Critical mineral bottlenecks constrain sub-technology choices in low-carbon energy deployment

Summary

To meet global climate targets, countries aim to triple renewable energy capacity and rapidly deploy other low-carbon technologies by 2030. We assess the critical mineral demand required to meet these goals using a bottom-up, scenario-based approach and examine how mineral bottlenecks affect sub-technology choices. Our analysis yields three key findings. First, annual demand for critical minerals is projected to rise 6-fold, from 4.7 million tons in 2022 to 30 million tons by 2030. Second, minerals such as natural graphite, cobalt, lithium, tellurium, indium, silver, aluminum, copper, and rare earth elements may face supply constraints. Third, specific sub-technologies depend heavily on certain minerals: cadmium and tellurium shortages could limit thin-film photovoltaics; indium scarcity may hinder perovskite tandem cells; rare earths are vital for permanent-magnet wind turbines; and lithium is a key for all-solid-state batteries. Improving material efficiency and advancing mineral-efficient technologies will be essential for a resilient energy transition.

Graphical abstract

Highlights

• •Mineral demand may rise 6-fold by 2030 under low-carbon energy goals
• •Lithium, cobalt, REEs, and indium pose key supply risks
• •Mineral shortages constrain specific low-carbon sub-technologies
• •Boosting material efficiency and alternatives is increasingly urgent

Environmental technology; Energy resources; Energy engineering

Introduction

Following the conclusion of the first Global Stocktake of the Paris Agreement, countries have committed to accelerate action on climate change mitigation across all sectors by 2030 and set ambitious new targets.¹ These include tripling global renewable energy capacity, doubling energy efficiency, and transitioning energy systems away from fossil fuels in a just, orderly, and equitable manner.² Achieving these ambitious near-term goals requires the large-scale deployment of low- and zero-carbon technologies, such as photovoltaics, wind power, battery storage, and electric vehicles (EVs), which will substantially increase global demand for a broad range of raw materials.³ Specifically, this calls for an average annual renewable energy installation rate of approximately 1,000 GW between 2023 and 2030, nearly four times the average annual addition of 264 GW over the past five years. With 473 GW of renewable energy installed globally in 2023, the gap to the target is rapidly narrowing.^4,5 However, many of the raw materials essential for these technologies face supply risks due to high costs, geopolitical complexities, concerns over human rights and social responsibility, as well as environmental concerns.^6,7 Broadly defined, materials critical to economic or national security with vulnerable supply chains are categorized as “critical minerals”.^8,9

The adequacy and reliability of materials supporting the large-scale deployment of low carbon technologies have become a primary concern for companies, governments, academia, and other stakeholders.⁸ A critical first step in addressing supply chain challenges is assessing the quantities of mineral resources required for future technology deployment. Modeling results across different energy scenarios suggest that the global energy transition could drive demand for one or more minerals beyond known annual supply levels—or even known reserves.^10,11,12 Such potential shortages could jeopardize the large-scale deployment of renewable energy technologies.¹³ Moreover, the availability of critical minerals has begun to influence policy decisions regarding which technologies to support. A study on the US Inflation Reduction Act (IRA) found that lithium iron phosphate (LFP) batteries are more likely to achieve supply chain diversification due to the greater availability of their critical minerals, making them more likely to receive substantive support.¹⁴

Numerous studies have assessed future demand for critical minerals, with most spanning approximately 40 years, typically extending to 2050. These studies often indicate that “mineral shortages” emerge in the later stages of the modeling period.¹³ Long-term assessments are valuable for developing strategies that align with the extended timeline required to transition from resource reliability evaluations to full-scale mineral development.³ However, within shorter time frames such as the accelerated action mandated by COP28—key questions arise: how much will mineral demand increase in the near term? Will it exceed the available supply, and if so, by what margin? Addressing these questions promptly is crucial for informing strategy and policymaking.

The material efficiency of technologies, the selection of existing mature sub-technology combinations, and the adoption of alternative emerging technologies have a significant impact on the demand for critical minerals and the “energy-minerals” nexus.^10,12,13,15 For instance, a single permanent magnet wind turbine requires several times more rare earth elements (REEs) than a doubly-fed induction generator (DFIG) wind turbine.¹⁶ A recent study examined the relationship between various electric vehicle battery chemistries and the supply chain vulnerabilities of four key metals—lithium, cobalt, nickel, and manganese—and concluded that nickel-cobalt-manganese (NCM) batteries entail additional risks relative to batteries based on alternative chemistries.¹⁷ This work underscores the heterogeneous impact of critical mineral availability on the adoption of batteries with different chemistries, thereby justifying further investigation into the differential outcomes associated with various photovoltaic and wind energy technologies.

