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  • Infinium’s 1 MW in 250 Sq Ft Shows Waterless AI Cooling’s Real Test Is Heat Rejection

    Infinium’s 1 MW in 250 Sq Ft Shows Waterless AI Cooling’s Real Test Is Heat Rejection

    TL;DR · 30-second read

    The Short Version

    A Sacramento company best known for making clean fuel has launched a cooling system for the computer buildings behind artificial intelligence. Its selling point is that it uses no water.

    Instead of blowing cold air over computers, it sinks them in a liquid that does not conduct electricity. The company says one unit can handle up to a megawatt of computing, roughly the electricity several hundred homes use, in a space about the size of a large bedroom.

    The catch is that the heat still has to go somewhere, and the company has not said how the system copes on a hot day.

    Infinium, a Sacramento clean-fuel company, has unveiled the EdgeSites Vector ONE, a self-contained data center cooling system that uses no water, the Sacramento Business Journal reported on July 27, 2026. The system submerges servers in dielectric fluid, a liquid that does not conduct electricity, rather than cooling them with air conditioning.

    According to the report, Vector ONE supports up to one megawatt of computing power in 150 to 250 square feet, and the company says it allows computing in 70% less space than air-cooled equipment. No pricing, customers, shipment dates or energy-efficiency figures were given.

    Executive Summary

    Infinium is entering data center cooling with an immersion system, a design in which servers sit in tanks of non-conductive liquid that carries heat away from chips far better than air does. The product, sold under the company’s EdgeSites and Infinium Edge names, is pitched on two claims: it uses no water, and it packs up to a megawatt of computing into a footprint the size of a large room.

    Both claims land on live issues in AI infrastructure. AI servers run hotter and denser than conventional servers, pushing air cooling to its limits, and data center water consumption has become a flashpoint with local communities and regulators. A product that addresses density and water at once is well aimed.

    What the announcement does not yet show is the part that decides whether waterless cooling works at scale: how the system rejects a megawatt of heat to the outdoors, how much electricity that takes, and how its capacity holds up in hot weather, which is exactly when evaporative cooling earns its keep.

    A Megawatt in a Large Room Is the Real Headline

    The most concrete number in the announcement is density. One megawatt in 150 to 250 square feet works out to roughly 4,000 to 6,700 watts of computing per square foot of floor. That is far beyond what traditional raised-floor, air-cooled data halls are built to handle, and it is the kind of concentration modern AI hardware demands. Graphics-processor servers used to train and run AI models pack far more power into each rack than the general-purpose servers most facilities were designed around.

    Immersion cooling makes that density possible because liquid absorbs and moves heat far more effectively than air. The claim of 70% less space follows naturally: without the aisles, air handlers and spacing air cooling requires, servers can sit much closer together. For operators short on floor space, or trying to fit AI capacity into an existing building or a small edge site, that is a genuine advantage.

    Waterless Moves the Hard Problem Outdoors

    Immersion solves the problem of getting heat off the chip. It does not make the heat disappear. Every watt a server draws ends up as heat in the fluid, so a fully loaded Vector ONE has to shed up to a megawatt of heat continuously, and it has to do so from a very small footprint. That step, known as heat rejection, is where the water question is actually decided.

    Many large data centers use evaporative cooling because evaporating water is an extremely effective way to dump heat, especially in hot, dry weather. A system that uses no water must reject heat by dry means, typically fans pushing outside air across heat exchangers. Dry systems avoid water consumption entirely, but their capacity depends on outdoor air temperature: the hotter the day, the harder they work and the more electricity their fans draw. Immersion helps here, because the fluid can run warmer than the air in a conventional data hall, which widens the gap between fluid and outdoor air and makes dry rejection more practical. How much it helps is a question of engineering data Infinium has not published.

    This is why the density figure and the water claim are linked. Packing a megawatt into 250 square feet concentrates the heat-rejection burden, and the outdoor equipment, its size, noise, power draw and hot-day rating, becomes the component that determines whether the megawatt figure holds in July in Sacramento or Phoenix. Site developers in water-stressed regions, utilities sizing grid connections, and buyers comparing total energy costs are the people for whom that answer matters most.

