The scale of the challenge is staggering. China alone consumes roughly half of the world’s lithium, driven largely by its dominant position in the electric vehicle market, and has pledged to cut greenhouse gas emissions by 60 to 65 percent by 2030. Meanwhile, mining these metals generates vast quantities of tailings laden with heavy metals and chemicals. When improperly disposed of, these wastes contaminate water supplies, destroy biodiversity, and degrade soil — with acid mine drainage, in which sulfide minerals oxidize to produce extremely acidic runoff, posing the single greatest threat to water quality across large regions. Conventional recycling routes offer little relief: pyrometallurgical smelting is energy-hungry, while hydrometallurgical leaching demands aggressive acids and generates sludge and saline effluents of its own.

Membranes work on an entirely different principle. Instead of burning or dissolving entire waste streams, they act as molecular gatekeepers — semi-permeable barriers that allow some ions to pass while blocking others based on size, electrical charge, or specific chemical interactions. Pressure-driven systems such as ultrafiltration, nanofiltration, and reverse osmosis push liquid through these barriers, while electro-driven systems like electrodialysis use an applied voltage to steer ions toward oppositely charged electrodes. The review categorizes four main feed streams — battery leachates, acid mine drainage, salt-lake brines, and industrial effluents — each with distinct chemistries that demand tailored membrane approaches rather than one-size-fits-all solutions.

The most striking results come from lithium recovery. In acidic sulfate leachates from spent batteries, lithium exists largely as free Li+ ions while cobalt, nickel, and manganese form sulfate complexes. Negatively charged nanofiltration membranes exploit this difference: they repel the multivalent transition metal cations through electrostatic repulsion and size exclusion while allowing the smaller, singly charged lithium ions to permeate. One study cited in the review achieved 99.5 percent pure lithium carbonate after just two nanofiltration passes — approaching battery-grade material without harmful chemical additives. Another research group using polymer inclusion membrane electrodialysis, where selective carriers embedded in a PVDF-HFP polymer matrix bind lithium and cobalt ions, reported recoveries of 99.1 percent for lithium and 99.9 percent for cobalt, with a carbon footprint of just 3.1 kilograms of CO2-equivalent per kilogram of lithium recovered.

Separating lithium from magnesium in brines presents an even tougher puzzle because the two ions have similar ionic radii. Here, the review explains that the key lies in hydration energy: magnesium ions hold water molecules far more tightly than lithium does, giving Mg2+ a bulkier, more strongly bound hydration shell. Negatively charged nanofiltration membranes exploit this by electrostatically repelling the divalent magnesium while the monovalent lithium slips through more easily. Separating cobalt from nickel is harder still — both are divalent with nearly identical hydrated radii — so simple charge exclusion fails. Supported liquid membranes, which impregnate a porous support with a tailored organic extractant that reversibly binds one metal preferentially, offer a way forward, achieving extraction and stripping efficiencies of 85.7 and 83.2 percent for nickel in one reported case.

But the review is refreshingly honest about where membranes struggle. Real battery leachates are not clean laboratory solutions: they are acidic (often below pH 2), highly saline, loaded with organic residues from binders and electrolytes, and contain a shifting cast of competing ions. Under these conditions, membranes fail in chemistry-specific ways. Precipitation is the most common culprit — as pH, temperature, or ionic strength shifts, salts like calcium carbonate, magnesium hydroxide, and gypsum (calcium sulfate dihydrate) become supersaturated and crystallize on membrane surfaces, blocking pores and causing irreversible flux decline. Iron and aluminum hydrolyze into gelatinous hydroxides that clog membranes, while oxidants such as hydrogen peroxide and hypochlorite — often added during leaching — attack polyamide membranes chemically, degrading the polymer itself.

