Lithium Shortages Hit Battery Giants Hardest, Global Supply Network Study Finds

The electric vehicle revolution has a hidden Achilles’ heel, and it is not the batteries themselves but the fragile web of companies that mine, refine, and ship the minerals inside them. A new study published in iScience has mapped the entire firm-level supply network of the lithium-ion battery industry and stress-tested it against shortages of lithium, cobalt, and nickel. The results reveal a system that is far more vulnerable than its headline market size suggests, with losses cascading through unexpected pathways and recovery depending less on direct suppliers than on a handful of shared corporate hubs.

The research team, led by Xuena Liu and Haibin Liu, constructed a multilayer supply chain network centered on nine of the world’s dominant battery manufacturers, including CATL, BYD, LG Energy Solution, Panasonic, SK Innovation, CALB, Samsung SDI, Gotion, and EVE Energy. Using the FactSet Revere database of interfirm supply relationships, supplemented by corporate disclosures and stock-market volatility data, they built a directed, weighted network spanning mineral extraction, intermediate materials, battery assembly, electric vehicle manufacturing, and recycling. The timing could hardly be more pressing: global electric vehicle battery demand reached 950 gigawatt-hours in 2024 and is projected to exceed 3 terawatt-hours by 2030, while the International Energy Agency expects electric vehicles and energy storage to account for more than 90 percent of future lithium demand.

The network’s anatomy alone tells a striking story. All nine manufacturer-centered networks follow power-law degree distributions, meaning a few hub firms dominate connectivity while most firms maintain only a handful of relationships. The commodity trader Glencore, the Australian lithium producer Pilbara Minerals, and the Chinese materials firm CNGR each maintain business relationships with seven to nine core battery makers, forming what the authors call cross-layer super-hubs. Meanwhile, most shared nodes connect to only two manufacturers. The networks led by Samsung SDI and LG Energy Solution are strongly correlated with each other and with Panasonic’s, implying that a shock at a shared supplier could transmit simultaneous damage across multiple corporate ecosystems. By contrast, the SK Innovation- and Gotion-led networks show slightly negative correlations, hinting at potential substitutability at certain supply nodes.

When the researchers simulated shortages of increasing intensity, from 10 percent to a complete cutoff of supply, lithium emerged as the most damaging mineral by a clear margin, with network losses ranking lithium above cobalt above nickel under every scenario. This asymmetry reflects chemistry as much as geology. Lithium is an indispensable element in every lithium-ion battery, whereas cobalt is progressively being engineered out of newer cathode designs, and nickel benefits from abundant resources and diversified supply. At a shortage intensity of 0.9, the CATL-dominated network suffered losses of 1171.42 under lithium scarcity, compared with 909.05 for cobalt and 918.45 for nickel. The BYD-led network fared worst of all under lithium stress, reaching 2587.49, a consequence of its enormous lithium iron phosphate production volumes and vertically integrated business model.

Manufacturer-level losses varied dramatically, defying any simple ranking of corporate might. CATL, the world’s largest battery maker, recorded the highest losses across all three minerals, ranging from roughly 130 to 160 under lithium shortages, a pattern the authors attribute to its simultaneous operation of both LFP and high-nickel NMC pathways, which broadens its mineral exposure and concentrates its supplier base. SK Innovation’s network proved exceptionally vulnerable to nickel because its product portfolio is dominated by high-nickel NCM811 cells, while EVE Energy’s cobalt-containing cathode materials and stringent certification requirements concentrated its dependence on upstream refining hubs. Panasonic, by contrast, recorded the lowest losses and responded only weakly to changes in shortage intensity, reflecting its comparatively low structural exposure.

Tracing exactly where the damage came from produced some of the study’s most actionable findings. Under cobalt shortages, a single firm, Glencore, accounted for between 73.43 and 92.75 percent of CATL’s attributed losses, a near-single-source structure in which one disruption could rapidly amplify risk downstream. Nickel losses for CATL were dominated by Glencore and the Indonesian producer Trimegah Bangun Persada, the latter reflecting the localized supply concentration fostered by Indonesia’s nickel ore export ban. Lithium losses were far more dispersed, spread across Tianqi Lithium, Ganfeng Lithium, Yahua, and Albemarle. Path analysis of a total Tianqi Lithium shortage showed that two pathways, a direct cross-chain link to BYD and a long cascade through the midstream materials firm BTR, together accounted for roughly 70 percent of BYD’s total impact, with the cathode makers Hunan Yuneng and Ronbay emerging as the most frequently traversed intermediary nodes.