    Water Is the Pressure Point, Energy Is the Trade-Off

    Positioning around zero water use is commercially astute. Data center water consumption has drawn scrutiny in drought-prone areas, and a cooling approach that removes water from the conversation can ease permitting and community relations. That value is real even before any efficiency numbers are considered.

    The efficiency claim as reported, that immersion cools servers more efficiently than air conditioning, is a comparison with air cooling, a fairly low bar for liquid systems. The more relevant comparison for AI-scale sites is against water-assisted cooling, where operators trade water for lower electricity use. The industry-standard way to express that trade is power usage effectiveness, or PUE, the ratio of total facility power to computing power, alongside water usage effectiveness. Neither figure accompanied the announcement, so the claim that Vector ONE is both waterless and efficient remains to be demonstrated.

    An Edge Product From an Unexpected Supplier

    Infinium’s core business is electrofuels, synthetic fuels made from renewable electricity, and the company has recently landed an airline fuel deal and begun work on what it calls the world’s largest electrofuel plant. A cooling product is a notable step sideways, though both lines of business sit at the intersection of energy and heavy industrial engineering.

    The EdgeSites and Infinium Edge branding, and the one-megawatt unit size, point toward modular and edge deployments rather than the hundred-megawatt campuses hyperscalers build. That is a sensible niche: edge sites are often in places where water hookups, space and cooling infrastructure are hardest to come by, and a self-contained unit that arrives ready to run fits those constraints. It also means Vector ONE competes with established immersion and modular data center vendors, where track record, server-maker support and service networks weigh heavily in purchasing decisions.

    Background

    Infinium is a Sacramento-based clean-fuel company that develops electrofuels, synthetic fuels produced with renewable electricity. It has announced an airline fuel supply deal and started construction on what it describes as the world’s largest electrofuel plant. The EdgeSites Vector ONE, marketed under its Infinium Edge name, marks its move into data center cooling.

    Immersion cooling is an established technique that has moved from niche uses toward mainstream interest as AI hardware pushes power density beyond what air cooling handles comfortably. At the same time, data center water consumption has become a siting and permitting issue in water-stressed regions, increasing demand for cooling approaches that avoid evaporative water use.

    Sources

    Source: Infinium unveils self-contained data center cooling system that uses no water (Sacramento Business Journal, July 27, 2026), reporting on Infinium’s EdgeSites Vector ONE waterless immersion cooling system.

  • Submer’s €1bn Flix Bet: An AI Cooling Firm Sees the Value in Land and Power

    Submer’s €1bn Flix Bet: An AI Cooling Firm Sees the Value in Land and Power

    TL;DR · 30-second read

    The Short Version

    A Barcelona company best known for keeping computers cool is spending about €1 billion to build and run its own huge computer warehouse for artificial intelligence.

    Submer plans to put it on the grounds of an old chemical factory in the Spanish town of Flix, which stopped operating in 2023. Catalonia’s regional president turned out for the announcement.

    What makes it interesting: a company that used to sell equipment to building owners now wants to be the owner. It has not yet said how big the site will be, when it opens, or who will use it.

    Submer, the Barcelona-based company that built its name in immersion cooling, plans a €1 billion ($1.14 billion) AI data center on the site of the former Ercros chemical plant in Flix, Catalonia, Data Center Dynamics reported. The facility will be built in two phases and operated by Rubix Data Centers, the AI data center division Submer launched in June, which aims to lease it to a single tenant running AI workloads.

    The project was unveiled on Saturday, July 11, at an event attended by Salvador Illa, president of the government of Catalonia, and Miquel Sàmper, the regional minister of business and labor. Submer has not disclosed the facility’s planned capacity or construction timeline; renders appear to show four data halls arranged around a central building.

    Executive Summary

    The headline number is €1 billion, but the more consequential fact is who is spending it. Submer’s business has been supplying cooling systems to other people’s data centers. With Flix, it becomes a developer and operator in its own right, following last year’s launch of the InferX AI cloud platform and June’s launch of Rubix Data Centers.

    Submer CEO Patrick Smets framed the move as a deliberate climb up the value chain: “we will expand across the full stack, from land and power to cloud and Edge.” Rubix, led by former Stack executive John Eland, leads its pitch not with cooling technology but with a claim of 8GW of power available across vacant sites in the Americas, EMEA and APAC. That ordering signals where the company believes durable value in AI infrastructure now sits.