Long-term durability emerges as the review’s central concern. In one particularly revealing study, commercial NF270 and DK nanofiltration membranes were exposed to hydrochloric acid at pH 1 for up to 30 days. Both initially retained divalent ions at 96.5 percent or better, but NF270’s rejection dropped from 99.1 to 84.3 percent over the exposure period — a systematic decline the authors attribute to acid hydrolysis of the polyamide active layer. Another group incorporated sulfonated covalent organic framework nanosheets into a nanofiltration membrane to boost acid resistance; initial lithium rejection was moderate at 43.7 percent while divalent metals exceeded 90 percent, but even this engineered membrane lost significant performance after 7 to 14 days in acid. The lesson, the review argues, is that short-term laboratory tests cannot predict months-long industrial performance.

On economics, the numbers are encouraging but conditional. Membrane processes like electrodialysis and nanofiltration typically consume 0.5 to 5 kWh per cubic meter of treated water — substantially less than conventional thermal or precipitation-based routes, which can exceed 10 kWh per cubic meter when the full water-intensive mining chain is accounted for. Membrane-hybrid systems have demonstrated 50 to 84 percent reductions in total energy demand compared to conventional solvent extraction. Lithium recovered from salt-lake brines costs roughly USD 2 to 3 per kilogram, compared with around USD 80 per kilogram from seawater, while lithium carbonate commands a market price near USD 24 per kilogram — making brine-based membrane recovery economically attractive. Polymeric membranes last 5 to 8 years and ceramic membranes 15 to 20, offering long-term savings through reduced replacement frequency.

Yet the review is careful to position membranes as complementary rather than replacement technology. Nanofiltration achieves lithium selectivity in the 70 to 90 percent range with transition metal rejections typically above 90 percent, but separating chemically similar divalent cations like nickel from cobalt remains limited. Fluxes in concentrated leachates are often constrained to below 10 liters per square meter per hour due to osmotic pressure and fouling. Membranes excel at lithium concentration and acid recovery, but solvent extraction or precipitation is still needed for full transition metal separation. The realistic industrial pathway, the authors suggest, is a hybrid flowsheet: membranes as selective concentration and acid-recycling steps, followed by conventional precipitation to deliver battery-grade products.

The review’s conclusion is both a warning and a roadmap. The principal bottleneck in membrane-based critical material recovery is not initial separation performance — many studies already report 90 to 99 percent recovery — but sustained stability, fouling control, and honest accounting of energy per kilogram of product, membrane lifetime, and cleaning frequency under realistic leachate conditions. Few studies report these parameters, and most rely on simulated rather than real battery-derived streams. Future progress, the authors argue, depends on targeted material innovations such as acid-resistant thin-film composites and crown ether-functionalized ion-exchange membranes, thorough long-term stability testing, and integration into holistic pretreatment and recovery trains. If those gaps close, membranes could shift from promising laboratory curiosities to indispensable components of a circular economy that treats yesterday’s batteries and mine waste as tomorrow’s ore bodies.

Subject of Research: Membrane-based separation technologies for recovering critical metals from spent batteries and mineral wastes

Article Title: Membrane-based extraction of critical materials from spent batteries and other mineral wastes

Article References: Matebese, F., Raseala, M. J., & Moutloali, R. M. (2026). Membrane-based extraction of critical materials from spent batteries and other mineral wastes. Frontiers in Membrane Science and Technology, 5, Article 1766669. https://doi.org/10.3389/frmst.2026.1766669

Image Credits: AI Generated

DOI: 10.3389/frmst.2026.1766669

Keywords: membrane technology, lithium recovery, battery recycling, nanofiltration, electrodialysis, acid mine drainage, critical materials, circular economy, cobalt, nickel, fouling, hydrometallurgy

Researchers at the Department of Energy’s Oak Ridge National Laboratory have developed a response to this dilemma. The platform, called Motor Decide, is described by its creators as a Super Intelligence, or SI, driven decision-support tool that helps manufacturers evaluate competing electric motor technologies before market conditions shift against them. Rather than telling a company which motor to build, the system models how different motor options would perform across a range of future scenarios, weighing performance characteristics against critical material availability, supply chain stability, technology maturity and long-term resilience to changing market conditions. The goal is to move technology selection away from instinct and toward structured, data-driven analysis.