Moreover, renewable energy technologies have evolved rapidly in recent years. Even within a single category of technology, as defined in most studies, the specific sub-technologies exhibit significant differences in mineral demand.¹³ For example, both tunnel oxide passivated contact solar cells (TOPCon) and passivated emitter and rear cells (PERC) are classified as silicon- and silver-dependent crystalline silicon photovoltaic technologies. However, in 2023, the silver required per unit deployment of TOPCon technology was 1.7 times that of PERC.¹⁸ In 2022, PERC accounted for nearly 90% of the market share, but this is projected to shrink rapidly to 31% by 2024 as TOPCon replaces much of the market,¹⁹ driving an overall 1.4-fold increase in silver consumption in photovoltaics. Similar trends are observed in sub-technologies of wind turbines and battery technologies,²⁰ further underscoring the dynamic and complex nature of mineral demand driven by technological evolution.

Emerging technologies often exhibit entirely different material demands compared to existing ones. As these technologies gain market share, they may alleviate pressures on critical mineral demand or, conversely, introduce new conflicts in mineral requirements.²¹ Furthermore, constraints on mineral availability could undermine economies of scale and learning processes for low carbon technologies, ultimately affecting their development trajectories.²² Different assumptions about the market share of sub-technologies within future technology pathways can lead to an order-of-magnitude variation in estimates of mineral demand.^13,23 Will alternative sub-technology pathways, constrained by real-world market and policy dynamics, mitigate critical mineral demand? Conversely, could the availability of critical minerals, in turn, shape sub-technology choices?

Research on the interplay between energy transitions and critical minerals generally follows two main directions: projecting mineral demand under alternative decarbonization pathways, and assessing how mineral constraints may in turn shape feasible transition trajectories.⁸ The former has improved our understanding of future resource requirements and informed strategies around recycling, substitution, and material efficiency.^22,24 The latter—though less explored—has begun to examine the implications of mineral bottlenecks for technology deployment and system design.²⁵ Within this emerging strand, a key unresolved question is how technological choices interact with mineral constraints. Existing studies often rely on highly aggregated representations of technologies—e.g., modeling entire sectors with a single representative PV, wind, or battery technology,^16,26 or distinguishing only between “back-stop” and “novel” options.^21,27 Recent efforts, including those by the International Energy Agency (IEA), have taken important steps toward differentiating technology variants, for example by assessing how shifts in sub-technology market shares affect mineral demand.³ However, such studies still aggregate diverse technologies into broad categories—for instance, treating TOPCon, PERC, and SHJ collectively as crystalline silicon (c-Si) PV. Consequently, they may miss important trade-offs linked to material intensity and scalability. More granular, sub-technology-level analyses are needed to assess realistic transition strategies under mineral supply constraints.

In this study, we assess the demand for critical minerals associated with achieving the global target of tripling renewable energy capacity by 2030, focusing on four key technologies: PV, wind power, EVs, and grid energy storage. Another key focus of this study is the interaction between the sub-technology pathway choices for these key low carbon technologies and the constraints imposed by critical mineral availability. We explore whether different combinations of sub-technologies might exacerbate or alleviate these mineral constraints. By concentrating on near-term shifts in technology pathways, we can sidestep the trade-offs in technical details that are typically required in longer-term forecasts and avoid aggregating sub-technologies that are broadly similar. However, given the practical limitations—such as the retooling of production facilities, significant technological shifts over shorter time frames are unrealistic. Therefore, our analysis emphasizes incremental changes in the market share of existing sub-technologies; Specifically, we consider scenarios where mature technology increases its market share or where an emerging technology achieves a certain level of market penetration.

For PV, wind, and battery technologies, we design three scenarios: (1) a baseline scenario reflecting current market trends, (2) a scenario where non-dominant but available technologies expand their market share, and (3) a scenario where emerging technologies achieve market breakthroughs and capture a portion of the market. Subsequently, we analyze how critical mineral demand varies under these sub-technology pathway scenarios for PV, wind power, and EVs.

We develop a model supported by bottom-up sub-technology development scenarios, based on existing energy system scenarios and sub-technology material demand, to estimate critical mineral demand. The model also integrates efficiency improvements and material recycling rates, as informed by prior research.²⁸ It considers advancements in sub-technology efficiency, improved material usage rates, and potential savings from secondary supply and material reuse.^{11,18,19,20,29,30,31} This framework aims to evaluate how shifts in sub-technology pathways influence critical mineral demand.

Our findings highlight the challenges posed by critical mineral supply in supporting the tripling of renewable energy capacity. The annual demand for 21 critical minerals included in this study rises from 4,715 kt in 2022 to 30,146 kt in 2030 under the baseline scenario 6.4-fold increase. While short-term resource bottlenecks are unlikely, the primary supply (mined output) of minerals, such as graphite, cobalt (Co), lithium (Li), tellurium (Te), indium (In), silver (Ag), aluminum (Al), copper (Cu), and REEs will be insufficient to sustain the required deployment of renewable energy technologies. When accounting for different sub-technology pathways, the annual demand for the 21 critical minerals in 2030 ranges from 28,315 kt to 32,494 kt.