    What the announcement does not yet establish is the project’s scale, power supply, financing or customer. Until those are disclosed, Flix is best read as a statement of strategy and site selection rather than a funded, contracted build.

    From Selling Cooling to Owning the Building

    Submer’s trajectory over roughly a year tells the story: an immersion cooling specialist (immersion cooling submerges servers in a non-conductive liquid to carry heat away more efficiently than air) launched an AI cloud platform, InferX, then a data center division, Rubix, and now a €1 billion campus. Each step moves the company closer to the end customer and further from being a component supplier.

    The economic logic is straightforward. An equipment vendor is typically paid once per deployment, and its fortunes depend on how many facilities its customers build. An operator that leases a facility earns recurring rent for the life of the lease and controls the asset that everything else depends on: the site, the building and its power supply. Smets’ own phrasing, “from land and power to cloud and Edge,” puts land and power first. Eland made the same point from the operator’s side: “We intend to operate the facility we are building here, so we are not simply passing through Flix.”

    That is the substance behind reading Flix as a bet on land and power rather than on cooling hardware. The company has not said whether Submer’s own immersion systems will be deployed at Flix, which underlines the point: the announcement is about owning capacity, not showcasing a product.

    Why Power Is the Asset Rubix Leads With

    For AI data centers, the scarce input is increasingly not buildings or servers but a site with a large, deliverable grid connection. That is why Rubix’s headline claim is 8GW of available power across vacant sites, a figure measured in gigawatts, or thousands of megawatts. Framing a data center business around power first reflects how the market now prices development opportunities.

    Former heavy-industrial sites such as the Ercros plant are attractive candidates in principle, because industrial users often required substantial electrical infrastructure and the land is already zoned for industrial use. Ercros also operates a solar farm on the site today. But Submer has not said what grid capacity is available at Flix, whether it is already connected, or how the solar installation fits into the project’s power plans. Those details will determine how quickly and how large Flix can realistically become.

    The 8GW figure deserves the same even-handed reading. It is a claim about power available across vacant sites, and Rubix has not broken it down by location, by grid status or by how much of it is contractually secured versus identified. As a signal of ambition it is clear; as a measure of deliverable capacity it is not yet substantiated.

    The Single-Tenant Model Cuts Both Ways

    Rubix aims to lease Flix to a single tenant for AI workloads. This build-to-suit approach is common for large AI campuses: one creditworthy customer on a long lease can anchor the financing for a very large build, and two-phase construction lets capital be deployed in step with demand.

    The flip side is concentration. Until a tenant signs, the €1 billion figure describes an intended investment rather than a committed one, and the facility’s design, timing and financing will likely hinge on that single counterparty. Without a disclosed capacity, it is also impossible to judge whether €1 billion is a large or modest sum per megawatt relative to comparable AI builds.

    A Supplier Becoming a Peer, With Political Backing

    Moving into operations can create tension with existing customers: data center operators that buy Submer cooling may now find the same company bidding for AI tenants. How Submer manages that overlap between its cooling business and Rubix will be worth watching.

    On the other side of the ledger, the project arrives with visible public support. The presence of Catalonia’s president and its business minister at the launch, and Submer’s framing of the project as part of the “reindustrialization of Flix,” suggest the regional government sees AI infrastructure as a use for idled industrial land. That backing can matter for permitting and grid access, though no specific commitments from the administration were announced.

    Background

    Submer, based in Barcelona, established itself as a specialist in immersion cooling, a technique that submerges servers in a non-conductive fluid to remove heat more efficiently than traditional air cooling, an approach that has gained attention as AI chips grow denser and hotter. Over the past year the company has expanded beyond cooling, launching the InferX AI cloud platform and, in June 2026, Rubix Data Centers, a division that develops and operates AI data centers and is headed by John Eland, formerly of data center operator Stack.

    The Flix site was home to a chemical plant run by Ercros until industrial operations ceased in January 2023. Ercros now operates a solar farm on the site. Redeveloping former industrial land for data centers has become a recurring theme as developers look for sites with industrial zoning and access to power.