“Many companies make technology decisions based largely on market momentum or competitor activity,” said ORNL’s Praveen Kumar, lead researcher on the project. “We wanted to create a tool that helps organizations make more informed, data-driven decisions for the long term.” The distinction matters because motor technology choices lock in material demand for years or decades. A manufacturer that commits to a permanent magnet motor design today is implicitly committing to a continued supply of rare earth elements, and if those supplies tighten or prices spike, the entire product line can become economically vulnerable. Motor Decide is designed to surface those hidden dependencies before the commitment is made.

The platform does not design motors directly. Instead, it analyzes which motor technology may be the best fit for a specific application under changing market and supply chain conditions. A manufacturer, for example, could use the tool to compare several motor technologies for an electric system and determine which option would remain the most reliable and cost-effective path to production if material prices spiked or supplies became strained. This scenario-based framing is what separates the tool from conventional comparison exercises, which typically evaluate motors under a single set of assumptions about cost and availability that may be obsolete by the time a product reaches the market.

Under the hood, Motor Decide combines SI-driven analysis, advanced modeling and large-scale scenario analysis to evaluate how motor technologies could perform under fluctuating material costs and supply chain disruptions. Researchers can model what happens if copper prices increase sharply, or if a newer motor technology becomes commercially viable years from now. The output is a ranked set of motor technology options accompanied by insights into cost, performance, critical material use, manufacturability and long-term risk. By quantifying these dimensions together, the platform gives decision-makers a structured view of tradeoffs that would otherwise be scattered across procurement data, engineering assessments and market forecasts.

“We define the operating environment in which the decision is being made,” Kumar explained. “That includes procurement sources, manufacturing readiness, technology maturity and application requirements. Then we test how those factors change under different scenarios.” This approach reflects a broader trend in engineering decision science: rather than optimizing for a single predicted future, robust decision-making tools stress-test candidate technologies across many plausible futures and identify the options that remain viable across the widest range of outcomes. For motor manufacturers, that could mean favoring a design with slightly lower peak performance but far less exposure to rare earth supply risk, or staging a transition plan that shifts material sourcing as new technologies mature.

The platform also accounts for how organizations actually make decisions, helping users evaluate tradeoffs and quantify risk when comparing emerging technologies against established ones. “People ultimately own the decision,” Kumar said. “We are trying to quantify uncertainty and incorporate it into the decision-making process.” That framing positions Motor Decide as a decision-support system rather than an autonomous decision-maker. The tool’s value lies in making the uncertain elements of a technology choice explicit and comparable, so that engineers, procurement specialists and executives can deliberate with a shared, quantified picture of the risks they are accepting.

The project draws on decades of motor, power electronics and transportation research conducted at ORNL’s National Transportation Research Center, the Department of Energy’s only user facility dedicated to transportation research and a hub for advanced mobility innovation. At the center, ORNL researchers work with industry partners to advance next-generation mobility and manufacturing technologies, giving the Motor Decide team direct access to the technical data on motor performance and manufacturability that such a platform requires. “We are combining motor research expertise with SI-driven analysis in a way that can help industry make smarter, more resilient technology decisions,” Kumar said. Researchers envision the tool helping manufacturers reduce dependence on vulnerable supply chains while planning future products more strategically.

Motor Decide is also designed to work alongside another ORNL-developed platform, Motor AI, which uses SI-assisted engineering tools to accelerate detailed motor design. The two systems form a pipeline: while Motor Decide helps identify the best motor technology pathway for a given application and market outlook, Motor AI performs the detailed design work needed to bring those concepts to life. Once a company selects a preferred motor approach, researchers can transition the results into Motor AI to generate detailed design configurations and engineering specifications. Together, the tools could help accelerate the development of more resilient electric motor systems while reducing the risks associated with critical material shortages, volatile supply chains and rapidly changing global markets.

