Lithium, graphite and REEs may outpace aluminium growth due to smaller starting bases, says OLI’s Chief Sustainability Officer

In an exclusive conversation with AL Circle, Vineeth Ram, Chief Sustainability Officer of OLI Systems, shares his perspectives on rare earth processing in the United States, the country’s growing demand for REEs, and its roadmap for reducing dependence on China. While he notes that complete self-sufficiency is not a realistic near-term goal, he believes that significantly reducing dependence is achievable.

Talking about the demand growth of aluminium and other critical minerals, he explains that minerals like gallium, graphite and REEs are likely to register higher percentage growth than aluminium, largely because they are starting from much smaller demand bases.

At the same time, he highlights that aluminium is increasingly being recognised globally as a critical and strategic mineral due to its growing usage in electricity networks, aerospace, defence and clean-energy technologies. Alongside, he shares his views on the aluminium industry’s primary decarbonisation pathway, which includes low-carbon electricity, increased recycling, energy and process efficiency, and inert-anode technologies.

Vineeth Ram leads sustainability strategy, government engagement, strategic research partnerships, and emerging market initiatives at OLI. His work spans critical materials, carbon capture, utilisation and storage, geothermal energy, industrial water, corrosion, and asset integrity, with a focus on translating chemistry innovation into scalable industrial and commercial outcomes.

AL Circle: With China dominating rare earth processing, refining, and magnet manufacturing, how realistic is it for the US and other countries to meaningfully reduce dependence? What are the main bottlenecks that could hinder these efforts?

Vineeth Ram: It is realistic to reduce dependence, but it is neither realistic nor necessary to expect complete self-sufficiency in the near term. The more practical goal is a diversified and resilient supply chain in which no single country controls every stage - from mining and separation through metals, alloys, component qualification, and magnet manufacturing.

The most difficult bottleneck is often not the availability of ore. It is the midstream: converting variable feedstocks into products that consistently meet demanding purity and performance specifications. Rare-earth separation and refining involve complex hydrometallurgy, multiple stages, strong interactions among metals and ligands, tight pH and redox windows, substantial reagent use, and residues that must be managed responsibly. New projects must also overcome permitting, capital intensity, specialised workforce and equipment, customer qualification, offtake certainty, and competition from established producers operating at scale.

The solution therefore requires an ecosystem rather than a series of isolated investments. Governments, national laboratories, universities, technology developers, processors, manufacturers, and end users need to develop projects together so that upstream production is connected to qualified downstream markets.

This is where sustained chemistry innovation matters. OLI has been a founding industry member of the U.S. Department of Energy Critical Materials Innovation Hub since 2013. Long-running research with national laboratories, universities and industrial partners has expanded the chemistry and process knowledge available for rare earth elements, lithium, nickel, cobalt, and manganese.

That knowledge is then embedded in models and databases that can be reused across future research and industrial projects. In that sense, the technology becomes a knowledge multiplier: each validated research programme strengthens the platform available to the next project.

Predictive process modeling can help reduce technical and financial risk throughout development. It can compare leaching and separation pathways, identify credible operating windows, anticipate unwanted precipitates, estimate reagent requirements, and focus experiments on the most promising conditions. Chemistry-informed AI can then explore a much larger design space, while first-principles models and experimental validation prevent it from recommending conditions that are chemically impossible or unsafe.

No model removes the need for pilot plants and qualification. Its value is to make each experiment, pilot campaign, and capital decision more informative. That can shorten development cycles, reduce trial and error, and improve the probability that a technically promising process can become a reliable commercial operation.

AL Circle: Aluminium is recognised as a critical material alongside other minerals. From a sustainability and industrial perspective, what differentiates aluminium's strategic importance, and how does its demand growth compare with other critical minerals in the US, EU, and UK?

Vineeth Ram: Aluminium is strategically important for a different reason than many rare or specialty minerals. Its importance comes from its enormous scale, breadth of use and role as an enabling material across transportation, electricity networks, construction, packaging, aerospace, defence and clean-energy technologies. It is also highly recyclable, although the real environmental and economic performance of recycling depends on collection, sorting, alloy management, contamination control, and the energy used for remelting.