Perhaps the most surprising result concerns how the industry recovers. The researchers decomposed recovery into three mechanisms: direct restoration through existing supply relationships, indirect recovery through shared nodes that connect multiple manufacturer networks, and recovery through newly established supply links. Indirect recovery dominated overwhelmingly, contributing 70 to 74 percent of total recovery, followed by new links at 15 to 18 percent, with direct recovery contributing a mere 10 to 12 percent. In other words, when a mineral shortage strikes, battery makers do not primarily heal through their own contracted suppliers; they heal through the network’s hidden cross-connections, as shared suppliers reallocate resources across tiers. EVE Energy relied most heavily on forging new relationships, at 35 to 40 percent, while Gotion addressed roughly 40 percent of its shortfalls through existing ties. Recovery pathways themselves were highly concentrated, repeatedly routing through a small group of firms including Hunan Zhongke Electric, Hunan Yuneng, and Tianqi Lithium.

To quantify resilience across the full disruption-and-recovery cycle, the team borrowed the marginal-response logic of price elasticity of demand, regressing each manufacturer’s cumulative loss rate on shortage intensity to obtain a resilience response coefficient. The results exposed a crucial disconnect between loss magnitude and loss sensitivity. Under lithium shortages, CATL combined the highest cumulative losses with the longest recovery requirement, roughly 88 to 90 cycles, and a significantly positive response coefficient of 0.071. Under cobalt shortages, CALB showed the strongest marginal response at 0.420, while under nickel shortages all nine manufacturers responded significantly, with Samsung SDI and EVE Energy posting the highest coefficients at 0.209 and 0.138 despite suffering relatively low cumulative losses. Samsung SDI even recorded a negative coefficient under lithium stress, indicating attenuating losses as intensity grew. High loss, the study concludes, does not necessarily coincide with high sensitivity, and loss rankings alone cannot capture corporate vulnerability.

The findings survived an unusually thorough battery of robustness tests. Inventory buffering of 90 days cut high-end loss rates by up to 24.7 percent under cobalt stress but left manufacturer rankings essentially unchanged, with Spearman correlations above 0.93. Convex nonlinear propagation, meant to mimic order-batching and capacity constraints, raised median cumulative losses by 51 percent yet preserved both the lithium-over-cobalt-over-nickel ordering and the vulnerability rankings. Across 1,500 Monte Carlo parameter combinations, indirect recovery remained dominant with average contributions near 79 percent. Parameterized adaptation, simulating strategic inventories, material substitution, chemistry switching, and contract renegotiation, cut mean cumulative losses by up to 34.7 percent and recovery cycles by 47.4 percent. Recycling networks built around GEM and Umicore already reduced system losses by 10.35 percent under cobalt and 9.69 percent under nickel at full shortage intensity, though strengthening recycling paradoxically increased cobalt losses in some scenarios by rerouting propagation pathways.

The implications reach well beyond corporate boardrooms. The authors argue that critical mineral governance must extend beyond counting reserves and import dependence to monitor midstream processors, shared suppliers, and the deep interfirm relationships through which risk actually travels. Because a small number of pathways contribute disproportionately to downstream losses, targeted interventions such as dual sourcing, pre-qualified backup suppliers, and inventory buffers along dominant routes offer more leverage than blanket diversification. For the energy transition as a whole, the message is sobering: the feasibility of electrifying transport depends not only on how much lithium, cobalt, and nickel the world can extract, but on the resilience of a network whose most important nodes are often invisible until the moment they fail.

Subject of Research: Resilience of lithium-ion battery supply chains to critical mineral shortages

Article Title: Resilience assessment of lithium ion battery supply chains under critical mineral shortages

Article References: Liu, X., Huang, H., An, F., Dong, X., Fang, W., Wang, Y., Zhang, H., Liu, Y., & Liu, H. (2026). Resilience assessment of lithium ion battery supply chains under critical mineral shortages. iScience, 29(10), Article 117703. https://doi.org/10.1016/j.isci.2026.117703

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117703

Keywords: lithium-ion batteries, supply chain resilience, critical minerals, lithium, cobalt, nickel, electric vehicles, risk propagation, network analysis, CATL, BYD, energy transition