Perspectives on Cobalt Supply through 2030 in the Face of Changing Demand.

Lithium-ion battery demand, particularly for electric vehicles, is projected to increase by over 300% throughout the next decade. With these expected increases in demand, cobalt (Co)-dependent technologies face the risk of significant impact from supply concentration and mining limitations in the short term. Increased extraction and secondary recovery form the basis of modeling scenarios that examine implications on Co supply to 2030. Demand for Co is estimated to range from 235 to 430 ktonnes in 2030. This upper bound on Co demand in 2030 corresponds to 280% of world refinery capacity in 2016. Supply from scheduled and unscheduled production as well as secondary production is estimated to range from 320 to 460 ktonnes. Our analysis suggests the following: (1) Co price will remain relatively stable in the short term, given that this range suggests even a supply surplus, (2) future Co supply will become more diversified geographically and mined more as a byproduct of nickel (Ni) over this period, and (3) for this demand to be met, attention should be paid to sustained investments in refined supply of Co and secondary recovery.

Ferrous and non-ferrous recycling: Challenges and potential technology solutions.

Metals recycling is one of the oldest industries in the United States that now employs over 530,000 individuals. It has always played a significant role in the economy, supplied extensive goods and services, and the costs and benefits directly and/or indirectly extend worldwide. Improved efficiency in metals recycling is crucial to achieving a more circular economy; to enable this requires understanding how the industry operates and the challenges it must overcome. Increasing metal product diversity and design complexity combined with increased feed volumes has introduced recent additional challenges. This review explores the current status and state of the industry and examines potential technology solutions that address inbound inspection and material identification challenges.

Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.

Comparative Analysis of Supply Risk-Mitigation Strategies for Critical Byproduct Minerals: A Case Study of Tellurium.

Materials criticality assessment is a screening framework increasingly applied to identify materials of importance that face scarcity risks. Although these assessments highlight materials for the implicit purpose of informing future action, the aggregated nature of their findings make them difficult to use for guidance in developing nuanced mitigation strategy and policy response. As a first step in the selection of mitigation strategies, the present work proposes a modeling framework and accompanying set of metrics to directly compare strategies by measuring effectiveness of risk reduction as a function of the features of projected supply demand balance over time. The work focuses on byproduct materials, whose criticality is particularly important to understand because their supplies are inherently less responsive to market balancing forces, i.e., price feedbacks. Tellurium, a byproduct of copper refining, which is critical to solar photovoltaics, is chosen as a case study, and three commonly discussed byproduct-relevant strategies are selected: dematerialization of end-use product, byproduct yield improvement, and end-of-life recycling rate improvement. Results suggest that dematerialization will be nearly twice as effective at reducing supply risk as the next best option, yield improvement. Finally, due to its infrequent use at present and its dependence upon long product lifespans, recycling end-of-life products is expected to be the least effective option despite potentially offering other benefits (e.g., cost savings and environmental impact reduction).

Targeting high value metals in lithium-ion battery recycling via shredding and size-based separation.

Development of lithium-ion battery recycling systems is a current focus of much research; however, significant research remains to optimize the process. One key area not studied is the utilization of mechanical pre-recycling steps to improve overall yield. This work proposes a pre-recycling process, including mechanical shredding and size-based sorting steps, with the goal of potential future scale-up to the industrial level. This pre-recycling process aims to achieve material segregation with a focus on the metallic portion and provide clear targets for subsequent recycling processes. The results show that contained metallic materials can be segregated into different size fractions at different levels. For example, for lithium cobalt oxide batteries, cobalt content has been improved from 35% by weight in the metallic portion before this pre-recycling process to 82% in the ultrafine (<0.5mm) fraction and to 68% in the fine (0.5-1mm) fraction, and been excluded in the larger pieces (>6mm). However, size fractions across multiple battery chemistries showed significant variability in material concentration. This finding indicates that sorting by cathode before pre-treatment could reduce the uncertainty of input materials and therefore improve the purity of output streams. Thus, battery labeling systems may be an important step towards implementation of any pre-recycling process.

System tradeoffs in siting a solar photovoltaic material recovery infrastructure.

The consumption and disposal of rare and hazardous metals contained in electronics and emerging technologies such as photovoltaics increases the material complexity of the municipal waste stream. Developing effective waste policies and material recovery systems is required to inhibit landfilling of valuable and finite resources. This work developed a siting and waste infrastructure configuration model to inform the management and recovery of end-of-life photovoltaics. This model solves the siting and waste location-allocation problem for a New York State case study by combining multi-criteria decision methods with spatial tools, however this methodology is generalizable to any geographic area. For the case study, the results indicate that PV installations are spatially statistically significant (i.e., clustered). At least 9 sites, which are co-located with landfills and current MRFs, were 'highly' suitable for siting according to our criteria. After combining criteria in an average weighted sum, 86% of the study area was deemed unsuitable for siting while less than 5% is characterized as highly suitable. This method implicitly prioritized social and environmental concerns and therefore, these concerns accounted for the majority of siting decisions. As we increased the priority of economic criteria, the likelihood of siting near ecologically sensitive areas such as coastline or socially vulnerable areas such as urban centers increased. The sensitivity of infrastructure configurations to land use and waste policy are analyzed. The location allocation model results suggest current tip fees are insufficient to avoid landfilling of photovoltaics. Scenarios where tip fees were increased showed model results where facilities decide to adopt limited recycling technologies that bypass compositionally complex materials; a result with strong implications for global PV installations as well as other waste streams. We suggest a multi-pronged approach that lowers technology cost, imposes a minimum collection rate, and implements higher tip fees would encourage exhaustive material recovery for solar photovoltaic modules at end-of-life, beyond New York State. These results have important implications for policy makers and waste managers especially in locations where there is rapid adoption of renewable energy technologies.