At the same time, primary aluminium production is highly energy-intensive. That creates a productive tension: aluminium is essential to electrification and decarbonisation, but its own value chain must continue to reduce energy use, emissions, water consumption, and waste. Cleaner electricity, higher recycling rates, improved yield, process intensification, better control of impurities and lower-carbon refining and smelting technologies all matter.

The policy recognition is increasingly explicit. Aluminium is included on the United States' final 2025 Critical Minerals List. The European Union treats the bauxite-alumina-aluminium value chain as both critical and strategic, and the United Kingdom includes aluminium within its critical- and growth-minerals framework.

Demand comparisons should be interpreted carefully. Lithium, graphite, and some rare earth elements may grow faster in percentage terms because they begin from much smaller bases. Aluminium may grow more moderately as a percentage, but it represents vastly greater physical volumes and touches many more sectors. Its strategic significance is therefore not only the rate of demand growth; it is the economy-wide consequence of disruption.

The aluminium value chain can also contribute to the supply of other critical materials. Bauxite process liquors and residues can contain gallium, scandium, titanium, and rare earth elements. Red mud, in particular, illustrates how a historical waste liability may become a secondary resource. The challenge is not simply whether valuable elements are present, but whether they can be recovered selectively, safely, and economically from a complex iron-rich and highly alkaline matrix.

That is where hydrometallurgical modeling can add value. By predicting metal speciation, solubility, complexation, acid and base consumption, precipitation and competing reactions, industry can compare recovery pathways before committing to large experimental programmes or equipment. Better chemistry insight can improve yield, reduce waste, use less energy, and water, and keep assets operating safely for longer - strengthening both sustainability and profitability.

AL Circle: Gallium, sourced from bauxite, is critical for semiconductors, defense, and solar tech. Given the US lacks domestic bauxite production, how dependent is the country on imports, and what are the implications for manufacturing costs and margins?

Vineeth Ram: The United States does not currently produce low-purity, unrefined gallium and depends on imports to meet that requirement. Gallium is used primarily in compound semiconductors such as gallium arsenide and gallium nitride, which support communications, power electronics, defence systems, LEDs, solar technologies, and other advanced applications.

The vulnerability is not only the absence of domestic bauxite production. Gallium is generally recovered as a byproduct of much larger bauxite or zinc-processing operations. The strategic constraint is the limited availability of an integrated recovery, purification and refining chain that can consistently produce material meeting demanding semiconductor-grade specifications.

For many downstream products, gallium may be a small share of final product cost. However, a shortage of small-volume input can interrupt production of a much higher-value component. The financial impact therefore extends beyond the spot price of the metal. It can include higher inventories, supplier qualification, process redesign, delayed deliveries, lost production and margin pressure across semiconductor, aerospace, energy and defence supply chains.

A diversified strategy should include allied-country supply, recovery from bauxite and zinc processing, recycling, and the evaluation of existing bauxite-residue inventories. Red mud is particularly interesting because it may contain gallium together with scandium, titanium, and rare earth elements. However, it is also a technically difficult feedstock because of its highly alkaline, iron-rich, and chemically complex composition.

Recovering value from it requires a detailed understanding of metal speciation, solubility, competing precipitation reactions and separation behavior. Experience developed across rare-earth and related critical-material recovery systems can therefore be directly relevant to evaluating which leaching, purification and separation pathways are technically and economically viable. OLI’s work in these areas includes modeling capabilities that can help researchers and process developers assess these complex interactions before committing to extensive laboratory and pilot-scale testing.

The technical challenge is selectivity. Valuable elements may be present at low concentrations in a matrix containing much larger quantities of iron, aluminium, sodium, silica, calcium, and other species. A recovery process must manage not only extraction, but downstream purification, reagent recycle, residue stability, water balance, and product specifications.

Chemistry-based simulation can help researchers understand which species are present, how much acid or base will be consumed, where solids may form, which ligands or solvents are selective, and how changes in feed composition affect the flowsheet. Coupled with experiments and techno-economic analysis, that knowledge can help determine whether a recovery concept is merely chemically possible or has a credible pathway to commercial deployment.

AL Circle: Amid the Middle East-driven oil and gas crisis, how is OLI leveraging its predictive solutions to help operators safeguard assets and ensure supply continuity, particularly for energy-intensive industries like aluminium?