    Sources

    Source: Submer plans €1bn data center at former chemical plant in Catalonia (Data Center Dynamics) — Submer’s Rubix division will build and operate a two-phase AI data center on the former Ercros site in Flix.

  • Why Liquid Cooling Is Non-Negotiable for High-Density AI Factories

    Why Liquid Cooling Is Non-Negotiable for High-Density AI Factories

    Data Center Dynamics published an analysis on 25 June 2026 contrasting the cooling demands of AI factories — facilities purpose-built for dense GPU training and inference clusters — with those of conventional cloud data centers, arguing that liquid cooling is now essential for high-density AI workloads rather than an optional upgrade.

    The piece lands amid an industry-wide retooling: operators worldwide are redesigning halls, mechanical plants, and supply chains around direct-to-chip and other liquid cooling approaches as accelerated computing outgrows the air-cooled designs that served the cloud era.

    Executive Summary

    The core claim is straightforward: the data center designs that carried the cloud computing era are hitting a physical ceiling. Conventional cloud halls were engineered around air cooling — moving chilled air through racks drawing power in the single-digit-to-low-double-digit kilowatt range. AI training clusters concentrate far more power in each rack, because modern GPU systems pack accelerators tightly together to keep them on fast, short interconnects. At those densities, air simply cannot carry heat away fast enough, and liquid — which is far denser and holds vastly more heat per unit volume than air — becomes the only practical medium.

    Why it matters: cooling is no longer a back-of-house mechanical detail but a gating factor for who can host AI workloads at all. Operators with liquid-ready facilities can court the highest-value tenants; operators with legacy air-cooled halls face expensive retrofits or a narrowing addressable market. For enterprises buying AI capacity, a provider’s cooling architecture is now a proxy for whether it can actually deliver current-generation GPU infrastructure.

    The analysis frames this as a structural divide — ‘AI factory’ versus ‘cloud hall’ — rather than a spectrum, which is a useful lens even if real-world facilities often blend both.

    The Physics Sets the Deadline, Not the Marketing

    Air cooling works by blowing large volumes of conditioned air through servers, and it has a well-understood practical ceiling: as rack power climbs, the airflow, fan energy, and temperature gradients required become unmanageable. Liquid cooling — most commonly direct-to-chip cold plates, where coolant flows across a metal plate bonded to the processor, or immersion, where hardware is submerged in a dielectric (electrically non-conductive) fluid — removes heat at the source with far greater efficiency. This is not a vendor preference; it is thermodynamics. Water-based coolants can absorb on the order of thousands of times more heat per unit volume than air, which is why every leading accelerated-computing platform roadmap now assumes liquid at the high end.

    The important nuance is that the ceiling is not a single number. Well-engineered air systems with hot-aisle containment can stretch surprisingly far, and many inference and enterprise workloads will remain comfortably air-coolable for years. The ‘non-negotiable’ framing applies specifically to dense training clusters, where chips must sit physically close together for interconnect performance. Density is a networking decision as much as a thermal one — and that is precisely why it cannot be relaxed just to make cooling easier.

    Economics: Liquid Costs More Up Front and Less to Run

    Liquid cooling shifts spending from operations to capital. Cold plates, coolant distribution units, manifolds, leak detection, and plumbing add up-front cost and engineering complexity that air systems avoid. In exchange, operators typically get lower fan energy, better power usage effectiveness (PUE — the ratio of total facility power to IT power, where closer to 1.0 is better), and the ability to run warmer coolant loops that reduce or eliminate energy-hungry chillers. Heat captured in liquid at useful temperatures is also far easier to reuse — for district heating or industrial processes — than diffuse warm air.

    The strategic consequence is that cooling architecture now shapes site selection and facility economics together. A liquid-cooled AI factory can put more revenue-generating compute on the same power envelope, which matters enormously when grid connections — not land or capital — are the scarcest input in the industry. That said, buyers should treat sweeping efficiency claims with care: realized PUE depends on climate, design discipline, and utilization, and figures quoted for flagship builds do not automatically transfer to retrofits.