Previous studies have generally suggested that diversifying technology portfolios and adopting alternative technologies could effectively alleviate pressures on critical mineral demand.^8,21 In our study, we categorize the diversification of technology combinations into two types: the expansion of the market size of a mature sub-technology, and the increase in market share of emerging technologies. For example, in the case of photovoltaics, the market expansion of thin-film photovoltaics is classified as the former, while the additional market share gained by perovskite tandem cells is considered the latter. However, our analysis reveals that, when incorporating market, policy, and technological dynamics, shifts in existing sub-technology market shares and increased penetration of emerging technologies are more likely to exacerbate critical mineral constraints than to relieve them in most scenarios. Therefore, we conclude that improving material efficiency in existing technologies and continuing the development of other alternative technologies should remain top priorities for the low carbon energy sector.

Results

Growth of low-carbon technologies and sub-technology trends

The specific pathways to achieve the target of tripling renewable energy capacity vary slightly across different organizations’ projections but are generally aligned with scenarios that limit global temperature rise to 1.5°C. This study adopts International Renewable Energy Agency’s 1.5°C scenario to estimate annual deployment levels for key renewable energy technologies from 2023 to 2030 under the tripling target.³² In our scenario, the global installed renewable energy capacity increases from 3,382 GW in 2022 to 11,173 GW by 2030. We focus on PV, wind power, grid energy storage, and EVs—technologies whose rapid deployment is most likely to face material constraints.³ Between 2023 and 2030, PV cumulative installed capacity grows from 1,401 GW to 5,457 GW, with an average annual growth rate of 19.4%. Wind power capacity expands from 1,032 GW to 3,534 GW, representing an average annual growth rate of approximately 17.6%. Grid energy storage scales from 28 GW to 359 GW, achieving an average annual growth rate of 31.9%. Meanwhile, the stock of EVs and plug-in hybrid electric vehicles (PHEV) increases from 36.35 million to 360 million units during the same period.

To analyze the evolution of sub-technology deployment within low-carbon sectors, we developed a set of scenarios that distinguish between mainstream and emerging sub-technologies across photovoltaics, wind power, and batteries. Figure 1 illustrates the resulting market share trajectories, capturing both prevailing trends and plausible shifts informed by technical maturity, performance advantages, and policy support. These scenarios were constructed using a structured methodology that integrates industry data, expert judgment, and clearly defined inclusion criteria, ensuring consistency with real-world developments. Detailed data sources, scenario assumptions, and sub-technology definitions are provided in the supplemental information. While the baseline scenario reflects the continuation of current market dynamics, alternative scenarios isolate the effects of expanding individual sub-technologies, enabling us to assess how such shifts may influence future critical mineral demand.

Figure 1.

Sub-technology scenario design

2022 Current represents the current market share of each sub-technology, while Baseline Scenario 2030 reflects conservative projections of sub-technology market share changes based on market trends.

(A) Photovoltaics: In the MoreTD 2030 scenario, perovskite tandem cells achieve a 20% market share by 2030, while in the MoreTF 2030 scenario, CdTe and CIGS collectively capture 20% of the market by 2030.

(B) Wind Power: In the MoreDD scenario, DD-PMSG turbines expand their market share to 40% by 2030, and in the MoreGP scenario, medium-speed turbines using gearbox and PMSG (GB-PMSG) technology also achieve a 40% market share by 2030.

(C) Electric vehicles (including PHEVs): In the MoreHN scenario, the market share of LFP batteries decreases to 20% by 2030, while in the MoreAB scenario, solid-state batteries begin market penetration in 2026 and achieve a 10% market share by 2030.

In PV technologies, c-Si currently dominates the market, accounting for over 95% of installed capacity, with PERC and TOPCon being the leading c-Si technologies.^18,19 By 2030, TOPCon is expected to become the dominant PV technology. Thin-film PV (represented in purple in the figure) is often categorized as a second-generation PV technology, with cadmium telluride thin-film solar cells (CdTe) and copper indium gallium selenide thin-film solar cells (CIGS) holding the second- and third-largest market shares after c-Si. Thin-film technologies offer a higher potential efficiency limit and longer lifespans.^33,34 Additionally, CdTe has received substantial support from the IRA, which may enable it to capture a larger-than-anticipated market share. This potential underpins the design of our MoreTF scenario. The efficiency limits of c-Si PV may pose constraints on further technological advancements. Several companies are already commercializing perovskite tandem PV modules, which could gain a higher-than-expected market share by 2030.³⁵ This possibility informs us of the design of the MoreTD scenario.

Wind power technology remains dominated by DFIG, which are projected to maintain a market share exceeding 60% by 2030.^3,16,29 Direct-drive permanent magnet synchronous generator (DD-PMSG) turbines, known for their low maintenance requirements and stable performance, have been widely adopted for offshore wind farms.^29,36 The growing demand for larger onshore turbines and the long-term economic viability of wind farms may drive DD-PMSG to capture a greater market share than anticipated. This prospect forms the basis for our MoreDD scenario. Since 2015, hybrid turbines utilizing gearboxes and PMSG have gained traction in medium wind-speed regions due to their cost-effectiveness, adaptability, and reliability.^36,37 These factors suggest the potential for hybrid turbines to achieve significantly higher market share than projected in the baseline scenario. This possibility underpins our MoreGP scenario.