Vineeth Ram: Periods of energy-market disruption place extraordinary pressure on operators to maintain production while managing changing feedstocks, altered operating rates, constrained maintenance windows and volatile energy and chemical costs. Those same conditions can increase asset-integrity risk. A facility may be asked to operate outside its normal envelope precisely when an unplanned shutdown would be most damaging.

OLI helps operators understand how the underlying chemistry changes as temperature, pressure, composition, water content, acid gases, salts, and trace impurities change. In oil and gas production and refining, these variables influence corrosion, mineral scaling, salt formation, phase behavior, water treatment, and materials performance. Predictive models allow engineering teams to test scenarios, define integrity operating windows, and identify where risk may increase before the problem becomes visible in the plant.

For aluminium producers, the unit operations are different, but the management principle is similar. Energy-intensive facilities need to know how far they can adjust throughput, energy inputs, water sources, feed composition, or maintenance schedules without creating new scaling, corrosion, and fouling, product-quality, or reliability problems.

Physics-based models can also be combined with plant data and AI. Plant data reveal what is happening; first-principles chemistry helps explain why it is happening and whether a recommendation remains credible outside the historical dataset. This is particularly important in volatile conditions when operations may move into regimes the plant has not previously experienced.

The goal is not merely to predict failure. It is to help operators preserve safe production, avoid unnecessary conservatism, and make defensible decisions. During periods of supply stress, a serious accident or extended outage would be damaging not only economically, but also to environmental performance and broader sustainability commitments.

AL Circle: Energy and water are essential for both aluminium production and data centres. How does OLI ensure long-term, sustainable, and reliable supply to industrial users? In cases of competing demand, how should priorities be balanced for economic and sustainability goals?

Vineeth Ram: OLI does not produce electricity or water, so our role is not to guarantee supply. Our contribution is to help industrial users obtain more productive, reliable, and sustainable use from the energy and water that are available.

For both aluminium facilities and data centres, water quality is as important as water quantity. Salts, silica, alkalinity, chlorides, dissolved gases, and trace contaminants determine how much water can be recycled, how many concentration cycles are possible, which treatment methods are viable, and where scaling, corrosion or fouling will limit reliability.

Predictive chemistry and process simulation can evaluate alternative water sources, cooling-water strategies, desalination or membrane systems, brine concentration, chemical treatment, reuse, and zero-liquid-discharge options. A digital twin can then combine operating data with first-principles models to adjust recommendations as source-water chemistry, weather, heat load, and production conditions change.

The same lifecycle approach applies here. Modeling can support an early water and energy business case, prioritise laboratory testing, inform pilot design, define equipment requirements, and then support operating optimisation. Because the underlying chemistry is reusable, knowledge generated for one treatment train or industrial sector can strengthen the platform used in later projects.

Competing demand should not be resolved by declaring one industry inherently more deserving than another. Decisions should consider public-health needs, local community impacts, employment, national and regional economic value, grid and water-system reliability, environmental consequences, and the realistic availability of alternative supplies.

Large industrial users should also be expected to improve efficiency, use reclaimed or lower-quality water where technically feasible, support enabling infrastructure and avoid shifting disproportionate cost or risk to local communities. The most sustainable unit of water or electricity is often the unit made available through efficiency, reuse, better process design, and avoided losses.

AL Circle: How is OLI applying carbon capture technologies in carbon-intensive industries such as aluminium, and what measurable impact have these solutions had on emissions reduction and operational efficiency?

Vineeth Ram: It is important to distinguish between supplying carbon-capture equipment and providing the chemistry and process models needed to evaluate, design, and operate capture systems. OLI’s role is the latter.

Carbon capture is not currently the aluminium industry’s primary decarbonisation pathway. The main levers are low-carbon electricity, increased recycling, energy and process efficiency, inert-anode technologies that avoid emissions from consumable carbon anodes, and electrification or potentially hydrogen for refining and calcination heat. Carbon capture remains an additional option under evaluation, particularly for concentrated or difficult-to-abate emissions.

Where capture is considered, the key question is whether a specific capture, conditioning, transport, or utilisation pathway is technically and economically credible at a given facility. This depends on gas composition, impurities, available heat and electricity, water chemistry, solvent behavior, materials compatibility, and integration with existing operations.

