cell wall structure, which benefits from the favorable effects of high temperature-induced plasticization of cell walls and thermal degradation of hemicellulose. The efficacy of this high-temperature compression technique highlights its significant potential for the mass production of high-performance wood from fast-growing species. Consequently, the resulting USD wood is ideally suited for value-added applications in the furniture and construction industries, offering a pathway towards sustainable and eco-friendly manufacturing solutions.

Investigating the environmental impacts of lithium-oxygen battery cathode production: A comprehensive assessment of the effects associated with oxygen cathode manufacturing

Lithium-oxygen batteries offer remarkably high energy density compared to current lithium-ion batteries. The key to their electrochemical performance lies in the processes occurring at the air cathode. However, the complexity of these reactions, coupled with the by-products generated during discharge, can make the reaction process slow or impede their efficiency. This study evaluates the environmental impact of high-efficiency lithium-oxygen batteries cathodes, including titanium oxide composites, graphene-based composites and activated carbon-based composites, through a life cycle assessment across 18 impact categories using a cradle-to-gate approach with a functional unit of 25 kWh. Results show that active material production was the largest contributor to environmental impact, particularly Global Warming Potential. Among the evaluated cathodes, reduced graphene oxide/α-mnaganese oxide/palladium (rGO/α-MnO2/Pd) demonstrated the highest environmental impact, with a global warming potential of 1130.71 kg carbon dioxide from active material production, due to its energy-intensive synthesis and the use of chemicals like sulfuric acid, sodium borohydride, hydrochloric acid, and hydrogen peroxide. Additionally, the rGO/α-MnO2/Pd cathode had the highest Human Toxicity Potential and Ozone Depletion Potential. Batteries with graphene-based cathodes achieved a specific capacity of 7500 mAh.g-1, underscoring their performance potential while highlighting the need for more sustainable cathode manufacturing methods. These findings emphasize the environmental considerations necessary for large-scale lithium-oxygen batteries implementation.