Economic and environmental characterization of an evolving Li-ion battery waste stream.

While disposal bans of lithium-ion batteries are gaining in popularity, the infrastructure required to recycle these batteries has not yet fully emerged and the economic motivation for this type of recycling system has not yet been quantified comprehensively. This study combines economic modeling and fundamental material characterization methods to quantify economic trade-offs for lithium ion batteries at their end-of-life. Results show that as chemistries transition from lithium-cobalt based cathodes to less costly chemistries, battery recovery value decreases along with the initial value of the raw materials used. For example, manganese-spinel and iron phosphate cathode batteries have potential material values 73% and 79% less than cobalt cathode batteries, respectively. A majority of the potentially recoverable value resides in the base metals contained in the cathode; this increases disassembly cost and time as this is the last portion of the battery taken apart. A great deal of compositional variability exists, even within the same cathode chemistry, due to differences between manufacturers with coefficient of variation up to 37% for some base metals. Cathode changes over time will result in a heavily co-mingled waste stream, further complicating waste management and recycling processes. These results aim to inform disposal, collection, and take-back policies being proposed currently that affect waste management infrastructure as well as guide future deployment of novel recycling techniques.

Prioritizing material recovery for end-of-life printed circuit boards.

The increasing growth in generation of electronic waste (e-waste) motivates a variety of waste reduction research. Printed circuit boards (PCBs) are an important sub-set of the overall e-waste stream due to the high value of the materials contained within them and potential toxicity. This work explores several environmental and economic metrics for prioritizing the recovery of materials from end-of-life PCBs. A weighted sum model is used to investigate the trade-offs among economic value, energy saving potentials, and eco-toxicity. Results show that given equal weights for these three sustainability criteria gold has the highest recovery priority, followed by copper, palladium, aluminum, tin, lead, platinum, nickel, zinc, and silver. However, recovery priority will change significantly due to variation in the composition of PCBs, choice of ranking metrics, and weighting factors when scoring multiple metrics. These results can be used by waste management decision-makers to quantify the value and environmental savings potential for recycling technology development and infrastructure. They can also be extended by policy-makers to inform possible penalties for land-filling PCBs or exporting to the informal recycling sector. The importance of weighting factors when examining recovery trade-offs, particularly for policies regarding PCB collection and recycling are explored further.

Increasing secondary and renewable material use: a chance constrained modeling approach to manage feedstock quality variation.

The increased use of secondary (i.e., recycled) and renewable resources will likely be key toward achieving sustainable materials use. Unfortunately, these strategies share a common barrier to economical implementation - increased quality variation compared to their primary and synthetic counterparts. Current deterministic process-planning models overestimate the economic impact of this increased variation. This paper shows that for a range of industries from biomaterials to inorganics, managing variation through a chance-constrained (CC) model enables increased use of such variable raw materials, or heterogeneous feedstocks (hF), over conventional, deterministic models. An abstract, analytical model and a quantitative model applied to an industrial case of aluminum recycling were used to explore the limits and benefits of the CC formulation. The results indicate that the CC solution can reduce cost and increase potential hF use across a broad range of production conditions through raw materials diversification. These benefits increase where the hFs exhibit mean quality performance close to that of the more homogeneous feedstocks (often the primary and synthetic materials) or have large quality variability. In terms of operational context, the relative performance grows as intolerance for batch error increases and as the opportunity to diversify the raw material portfolio increases.

Toward sustainable material usage: evaluating the importance of market motivated agency in modeling material flows.

Increasing recycling will be a key strategy for moving toward sustainable materials usage. There are many barriers to increasing recycling, including quality issues in the scrap stream. Repeated recycling can compound this problem through the accumulation of tramp elements over time. This paper explores the importance of capturing recycler decision-making in accurately modeling accumulation and the value of technologies intended to mitigate it. A method was developed combining dynamic material flow analysis with allocation of those materials into production portfolios using blending models. Using this methodology, three scrap allocation methods were explored in the context of a case study of aluminum use: scrap pooling, pseudoclosed loop, and market-based. Results from this case analysis suggest that market-driven decisions and upgrading technologies can partially mitigate the negative impact of accumulation on scrap utilization, thereby increasing scrap use and reducing greenhouse gas emissions. A market-based allocation method for modeling material flows suggests a higher value for upgrading strategies compared to a pseudoclosed loop or pooling allocation method for the scenarios explored.