The effort reflects ORNL’s broader mission to combine super intelligence, advanced manufacturing and energy research in support of U.S. competitiveness and industrial resilience, and researchers are continuing to evaluate and expand the platform’s capabilities for future applications. The project was funded by the Department of Energy’s Office of Critical Minerals and Energy Innovation’s Transportation Technologies Office, an alignment that underscores the federal government’s growing focus on securing the material foundations of electrification. As industries from automotive to aerospace confront the same arithmetic of rising demand and constrained supply, tools like Motor Decide suggest a future in which the materials risk embedded in every engineering choice can be measured, modeled and managed before it becomes a crisis. UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States.

Subject of Research: A decision-support platform for evaluating electric motor technologies against critical material supply chain risks

Article Title: New platform tackles critical material risks in electric motors

Article References: New platform tackles critical material risks in electric motors. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: electric motors, critical materials, supply chain, rare earth elements, copper, Oak Ridge National Laboratory, Super Intelligence, decision support, manufacturing, Motor Decide, Motor AI, transportation research

The research team, led by Jingwei Hou and Yong Geng, applied dynamic material flow analysis (dMFA), a mass-conservation accounting framework that tracks every tonne of a substance through extraction, refining, manufacturing, use, and disposal. Their system boundary covered mainland China and divided the boron industry chain into seven stages: mining and beneficiation, refining and separation, smelting, fabrication, manufacture, use, and waste management and recycling. Thirty-eight boron-containing commodities were tracked, with trade data drawn from China Customs Yearbooks and the UN Comtrade database, production statistics from the U.S. Geological Survey and the CBC Metal database, and process parameters validated through field visits to major producers and ten face-to-face interviews with industry executives and technical personnel.

The methodological machinery is considerable. Process flows were calculated by multiplying production quantities by boron concentrations, losses were applied at each stage using documented loss rates, and the accumulation and retirement of boron in products was modeled with a Weibull probability distribution, the standard statistical tool for describing how products fail and exit service over time. To test robustness, the team ran a Monte Carlo simulation with 10,000 iterations, assigning coefficients of variation of 5 percent to reliable official statistics and 10 percent to literature-derived parameters. The results showed uncertainty below 5 percent for imports, exports, and consumption, and 13 to 19 percent for end-of-life flows, narrow enough that the study’s central conclusions hold firm.

The headline numbers are sobering. Over the twenty-year period, net imported boron at the mining and refining stages reached 2,784 kilotonnes, while domestic extraction contributed only 1,026.7 kilotonnes. China’s reserves, ranked fifth globally at 9.1 million tonnes of boron trioxide equivalent, are concentrated in Qinghai and Liaoning provinces but suffer from low ore grades that make domestic mining economically punishing. Turkey, which holds 950 million tonnes of reserves, dominates the global market and supplied roughly half of China’s total boron imports, with borax, boron ores, boric acid, and boron oxides making up 99.5 percent of that bilateral trade. Such concentration in a single supplier exposes China to geopolitical, trade-policy, and natural-disaster risks.

Consumption tells its own story of transformation. Annual boron use climbed from 41.3 kilotonnes in 2004 to a peak of 161.8 kilotonnes in 2021, before easing to 94.6 kilotonnes in 2023 as upstream mining constraints bit. Glass, ceramics, and enamel products consistently absorbed more than 40 percent of total consumption, with the chemical industry, spanning disinfectants, flame retardants, and catalysts, taking another 24 percent. But the fastest growth came from emerging technologies: by 2020, new energy vehicles and batteries accounted for over 4 percent and 8 percent of consumption respectively, a share that seemed set to expand before supply bottlenecks curtailed it.

