The challenge of recycling fast-growing fibre-reinforced polymer waste
Related Articles
The evolution of lithium-ion battery recycling
Demand for lithium-ion batteries (LIBs) is increasing owing to the expanding use of electrical vehicles and stationary energy storage. Efficient and closed-loop battery recycling strategies are therefore needed, which will require recovering materials from spent LIBs and reintegrating them into new batteries. In this Review, we outline the current state of LIB recycling, evaluating industrial and developing technologies. Among industrial technologies, pyrometallurgy can be broadly applied to diverse electrode materials but requires operating temperatures of over 1,000 °C and therefore has high energy consumption. Hydrometallurgy can be performed at temperatures below 200 °C and has material recovery rates of up to 93% for lithium, nickel and cobalt, but it produces large amounts of wastewater. Developing technologies such as direct recycling and upcycling aim to increase the efficiency of LIB recycling and rely on improved pretreatment processes with automated disassembly and cleaner mechanical separation. Additionally, the range of materials recovered from spent LIBs is expanding from the cathode materials recycled with established methods to include anode materials, electrolytes, binders, separators and current collectors. Achieving an efficient recycling ecosystem will require collaboration between recyclers, battery manufacturers and electric vehicle manufacturers to aid the design and automation of battery disassembly lines.
State-level policies alone are insufficient to meet the federal food waste reduction goal in the United States
The United States Food Loss and Waste Reduction Goal seeks to reduce national food waste by 50%, down to 74 kg per capita, by 2030. Here we investigate state policies’ alignment with the federal goal across four policy categories. We develop a policy scoring matrix and apply it to wasted food solutions listed in the non-profit ReFED’s database to derive ranges of food waste diversion potential and projected generation across states. On the basis of state policies alone, no state can meet the federal target. We estimated a diversion potential of 5–14 kg per capita and a food waste generation of 149 kg per capita nationally in 2022, equivalent to the 2016 baseline. Without additional intervention at the state and federal level promoting a shift from food waste recycling towards prevention, rescue and repurposing, food generation in the United States will probably remain high.
Flash Joule heating for synthesis, upcycling and remediation
Electric heating methods are being developed and used to electrify industrial applications and lower their carbon emissions. Direct Joule resistive heating is an energy-efficient electric heating technique that has been widely tested at the bench scale and could replace some energy-intensive and carbon-intensive processes. In this Review, we discuss the use of flash Joule heating (FJH) in processes that are traditionally energy-intensive or carbon-intensive. FJH uses pulse current discharge to rapidly heat materials directly to a desired temperature; it has high-temperature capabilities (>3,000 °C), fast heating and cooling rates (>102 °C s−1), short duration (milliseconds to seconds) and high energy efficiency (~100%). Carbon materials and metastable inorganic materials can be synthesized using FJH from virgin materials and waste feedstocks. FJH is also applied in resource recovery (such as from e-waste) and waste upcycling. An emerging application is in environmental remediation, where FJH can be used to rapidly degrade perfluoroalkyl and polyfluoroalkyl substances and to remove or immobilize heavy metals in soil and solid wastes. Life-cycle and technoeconomic analyses suggest that FJH can reduce energy consumption and carbon emissions and be cost-efficient compared with existing methods. Bringing FJH to industrially relevant scales requires further equipment and engineering development.
Advancing extrapolative predictions of material properties through learning to learn using extrapolative episodic training
Recent advancements in machine learning have demonstrated its potential to significantly accelerate the discovery of new materials. Central to this progress is the development of rapidly computable property predictors, which allow identifying novel materials with the desired properties from vast material spaces. However, the limited availability of data resources poses a significant challenge in data-driven material research, particularly hindering the exploration of innovative materials beyond the boundaries of existing data. Although machine-learning predictors are inherently interpolative, establishing a general methodology to create an extrapolative predictor remains a fundamental challenge. In this study, we leveraged the attention-based architecture of neural networks and a meta-learning algorithm to enhance extrapolative generalization capabilities. Meta-learners trained repeatedly on arbitrarily generated extrapolative tasks show outstanding generalization for unexplored material spaces. Through the tasks of predicting the physical properties of polymeric materials and hybrid organic–inorganic perovskites, we highlight the potential of such extrapolatively trained models, particularly their ability to rapidly adapt to unseen material domains in transfer-learning scenarios.
Galvanic leaching recycling of spent lithium-ion batteries via low entropy-increasing strategy
The recycling of spent lithium-ion batteries can effectively mitigate the environmental and resource challenges arising from the escalating generation of battery waste and the soaring demand for battery metals. The existing mixing-then-separating recycling process is confronted with high entropy-increasing procedures, including crushing and leaching, which result in irreversible entropy production due to the decrease in material orderliness or heavy chemical consumption, thereby hindering its thermodynamic efficiency and economic viability of the entire recycling process. Herein, we propose a galvanic leaching strategy that leverages the self-assembly of LiNi0.6Co0.2Mn0.2O2 particles with their inherent aluminium foil current collectors in spent lithium-ion batteries, creating a primary cell system capable of recovering battery metals without pre-crushing or additional reductants. Under the theoretical potential difference of up to 3.84 V, the electrons flow and charge aggregation effectively achieve the valence state reduction, crystal phase transition and coordination environment change of the hard-to-dissolve metal components, contributing to over 90% battery metals recovery and a nearly 30-fold increase in leaching kinetics. Environmental-economic assessments further indicate that this strategy reduces energy consumption and carbon emissions by 11.36%-21.10% and 5.08%-23.18%, respectively, compared to conventional metallurgical methods, while enhancing economic benefits by 21.14%-49.18%.
Responses