Batteries for EVs are predominantly composed of LFP and high-nickel batteries, which together account for over 90% of the market share.^30,38 Enhancing energy density remains a key focus for industry. High-nickel batteries, with their relatively higher energy density compared to LFP, are projected to gain a larger market share by 2030³ (represented by the blue segment in the figure). This forms the basis for our MoreHN scenario. Solid-state batteries (ASSB) offer superior energy density and safety, with a higher technology readiness level compared to other promising alternatives for EVs, such as Li-Air batteries.³¹ Some companies have already announced the small-scale commercialization of ASSBs, supporting the development of our MoreAB scenario.

Critical mineral demand and supply

This study estimates that achieving the tripling of renewable energy targets will significantly increase the demand for critical minerals compared to current levels. Under the baseline technology scenario, the annual primary production demand for the 21 minerals included in the study rises from 4,715 kt in 2022 to 30,146 kt in 2030, a 6.4-fold increase (Figure 2). The growth in demand varies considerably among minerals, with individual mineral demand in 2030 increasing by 2.2–16 times compared to 2022. Indium exhibits the highest growth (16-fold), while tellurium shows the lowest (2.2-fold). Long-term studies generally suggest that mineral demand will not continue to grow indefinitely but will peak and then decline due to factors such as recycling or other changes.⁸ However, our estimates indicate that, given current recycling rates and the extent of technological changes, mineral demand will still be in an accelerated growth phase by 2030, in line with estimates from the IEA.³⁹ Notably, we estimate that Indium demand will significantly exceed typical research projections due to the inclusion of SHJ cell technology in our analysis, a photovoltaic technology known for its high efficiency and potential to drive increased demand for indium.^8,16

Figure 2.

Projected mineral demand in 2030 relative to current supply levels

This figure illustrates the ratio of annual demand for 21 minerals included in the study to primary supply levels in 2023. The comparison is made between 2022 and the baseline scenario for 2030 (blue to purple bars representing demand from various low carbon energy technologies, and gray bars for demand from other sectors). The demand from other sectors is based on the global consumption data for 2022 and 2023, minus the demand from the selected technologies in 2022, assuming no change by 2030 as a conservative estimate (see Supplementary Information for details). The red line indicates the current primary supply levels. Magnet REEs include four elements: Dy, Nd, Pr, and Tb. Minerals marked with an asterisk (Te, Se, Na, Mn, and Si) lack data for demand from other sectors. In 2030, In demand is projected to reach 545.4% of the current primary supply levels. C represents graphite, encompassing both natural and synthetic graphite. Si represents polysilicon alone.

Overall, the annual extraction of some materials will need to increase significantly from current levels. First, there are no resource reserve constraints for any of the minerals studied; the cumulative demand for all materials remains within the limits of proven reserves. However, achieving the tripling of renewable energy targets will require the considered technologies to demand quantities of graphite, cobalt, lithium, tellurium, and indium that exceed current supply levels. By 2030, the primary supply levels of Co and Li face shortfalls of 139.20 kt and 157.68 kt, respectively, equating to 70% and 32% of their current supply levels. Although global supply chains for Co and Li are being rapidly scaled up, material bottlenecks may emerge earlier than previously projected.^3,8,11,24 Te and In demand, driven primarily by photovoltaic technologies, will exceed current supply levels by approximately 0.15 kt and 4.48 kt, respectively. Polysilicon demand will exceed current supply level by 311.55 kt. Graphite primary demand will surpass current supply levels by about 4,676.40 kt but falls within the range of expected supply from announced projects (over 10 Mt), as reported by the IEA.³⁹ Graphite is used in almost all lithium battery anodes. Some studies suggest that increasing the use of natural graphite could help alleviate these supply constraints.^40,41 Currently, battery anodes for transportation and energy storage rely mainly on synthetic graphite, which is energy-intensive but faces no extraction constraints. In contrast, natural graphite is less energy-intensive but faces supply pressures due to extraction limitations.

When considering other sectors, the demand for silver (Ag), aluminum (Al), copper (Cu), and REEs also exceed current supply levels. The supply of Al and Cu must adapt to the rapid growth in demand driven by low carbon energy technologies. Ag demand will surpass current supply levels by approximately 3.78 kt. REEs face a potential material shortfall of about 23.40 kt, primarily driven by the demand for wind turbine generators and electric vehicle motors. Although the immediate shortfall is relatively small, REEs have consistently experienced tight supply conditions.^10,11,42

Revisiting the critical minerals and technology pathways nexus

The choice of sub-technology pathways for deploying critical low carbon energy technologies has a significant impact on mineral demand, with the availability of key minerals imposing constraints on specific technology combinations. By 2030, the annual total demand for the 21 critical minerals considered ranges from 28,899 kt to 32,634 kt. Demand for Ag, Cd, Co, Ga, In, Li, Mn, REEs, Ni, Se, Te, and V is particularly sensitive to variations in sub-technology pathways. These materials, though relatively low in total demand, are closely tied to specific technologies and, except for V, are widely regarded as “critical raw materials.”⁴³ Among them, as discussed earlier, potential supply bottlenecks exist for Co, Li, Te, In, Ag, and REEs. These bottlenecks could constrain the realization of certain technology combinations, such as thin-film photovoltaics being limited by access to Cd, Te, and In, or the reliance of high-Ni batteries on Ni and Co potentially hindering their market expansion. The following sections provide a detailed analysis of the technology combinations and critical mineral demands for photovoltaics, wind power, and electric vehicle batteries.