    Winners, Losers, and the Retrofit Question

    The clearest winners are operators and builders that committed early to liquid-ready designs — reinforced floors for heavier racks, space for coolant distribution, higher-capacity power delivery — along with the supply chain behind them: cold-plate and CDU manufacturers, fluid suppliers, and mechanical contractors with liquid experience. Chipmakers benefit too, since liquid cooling removes a constraint on how much power their next generations can draw.

    The harder story is the installed base. Thousands of existing air-cooled halls cannot be casually converted: adding liquid means new piping, floor loading analysis, leak-management protocols, and often a rethink of the entire mechanical plant. Some facilities will be retrofitted profitably, some will serve the still-large market for air-coolable workloads, and some will be stranded relative to AI demand. For colocation providers, the honest question customers should ask is not ‘do you support liquid cooling?’ but ‘how many megawatts of it can you deliver, at what density, and by when?’

    Operational Risk: New Skills, New Failure Modes

    Bringing liquid into the white space introduces failure modes the air-cooled era rarely faced: leaks near live electronics, coolant chemistry maintenance, and the coordination of facility water loops with IT equipment loops. None of these are exotic — mainframes were water-cooled decades ago, and modern systems are engineered with negative-pressure loops and leak detection — but they demand skills that many data center operations teams are still building. Expect certification programs, standardized quick-disconnect fittings, and reference designs to matter as much as raw technology in determining who executes this transition smoothly. The industry’s real constraint may be trained people, not parts.

    Background

    Data center cooling has followed computing density for decades: water-cooled mainframes gave way to air-cooled commodity servers in the client-server and cloud eras, when racks drawing modest power made air the cheap, simple choice. The generative AI boom reversed the trend — modern accelerator systems concentrate unprecedented power in single racks, and leading GPU platform roadmaps now assume liquid cooling at the high end, pulling the entire industry’s mechanical design along with them.

    Data Center Dynamics, the publication behind this analysis, is a long-established trade outlet covering data center design and operations. Its framing of ‘AI factories’ versus conventional cloud facilities echoes terminology popularized by the accelerated-computing industry to describe purpose-built AI infrastructure — a sign of how thoroughly that vocabulary has permeated the sector.

    Source: AI factory cooling vs cloud data centers: Why liquid cooling is essential for high-density AI workloads — a Data Center Dynamics analysis, published 25 June 2026, on why liquid cooling has become a baseline requirement for dense AI infrastructure.

  • Dow’s Liquid Cooling Support Network Signals a Maturing AI Cooling Supply Chain

    Dow’s Liquid Cooling Support Network Signals a Maturing AI Cooling Supply Chain

    Dow, one of the world’s largest materials science companies, has launched a liquid cooling support network for data centres, according to a report published by Data Centre Magazine on 18 May 2026. The reported launch positions Dow — a supplier of silicones, fluids, and specialty chemistries — as an organized participant in the fast-growing market for cooling the dense computing racks that power artificial intelligence.

    Executive Summary

    The announcement, as reported, is simple in outline: Dow is standing up a formal support network around liquid cooling for data centres. Support or partner networks in the materials world typically bundle products with validation, compatibility guidance, and access to a vetted ecosystem of collaborators — though the source report does not detail which of these Dow’s network includes.

    Why it matters is larger than the announcement itself. Liquid cooling — circulating fluid to chips or immersing hardware in it, instead of relying on air — has moved from niche to necessity as AI servers pack more power into each rack than air can practically remove. When a company of Dow’s scale builds formal structure around that market, it signals that liquid cooling is graduating from a collection of point products into an industrial supply chain, with the materials layer — coolants, silicones, seals, thermal interfaces — treated as critical infrastructure rather than a commodity input.

    Why a Chemicals Giant Is Organizing Around Server Cooling

    Air cooling has a physics problem. Modern AI accelerators concentrate so much power in each rack that moving enough air through them becomes impractical, which is why the industry has shifted toward direct-to-chip liquid cooling (piping coolant across a cold plate mounted on the processor) and, in some deployments, immersion cooling (submerging entire servers in a non-conductive fluid). Every one of those approaches depends on chemistry: the coolant itself, plus the hoses, seals, gaskets, and thermal interface materials that keep fluid where it belongs for years at a time.