Chemistry and process modeling can help answer these questions. Capture systems involve complex interactions among CO2, water, solvents, salts, impurities, solids, and construction materials. Predictive models can support solvent selection, absorption and regeneration, heat and mass balances, solvent degradation, impurity management, precipitation, water management, and corrosion assessment.

Impurity chemistry is especially important across the CCUS value chain. In capture, modeling can support solvent performance and degradation management. During conditioning and transport, it can assess phase boundaries, water dropout, acid and salt formation, and corrosion risk. For injection and storage, it can evaluate interactions among CO₂, formation brines, minerals, wells, and containment systems. Similar chemistry can support selected utilisation and mineralisation pathways involving alkaline industrial residues.

These capabilities have been strengthened through sustained research, including OLI’s work with the Institute for Energy Technology in Norway and a global industry consortium studying CO₂ transport and impurity effects and U.S. Department of Energy funded projects. Experimental data and mechanistic insights from such programs are incorporated into reusable models and software, allowing knowledge developed in one project to support future feasibility studies, laboratory work, pilots, demonstrations, and commercial operations. This is how research becomes a knowledge multiplier for the wider industry.

For aluminium producers, potential applications include emissions from refinery heat and steam generation, calcination, smelter, and anode operations, and supporting power assets. Modeling can test whether proposed solutions remain viable under realistic impurities and operating conditions, focus experimental and pilot work, and identify concepts that may be limited by energy use, corrosion, solvent degradation, water demand, or poor process integration.

Environmental and operational impacts must be measured project by project. Relevant indicators include tonnes of CO2 captured or avoided, capture efficiency, regeneration energy, solvent and water use, impurity tolerance, equipment availability, corrosion, maintenance and compression and transport energy. A high theoretical capture rate may deliver limited value if it also causes excessive energy use, degradation, or downtime.

Some of aluminium’s most immediate sustainability opportunities may lie outside carbon capture. These include recovering gallium, scandium, rare earth elements and other valuable materials from bauxite residue and improving industrial-water reuse and reliability. Both depend on understanding speciation, solubility, precipitation, and separation behavior in complex systems.

In complex industrial systems, sustainability and profitability are frequently the same engineering problem: improving yield, reducing waste, using less energy and water, and keeping assets operating safely for longer.

AL Circle: With oil and gas markets under pressure due to the Middle East conflict, what near-term dynamics should manufacturing industries like aluminium producers are aware of, and how can the industry adapt to energy volatility while maintaining sustainable operations?

Vineeth Ram: Manufacturers should prepare for volatility rather than build plans around a single oil- or gas-price forecast. The near-term risks include the reliability of shipping routes, regional gas and electricity availability, refined-product tightness, freight and insurance costs, availability of raw materials and reagents, and the possibility that these variables move in different directions at the same time.

Aluminium is particularly exposed because its value chain depends on reliable electricity and on international flows of bauxite, alumina, carbon materials, caustic, fuels, and finished metal. Disruption can therefore affect both operating cost and the physical ability to sustain production.

The appropriate response begins with scenario planning. Producers should identify which energy, feedstock and logistics disruptions would constrain operations first; assess alternative suppliers and transportation routes; determine appropriate inventories for truly critical inputs; and understand contractual exposure to power, gas, freight, and commodity prices.

Operational flexibility is equally important. Plants should know the safe and economic limits within which they can alter production rates, feed composition, energy inputs, water sources, and maintenance schedules. Predictive process models can help determine whether an apparently economical operating change could create product-quality problems, higher reagent consumption, scaling, corrosion, increased waste, or a later reliability failure.

Safety and asset integrity deserve particular emphasis during volatile periods. Pressure to sustain production should not push equipment beyond a defensible operating envelope. A major incident would be catastrophic for people and the environment, and it would undermine the very sustainability and supply-continuity objectives the industry is trying to protect.

Sustainability should not be suspended during a crisis. Efficiency becomes more valuable when energy and materials are expensive. Measures that improve yield, recover byproducts, reduce energy, and water losses, extend equipment life, and increase recycling generally strengthen both resilience and environmental performance.

The broader lesson is that operational continuity and sustainability are not opposing objectives. In complex industrial systems, sustainability and profitability are frequently the same engineering problem: improving yield, reducing waste, using less energy and water, and keeping assets operating safely for longer.