Solar

A comparison of material demand across different photovoltaic sub-technology scenarios highlights the urgent need to improve silver utilization efficiency (see Figure 3). By 2030, the Ag required for photovoltaic deployment is projected to increase from approximately 3.27 kt in 2022 to between 8.98 kt and 10.68 kt, depending on the scenario (see Figure 3A). This represents a rise in photovoltaics’ share of global silver consumption from the current ∼13.8% to 38.4–45.6%. Even with partial substitution of crystalline silicon photovoltaic technology by thin-film materials—a transition fraught with challenges—silver is poised to become a critical bottleneck. Due to cost and performance considerations, silver’s substitutability in current photovoltaic technologies is low.⁴⁴ However, there is room to improve its utilization efficiency, underscoring the importance of optimizing silver-use technological pathways.⁴⁵ Our findings also emphasize the critical need to advance substitution technologies for indium. Across all sub-technology scenarios, indium demand for photovoltaic deployment is expected to surge from 0.251 kt in 2022 to 4.11–5.72 kt by 2030, exceeding three times the annual primary supply level (see Figure 3B). This rising demand is driven by the use of indium tin oxide (ITO) conductive films in HJT/Tandem technologies and CIGS technology. Notably, indium prices have already risen by over 40% from 2022 to October 2024, signaling potential supply pressures ahead.⁴⁶

Figure 3.

Demand for critical minerals required by selected photovoltaic technologies

This figure illustrates the demand for critical minerals required by selected photovoltaic technologies in 2022 and 2030 under the baseline scenario, the MoreTF scenario, and the MoreTD scenario. Blue bars represent material demand for crystalline silicon photovoltaic technology, orange bars correspond to thin-film photovoltaic technology, and green bars depict material demand for emerging tandem technologies.

(A) Silver.

(B) Indium.

(C) Cadmium, Tellurium, Gallium and Selenium.

From the perspective of critical minerals, the future expansion of the thin film photovoltaic market faces significant challenges. The adoption of emerging technologies, such as higher-efficiency Tandem cells, will not substantially reduce the overall material demand for photovoltaic technologies. In the MoreTF scenario, demand for Cd, Ga, In, Se, and Te rises sharply, with Cd, In, and Te surpassing current mineral supply levels (see Figure 3C). There are currently no substitutes for these minerals in mainstream thin-film photovoltaic technologies.³ In the MoreTD scenario, while indium demand increases by 28.6% compared to the baseline, the demand for other materials remains largely unchanged. This is due to the low initial market penetration of the technology and the relatively modest efficiency improvements of small-scale commercial perovskite tandem solar cells compared to other mainstream crystalline silicon photovoltaic technologies.¹⁸ Despite the significant potential for efficiency improvements in perovskite tandem cells, achieving material savings with this technology will require a longer period of development.³⁵

Wind turbines

Figure 4F highlights the need to enhance primary supply levels of REEs to meet demand under different wind power sub-technology scenarios. By 2030, the primary demand for magnet REEs (Nd, Pr, Dy, and Tb) driven by wind power installations is projected to reach 25.02–37.47 kt, 4.39–8.63 kt, 4.53–6.21 kt, and 1.15–2.17 kt, respectively, totaling 37.41 kt (BAU) to 54.48 kt (MoreDD). According to IEA estimates, the expected supply from announced projects in 2030 is approximately 103 kt, while primary demand from other sectors may reach about 64 kt³⁹. Combined with our findings, this indicates that REEs are likely to face supply constraints. Steel (including alloy steel) accounts for 23%–26% of the total weight of wind turbines, primarily used in tower structures and generators, driving the demand for materials such as Mo, Ni, and Cr, see Figures 4C–4E.²⁰ Our analysis does not include materials used for wind turbine blades, which typically consist of composite materials, such as fiberglass, carbon fiber, and plastics as their supply chains differ significantly from mineral extraction and processing. Some reports suggest that these materials may also face potential supply shortages.²⁹

Figure 4.

Demand for critical minerals required by selected wind power technologies

This figure compares the demand for selected critical minerals required for wind power in 2022 and 2030 under the baseline scenario, the MoreDD scenario, and the MoreGP scenario.

(A) Aluminum.

(B) Copper.

(C) Molybdenum.

(D) Nickel.

(E) Chromium.

(F) Magnet Rare Earth Elements.