    That is Dow’s home turf. Materials suppliers have historically sold into this market indirectly, through the vendors that build cooling hardware. A formal support network — if it follows the usual shape of such programs — moves the materials maker closer to the operators and equipment builders who actually deploy the technology, which matters because coolant compatibility failures (degraded tubing, fouled cold plates, additive breakdown) are among liquid cooling’s most feared operational risks.

    Formalizing the Supply Chain Is the Real Story

    The editorial significance here is less any single product and more the institutional signal. Liquid cooling’s early years were characterized by fragmented suppliers, proprietary fluids, and limited interoperability guidance. Buyers — hyperscale cloud providers, colocation operators, enterprises — have been pushing for validated, multi-vendor supply chains before committing facilities designed to run for decades. Ecosystem programs are how industrial suppliers answer that demand: they convert one-off product sales into standing relationships with documented compatibility.

    Dow is not moving into an empty field. Fluid and chemistry players including Chemours, Shell, and Castrol have courted the data centre cooling market, while 3M’s announced exit from PFAS manufacturing by the end of 2025 removed a prominent supplier of certain engineered fluids and sharpened questions about fluid chemistry choices across the industry. Against that backdrop, a structured support offering from a major materials company is a bid for trust as much as for revenue: operators want assurance that the fluid in their loops will be supported, supplied, and compliant for the life of the facility.

    What Buyers Should Watch For

    For data centre operators and cooling equipment makers, the practical questions are concrete. Does the network provide compatibility validation across pumps, cold plates, and piping from multiple hardware vendors? Does it address regulatory exposure — notably the tightening scrutiny of per- and polyfluoroalkyl substances (PFAS) that affects some classes of engineered cooling fluids? And does it shorten the qualification cycle, which today can add months to a liquid cooling deployment?

    The source report does not answer these questions, and it would be premature to credit the network with capabilities it has not publicly detailed. What can be said fairly is that the direction of travel — materials incumbents building formal, supported ecosystems around data centre liquid cooling — is exactly what a maturing market looks like, and buyers benefit when more credible suppliers compete to underwrite reliability.

    Background

    Dow traces its roots to 1897 and today ranks among the world’s largest materials science companies, supplying silicones, fluids, and specialty chemistries across dozens of industries. Its materials have long appeared inside electronics and thermal management applications, though typically sold through intermediaries rather than under a data centre-branded program.

    The data centre cooling market has been reshaped by the AI build-out: rack power densities have climbed beyond what air cooling comfortably handles, pushing direct-to-chip and immersion cooling from experimental to mainstream. That shift has drawn fluid and chemistry suppliers — and their partner ecosystems — into a market once dominated by mechanical and HVAC vendors.

    Source: Dow Launches Liquid Cooling Support Network for Data Centres — Data Centre Magazine report, 18 May 2026, on Dow’s launch of a liquid cooling support network for data centres.

  • Keppel and Shell to Pilot Immersion Cooling at a Singapore Data Center

    Keppel and Shell to Pilot Immersion Cooling at a Singapore Data Center

    Keppel and Shell will launch an immersion cooling pilot at a data center in Singapore, according to an April 2026 report by Data Center Dynamics. Immersion cooling submerges servers in a non-conductive (dielectric) liquid instead of blowing chilled air across them, and the pilot pairs one of Asia’s most established data-center operators with an energy major that has been developing cooling fluids as a specialty product line.

    Executive Summary

    The announcement is short on specifics — no facility name, timeline, capacity, or fluid specification was reported — but the pairing itself is the story. Keppel is a longtime data-center developer and operator headquartered in Singapore, and Shell is one of several oil-and-gas majors that have built immersion cooling fluids into their lubricants and specialty-chemicals portfolios. A pilot puts that product in a live operator environment, which is the step fluid vendors need before operators will commit production workloads.

    It matters because the industry’s cooling assumptions are shifting. AI accelerators have pushed per-rack power draws well beyond what conventional air cooling handles economically, and Singapore — a tropical, land- and power-constrained market that conditions new data-center capacity on efficiency — is one of the most demanding places to prove out an alternative. If immersion works commercially anywhere, a Singapore pilot is a credible proving ground.