The losses along the chain are enormous. Refining borax generates roughly four tonnes of boron mud for every tonne of product, and China discharges about two million tonnes of this waste annually, with boron content of only 0.76 percent. Across the full period, total boron losses reached 1,757.1 kilotonnes, while just 24 kilotonnes were recycled, an overall recycling rate of approximately 1.37 percent. Chemical extraction from boron mud requires acid leaching with high reagent and energy costs and risks secondary pollution, so most recovery involves low-value physical processes such as sintering the mud into construction materials. By contrast, Turkey recovers more than 90 percent of boron from industrial wastes, a benchmark the authors argue China should urgently study.

Meanwhile, an invisible reservoir is quietly building. In-use boron stocks, the element embedded in products currently serving society, nearly doubled during the second decade of the study, rising from 502.5 kilotonnes in 2014 to 966.8 kilotonnes in 2023. Glass, ceramics, and enamel dominate this urban mine at 664.2 kilotonnes, followed by batteries, which grew from 25.7 to 68.7 kilotonnes over the decade, earthmoving machinery, glazed tiles, and aircraft. End-of-life flows, delayed by the roughly 16.5-year average lifespan of boron-containing products, entered rapid growth in the 2010s and reached 31 kilotonnes in 2023, signaling a secondary resource stream that current infrastructure is not equipped to capture.

The trade structure reveals a low-value trap. China imported 2,955.2 kilotonnes of boron over the period, dominated by raw and intermediate materials, then exported 1,257.4 kilotonnes of finished products, chiefly glass and ceramics, glazes, and boron steel, to 225 countries and regions, with Indonesia the largest buyer. Fabrication losses ran at roughly 20 percent, and the authors conclude that the whole boron industry chain remains low-value oriented, generating thin profits while imposing heavy environmental pressure. High-end products such as boron carbide, boron nitride, and rare earth borides are still largely manufactured in developed countries, and Chinese enterprises struggle to achieve large-scale production of these materials essential for energy, defense, and nuclear applications.

The policy prescriptions are concrete. The authors call for increased research and development investment and university-industry cooperation to crack the technological bottlenecks in high-end boron products and boron mud valorization, including promising but unconfirmed routes such as converting the waste into nuclear radiation shielding materials or fertilizers. They recommend a national boron information platform, national standards requiring retired boron-containing products to reach designated disassembly stations, and financial support for recycling enterprises. On supply security, they point to diversification through Chile, Russia, Peru, Argentina, Bolivia, and Kazakhstan, countries aligned with China’s Belt and Road frameworks and recent green minerals cooperation agreements. Economic instruments, including differentiated resource taxes tied to ore recovery rates, carbon taxes on energy-intensive operations, emission fees, and green labeling, round out the governance agenda.

What makes this study resonate beyond China is the method itself. dMFA has previously illuminated the metabolism of steel, aluminum, copper, rare earths, and dozens of critical metals, but boron, a nonmetallic critical material with extreme import dependence, had never received this treatment at national scale. As the world’s clean energy transition accelerates demand for every element that hardens steel, toughens glass, and steadies neutrons, the study warns that a country can dominate manufacturing yet remain dangerously exposed at the raw material frontier, and that the urban mines accumulating in its cities, currently leaking 790.7 kilotonnes of boron into the environment as waste, represent both an untapped opportunity and an unaddressed environmental burden.

Subject of Research: Dynamic material flow analysis of boron flows, stocks, trade, and recycling in China from 2004 to 2023

Article Title: Uncovering the features of boron flows and stocks in China

Article References: Hou, J., Geng, Y., Zhong, C., Gao, Z., & Liu, S. (2026). Uncovering the features of boron flows and stocks in China. Environmental Challenges, 25, Article 101675. https://doi.org/10.1016/j.envc.2026.101675

Image Credits: AI Generated

DOI: 10.1016/j.envc.2026.101675

Keywords: boron, material flow analysis, China, critical materials, recycling, supply chain, boron mud, in-use stocks, Turkey, import dependence, urban mining, resource policy