The expanded application of DD-PMSG is more susceptible to material bottlenecks. Greater adoption of medium-speed turbines using GB-PMSG technology can alleviate material pressures associated with wind power deployment. By 2030, the market share of permanent magnet wind turbines in the MoreDD scenario increases to 40% compared to 24.6% in the BAU scenario, resulting in a 45.6% higher demand for REEs, equivalent to approximately 17.07 kt, see Figure 4F. The key advantage of DD-PMSG technology lies in its higher efficiency and lower maintenance requirements, making it particularly suited for offshore wind power applications.³⁶ Historically, offshore wind has accounted for less than 10% of total wind power capacity,¹⁶ but the increased deployment of DD-PMSG turbines could double the demand for REEs. In the MoreGP scenario, the market share of direct-drive wind turbines rises to 40% by 2030, significantly reducing the demand for Cu, as well as Tb and Pr among REEs, by 18.2%, 16.3%, and 20.4%, respectively, compared to the BAU scenario (Figures 4B and 4F). This scenario results in only a slight increase in the demand for Al and Mo, Ni, and Cr used in alloy steel compared to BAU (Figures 4A and 4C–4E).

EV batteries

Comparison of demand across different sub-technology scenarios for EV power batteries reveals that the supply of Li and Co minerals must expand by 1.3–1.6 times and 1.1–1.7 times, respectively, from current levels to achieve the tripling of renewable energy targets (Figures 5B and 5C). Across all sub-technology scenarios, annual demand for Li from power batteries is projected to reach 495.89 kt (BAU) to 629.01 kt (MoreAB) by 2030, while demand for Co is expected to range from 223.74 kt (BAU) to 344.96 kt (MoreHN), as shown in Figure 5.

Figure 5.

Demand for critical minerals required by selected battery technologies

This figure compares the demand for selected critical minerals required by various battery technologies in 2022 and 2030 under the BAU, MoreHN, and MoreAB scenarios.

(A) Copper.

(B) Lithium.

(C) Cobalt.

(D) Nickel.

(E) Manganese.

(F) Graphite.

The diversification and advancement of currently commercially available battery sub-technologies have a limited impact on alleviating constraints in critical mineral availability. For essential minerals required by lithium-ion batteries, including Li, Co, Ni, and Mn, demand is lowest under the BAU scenario, while minerals with relatively flexible supply, such as Cu and graphite, exhibit the opposite trend (Figures 5A–5F). In the MoreHN scenario, Li demand is slightly reduced by approximately 5.8% (around 28.93 kt) compared to the BAU scenario, but demand for Co, Ni, and Mn increases significantly by 54.2%, 50.1%, and 54.0%, respectively (Figures 5C–5E). Although high-nickel batteries offer superior energy density compared to iron-based lithium batteries, scenarios where high-nickel batteries dominate the market would significantly increase the demand for certain materials, making them more susceptible to supply constraints.

Emerging alternative battery technologies may introduce new supply bottlenecks. In the MoreAB scenario, the increased adoption of solid-state batteries significantly raises the demand for Cu and Li, with increases of 36.7% and 19.9%, respectively, compared to the BAU scenario. Demand for Co, Ni, and Mn also sees slight growth. The primary advantage of current solid-state batteries lies in their improved safety, while their energy density advantage remains limited. However, their demand for Li is higher due to the replacement of graphite electrodes with Li-based materials.^47,48 Although sodium-ion (Nai) batteries can effectively reduce Li demand, prototype data from existing literature indicate that Na batteries require 1.90 and 1.86 times more Co and Mn per unit capacity compared to nickel-based batteries (NCM622).³ Other potential technologies, such as Li-air batteries, which are still at the laboratory or demonstration stage and not considered in this analysis, may face similar challenges.⁴⁹ This underscores the critical importance of Li and Co availability for the large-scale deployment of new battery technologies.

In summary, our study indicates that while diversifying technology pathways for large-scale deployment of low carbon energy technologies is essential, it may not directly mitigate material supply bottlenecks. Strong demand has driven significant growth in supply, with the overall market size and investment in critical minerals expanding rapidly. For instance, prices of lithium, cobalt, nickel, and graphite experienced sharp declines in 2023 due to supply market expansion.⁵⁰ However, a longer-term perspective reveals that challenges in balancing the supply and demand of critical minerals persist across all sub-technology scenarios. Our findings partially corroborate the IEA’s concerns that “today’s well-supplied market may not be a good guide for the future, as demand for critical minerals continues to rise.”

Discussion

Our study reaffirms the critical importance of addressing the availability of key minerals. Achieving the target of tripling renewable energy capacity by 2030 demands accelerated action across all sectors, but this acceleration must be built on a well-managed foundation of resource availability.

The critical mineral issue is increasingly being viewed through the lens of technological development. Our analysis reveals that some emerging technologies, or existing technologies with advantages in technical characteristics, may lead to greater mineral bottlenecks, affecting the scaling up of their deployment. Currently, the development of emerging low-carbon technologies generally focuses on improving technical characteristics and efficiency, such as the emergence of solid-state batteries.⁵¹ Future technological development and commercialization should also take material availability into account. On the other hand, accelerating mineral supply can effectively resolve this contradiction, as the Earth’s resources are sufficient to support the low-carbon transition.