    Why Air Cooling Is Running Out of Headroom

    For decades, data centers were cooled the same basic way: chill air, push it through server racks, and exhaust the heat. That model works well at the rack densities of the cloud era — roughly 5 to 15 kilowatts per rack — but AI training and inference hardware has driven densities several times higher, and air simply cannot carry heat away fast enough at those levels without extreme airflow and energy cost. Liquid conducts heat far more effectively than air, which is why the industry is moving toward direct-to-chip liquid cooling and, at the more radical end, full immersion.

    Immersion cooling takes the concept to its logical conclusion: the entire server is submerged in a bath of dielectric fluid — a liquid engineered not to conduct electricity — so every component sheds heat directly into the liquid. Proponents cite lower cooling energy, reduced fan power, and quieter, denser halls. The trade-offs are real too: servicing a submerged server is messier, hardware warranties and supply chains are built around air, and the fluid itself is a new consumable with its own cost and lifecycle. A pilot is precisely how an operator quantifies those trade-offs on its own workloads rather than a vendor’s test bench.

    An Oil Major’s Route Into the Data-Center Thermal Stack

    Shell’s participation reflects a broader pattern: oil-and-gas companies repositioning parts of their refining and lubricants expertise toward digital infrastructure. Immersion fluids are, at bottom, specialty chemistry — the same competency that produces engine oils and transformer fluids — and Shell has marketed immersion cooling fluids for several years as part of its lubricants business. For an energy major, data-center cooling offers a growth market tied to AI demand at a time when traditional fuel demand faces long-term uncertainty.

    For operators, the entry of large chemical producers addresses a practical adoption barrier: fluid supply at scale, with the quality control, safety documentation, and global logistics that hyperscale procurement requires. A niche fluid from a small vendor is a harder bet for a facility designed to run twenty years. That said, the release as reported does not disclose the commercial structure here — whether Shell is supplying fluid, co-developing the system, or simply lending its name to a joint trial — and those are very different depths of commitment.

    Singapore Is a Deliberately Hard Test Bed

    Singapore is one of the world’s most important data-center hubs and also one of its most constrained. The city-state paused new data-center approvals for several years over energy concerns, and when it resumed allocations it tied new capacity to stringent efficiency standards. Add a tropical climate — where conventional cooling works hardest and free-air economization is largely unavailable — and Singapore becomes a stress test: cooling technology that pencils out there has cleared a high bar.

    That context cuts both ways for this pilot. It gives the results credibility if they are published, and it aligns with Keppel’s interest in squeezing more compute from a fixed power and land envelope. But it also means the pilot’s findings may flatter immersion relative to temperate markets, where cheap outside-air cooling narrows the efficiency gap. Operators elsewhere should read any results with their own climate and power costs in mind.

    What a Pilot Proves — and What It Doesn’t

    A pilot answers engineering questions: real-world efficiency, serviceability, fluid behavior over time, and how existing operational teams adapt. It does not answer the commercial questions that determine adoption — total cost of ownership at fleet scale, hardware-vendor warranty support, insurance treatment, and whether tenants will accept immersed infrastructure. The history of data-center cooling includes many well-run pilots that never converted to production deployments because the economics or the supply chain wasn’t ready.

    The measured read is that this announcement signals direction, not destination. Keppel gains hands-on data for future builds in a market that rewards efficiency; Shell gains an operator reference in a marquee hub. Whether it becomes more than that depends on results neither company has yet reported.

    Background

    Keppel has been building and operating data centers for over two decades and is one of Asia’s most established players in the sector, with Singapore as its home market. Singapore itself paused new data-center approvals for several years over energy concerns before resuming allocations under strict efficiency conditions, making cooling performance a gating factor for growth there. Shell, like several energy majors, has extended its lubricants and specialty-chemicals expertise into immersion cooling fluids as demand for high-density computing rises — part of a broader repositioning of oil-and-gas capabilities toward digital infrastructure.

    Source: Keppel and Shell to launch immersion cooling pilot at Singapore data center — Data Center Dynamics report, April 25, 2026, on a planned immersion cooling trial at a Keppel data center in Singapore.

  • AI Turns Cooling Into the Defining Constraint of Data Center Design

    AI Turns Cooling Into the Defining Constraint of Data Center Design

    Data Center Knowledge reported on April 23, 2026 that cooling has moved to the forefront of data center design challenges, driven by the power density of AI computing. The trade publication’s framing captures a shift the industry has been living through: thermal management, once a back-of-house engineering detail, now shapes where facilities are built, how they are architected, and how quickly they can serve AI demand.

    Executive Summary

    The report’s core argument is structural rather than incremental: artificial intelligence has changed the physics of the data hall. Traditional enterprise servers could be cooled with chilled air pushed through raised floors and contained aisles. AI training and inference clusters concentrate far more electrical power — and therefore far more heat — into each rack than air can economically remove, forcing designers to treat heat rejection as a first-order constraint alongside power availability and land.

    Why it matters: when cooling becomes the binding constraint, it stops being a line item and starts being a strategy. Choices between air, direct-to-chip liquid cooling (circulating coolant through cold plates mounted on processors), rear-door heat exchangers, and immersion systems now determine a facility’s compatibility with next-generation chips, its water and energy footprint, and its retrofit economics. Operators, colocation providers, and their customers are all repricing those decisions in real time.

    When Air Runs Out of Headroom

    Air cooling served the industry for decades because server heat loads were modest and evenly distributed. AI accelerators break that model: they pack extraordinary computation — and heat — into small silicon footprints, and operators deploy them in dense clusters to keep chip-to-chip communication fast. Past a certain density, moving enough air through a rack becomes physically impractical and economically punishing, because fan energy and airflow engineering costs rise steeply while cooling effectiveness plateaus.

    Liquid is the natural successor because water and engineered coolants carry heat far more efficiently than air. But switching thermal mediums is not a component swap. It changes piping, floor loading, leak detection, maintenance procedures, and the skills a facilities team needs. That is why the trade press now describes cooling as a design challenge rather than an operations task: the decision has to be made before concrete is poured, and it constrains everything after.

    The Retrofit Divide: Winners and Losers

    The shift creates a two-tier market. New builds designed liquid-ready from day one can court the highest-value AI tenants. Older facilities — the majority of the world’s installed base — face a harder calculus: retrofitting liquid cooling into a live building is disruptive and expensive, but declining to retrofit risks ceding AI workloads entirely and competing for a shrinking pool of conventional enterprise demand.

    The beneficiaries are visible across the supply chain: cooling equipment manufacturers, mechanical engineering firms, and colocation providers with modern, high-density-capable inventory. The squeezed parties are operators of legacy stock and, potentially, customers who signed long leases in facilities that cannot follow the density curve. For buyers of data center capacity, a facility’s thermal architecture is becoming as important a diligence question as its power contract.

    Cooling as a Sustainability and Siting Question

    Cooling choices also carry environmental and community consequences. Evaporative systems trade energy efficiency for water consumption — a sensitive issue in drought-prone regions where many data center clusters sit. Closed-loop liquid systems can reduce water draw and, in some designs, make waste heat recoverable for district heating or industrial reuse. As municipalities scrutinize data center growth, thermal design is increasingly part of the permitting and public-acceptance conversation, not just the engineering one.

    That elevates cooling from a cost center to a siting variable. A design that minimizes water use or enables heat reuse can be the difference between a fast permit and a contested one — a dynamic worth watching as AI capacity expansion collides with local resource politics.

    Background

    For most of the industry’s history, data center design was governed by power and space, with cooling treated as a solved problem: chilled air, raised floors, and hot-aisle containment handled the modest, evenly distributed heat of enterprise servers. The AI buildout that accelerated after 2022 broke that assumption. Training and serving large models requires dense clusters of power-hungry accelerator chips, and each hardware generation has pushed per-rack heat loads further beyond what air-based systems were designed to handle.

    The result has been a rapid industry pivot toward liquid-based thermal architectures — direct-to-chip cold plates, rear-door heat exchangers, and immersion systems — and a re-sorting of the market between facilities that can host high-density AI workloads and those that cannot. Trade coverage like this Data Center Knowledge report reflects a consensus that has hardened across operators, chipmakers, and engineers: cooling is no longer downstream of design; it is design.

    Source: AI Pushes Cooling to the Forefront of Data Center Design Challenges — Data Center Knowledge’s April 23, 2026 report on how AI rack densities are making thermal management a primary data center design constraint.