Our analysis remains subject to various uncertainties, including geopolitical tensions, environmental and human rights concerns, and unforeseen “black swan” events.⁵² For instance, domestic instability in the Democratic Republic of the Congo could potentially affect cobalt exports; China may, under certain conditions, impose export restrictions on materials such as graphite or rare earths; and Indonesia has implemented restrictions on the export of unprocessed or low-grade nickel ore. These examples illustrate two notable features of the global mineral supply system: first, many critical minerals are highly geographically concentrated; second, this concentration—while efficient under stable conditions—significantly increases the system’s vulnerability to unexpected shocks.

Due to varying mineral requirements across low-carbon technologies, the exposure to such risks differs by technology and geography. For example, as one of the world’s largest wind turbine manufacturers, China is less likely to be affected by rare earth supply constraints, whereas manufacturers outside China may face limitations in adopting permanent-magnet-based technologies. In contrast, the supply of nickel and cobalt is poorly aligned with the global distribution of downstream battery manufacturing. As a result, sub-technologies that rely heavily on these materials, such as high-nickel chemistries, may be more vulnerable to disruptions. This further underscores the need to strengthen international cooperation, particularly in the coordination of mineral-related technologies and investments, and to minimize the impact of uncertainties such as geopolitical risks.^53,54

Our findings are also subject to uncertainties stemming from key modeling assumptions. To evaluate the robustness of our results, we conducted sensitivity analyses on three critical parameters: (1) alternative commercialization pathways for emerging technologies, (2) improvements in material efficiency, and (3) the scale-up of recycling efforts. The modeling assumptions and outcomes for each sensitivity case are documented in Section S5.

First, rare earth demand was found to be particularly sensitive to the market share of DD-PMSG, with each 1% increase in DD-PMSG adoption leading to an estimated 0.8% rise in rare earth demand by 2030. In contrast, other sub-technology shifts have a more limited impact. Second, advancements in material efficiency, as well as the successful commercialization of some technologies currently at the laboratory stage, could ease certain mineral requirements. For example, a 1% reduction in indium intensity in perovskite tandem or SHJ solar cells may lead to a nearly 0.9% decline in total indium demand by 2030. Replacing current solid-state battery assumptions with lithium–sulfur all-solid-state batteries—still at the research stage—could lower average demand for nickel, manganese, and cobalt by around 15% by 2030, while slightly increasing lithium needs. Third, scaling up recycling, especially for metals like silver, aluminum, and copper, could meaningfully alleviate future supply pressures. For strategic minerals such as lithium, cobalt, and rare earths, more effective recycling systems (e.g., standardized product design and improved recovery technologies) will be essential for reducing dependence on primary resources.

Overall, the evidence presented suggests that the availability of critical minerals will be a significant challenge in achieving the target of tripling renewable energy capacity. Diversification of sub-technologies and new technologies will not effectively resolve this issue. The target will drive a 6.4-fold increase in demand for key minerals, with supply-demand imbalances for graphite, cobalt, lithium, tellurium, indium, silver, aluminum, copper, and magnetic REEs being particularly strained. Deployment of photovoltaics, wind power, and EVs will face these constraints, with technology paths relying on thin-film solar, NCM batteries, and direct-drive wind turbines further exacerbating mineral bottlenecks. Early adoption of emerging technologies like perovskite solar cells and solid-state batteries is unlikely to alleviate these pressures. From a global perspective, we believe that accelerating the production of critical minerals, maintaining the stability of global critical mineral supply chains, and continuously optimizing material efficiency in deployment technologies, while continuing to develop alternative technologies, remain relatively more effective strategies.

Limitations of the study

This study assumes a balanced global supply of critical minerals, while regional geopolitical, trade, and policy dynamics may cause significant variations. Assumptions on emerging technologies are based on laboratory or small-scale commercial research, and actual mineral demand may differ as these technologies scale.

Resource availability

Lead contact

Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Baihe Gu (gubaihe@casisd.cn).

Materials availability

This study did not generate new unique reagents.

Data and code availability

• •All data reported in this paper will be shared by the lead contact upon request.
• •This paper does not report original code.
• •Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (nos. 72374192 and 72140007), Youth Innovation Promotion Association of Chinese Academy of Sciences (no. 2022151).

Author contributions

D.Y.: conceptualization, visualization, and writing – original draft. B.G.: conceptualization, supervision, methodology and writing – review & editing. M.Z.: formal analysis, and writing – review & editing. M.D.: conceptualization, writing – review & editing. All authors discussed the results and approved the article.

Declaration of interests

The authors declare no competing interests.

Declaration of generative AI and AI-assisted technologies

During the preparation of this work, the authors did not use any tools or services.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Software and algorithms
Python version 3.6	Python Core Team	https://www.python.org/

Method details

We conduct a critical minerals demand analysis under the tripling of renewable energy capacity target in three steps. Further details on our model, key assumptions, and parameters are provided in supplemental information. Below is an overview of our method.

Low carbon energy technologies capacities

We select key technologies including photovoltaics, wind power, electrochemical storage, and EVs/PHEVs. Given the full target, which includes further improvements in the global average annual energy efficiency rate, we incorporate EV and PHEV sales into our installed capacity considerations. Our capacity scenario is then developed in alignment with IRENA’s 1.5°C pathway projections.

Sub-technology and market share

Based on our review and analysis, we developed sub-technology scenarios to explore market dynamics and material demand for critical low carbon energy technologies. This process included the following components.

Identifying sub-technologies

We conducted a comprehensive review of existing sub-technologies within each low carbon technology. This included examining market reports from major industry associations and technology alliances, as well as commercial trend reports, to classify sub-technologies. A bottom-up analysis was then performed, detailing: the technical characteristics of each low carbon energy technology, key components along the supply chain and differences among sub-technologies. This analysis extended to next-generation and emerging sub-technologies, considering their commercial potential, and identifying the critical minerals required for each. The resulting list of sub-technologies and associated minerals is provided in Table S5.

Scenario design

The scenario design for different sub-technology pathways is divided into two steps.

Assessment of capacity expansion potential

Reviewing market trends and technical characteristics to determine whether technology can support capacity expansion before 2030. For emerging technologies, we require at least demonstration-level commercialization.⁵⁵ For existing market technologies, we consider potential efficiency or feature improvements and/or strong policy support (e.g., thin-film photovoltaics, which are supported by the IRA for First Solar).

Determination of potential market shares by 2030

Based on a literature review, for the BAU scenario, sub-technology market shares are derived from industry reports specific to each technology—photovoltaics are referenced from International Technology Roadmap for Photovoltaic (ITRPV) and China Photovoltaic Industry Association (CPIA), wind power market development data are sourced from Global Wind Energy Council, and battery information comes from the IEA. For alternative market share scenarios, we assign a predetermined market share for specific technologies with potential for expansion, as informed by the literature review (Table S5). For example, in the MoreTF scenario, we assume that the market share of thin-film photovoltaics will increase from 5% in the BAU scenario to 20%, while the market share proportions of the other sub-technologies remain unchanged relative to the BAU scenario.

We designed three key scenarios for each low carbon energy technology to reflect varying market trajectories.

• Solar PV: BAU (Business-as-Usual): Crystalline silicon PV dominates the market, MoreTF: Thin-film PV achieves a larger market share and MoreTD: Perovskite tandem cells achieve early breakthroughs.

• Wind Power: BAU: Geared double-fed induction generators (GB-DFIG) and direct-drive permanent magnet synchronous generators (DD-PMSG) dominate, MoreDD: Market share of DD-PMSG increases significantly and MoreGP: Medium-speed geared permanent magnet synchronous generators (GB-PMSG) gain prominence.

• Batteries: BAU: LFP batteries dominate, MoreHM: Nickel-cobalt-manganese (NCM811/622) batteries achieve higher market penetration and MoreAB: Solid-state batteries make significant early-stage progress.

Details on the design of these scenarios and the underlying assumptions are provided in the Tables S6–S8.

Mineral intensity and demand estimation

Our mineral demand estimation process involves three sub-steps.

Mineral intensity analysis

To determine mineral intensities, we conducted an independent literature review and selected the most reliable data. For most sub-technologies, we used baseline mineral intensities derived from life-cycle assessment (LCA) studies. In this step, we further narrowed the scope to 21 critical minerals with robust data availability: Ag, Al, B, C, Cd, Co, Cr, Cu, Ga, In, Li, Mn, Mo, Na, Ni, Se, Si, Te, V, and magnet REEs. Projections for future declines in material intensity were based on a combination of insights from previous studies and efficiency improvements identified in the Step 2 technical analysis. Detailed data and assumptions are provided in the Tables S10–S12.

Estimating primary mineral demand

We calculated the primary mineral demand under different sub-technology scenarios by considering annual installed capacities of technologies, Market shares of sub-technologies, Material intensities of sub-technologies and recycling rates of minerals. The recycling rate refers to the proportion of secondary and reused materials in total supply. These rates were derived from data provided by The United Nations Environment Programme (UNEP), IEA, and previous studies.

Comparing demand with supply

Finally, we compared the estimated mineral demand under various sub-technology scenarios with primary supply projections. This analysis incorporated additional demand from non-energy sectors, under the conservative assumption that their demand remains constant through 2030. Primary supply data were sourced from the World Mining Database (WMD) and United States Geological Survey (USGS). Non-energy sector demand was estimated using data from USGS and other supplementary sources. Further details on the methodology and parameters are provided on Tables 13 and S14.

Quantification and statistical analysis

No statistical tests were performed in this study. The analysis is based on a scenario-driven modeling framework. Details of the model structure, parameter settings, and key assumptions can be found in supplemental information.

Published: August 5, 2025