Cooling vendor Wafr Technologies has raised $100 million, according to a report carried by Data Center Dynamics on July 7, 2026. The publication characterized the raise as a report rather than a company announcement, and the item available to us does not name the investors, the round structure, or the intended use of proceeds.
Executive Summary
According to the Data Center Dynamics item, Wafr Technologies — identified simply as a cooling vendor — has reportedly secured $100 million in new funding. That is the extent of what the source substantiates: a company name, a sector, a dollar figure, and the qualifier “report,” which signals the news has not been confirmed in detail by the company itself.
Even in that skeletal form, the story matters because of what it represents. Cooling — the unglamorous business of moving heat away from computer chips — has become one of the tightest constraints on data center construction in the AI era. A nine-figure round for a cooling specialist, if confirmed, would be another data point in a clear pattern: capital that once flowed almost exclusively to chips, land, and power is now chasing thermal management, because without it the rest of the AI buildout stalls.
Why Heat Became the Industry’s Chokepoint
For most of the data center industry’s history, cooling was a solved problem: blow chilled air across servers, exhaust the hot air, repeat. That model works up to roughly the power density of a traditional enterprise rack. AI training hardware broke the equation. Modern accelerated-computing racks draw many times what air can economically remove, which is why the industry is shifting to liquid cooling — circulating fluid directly to cold plates on the chips, or immersing hardware in dielectric fluid — to carry heat away far more efficiently than air ever could.
That transition is not optional for AI-class facilities, and it is happening faster than the supply chain matured. Cold plates, coolant distribution units, rear-door heat exchangers, and the engineering talent to deploy them have all been in tight supply. When a component becomes the binding constraint on a trillion-dollar buildout, capital follows. A reported $100 million round for a cooling vendor fits that logic precisely.
What a Nine-Figure Round Signals About the Market
Cooling has historically been the domain of large industrial incumbents — the Vertivs and Schneider Electrics of the world — for whom thermal management is one product line among many. Venture-scale money flowing to independent cooling specialists suggests investors believe the liquid-cooling transition is big enough, and moving fast enough, to support new entrants rather than simply enlarging incumbents’ order books.
It also says something about where returns are perceived to be. Building data centers is capital-intensive and increasingly commoditized; supplying the critical components that gate construction can carry better margins and faster growth. Investors who missed the GPU wave or the land-and-power wave may see thermal management as the remaining underpriced layer of the AI infrastructure stack. Whether that thesis pays off depends on execution questions this report cannot answer — but the direction of the money is itself informative.
Winners, Losers, and the Scaling Test Ahead
If the raise is confirmed, the most immediate beneficiaries are data center operators and their customers: more capitalized suppliers mean more manufacturing capacity, shorter lead times, and more competitive pricing in a segment where demand has outrun supply. Chipmakers benefit indirectly, since every rack that can be cooled is a rack that can be sold.
The harder question is whether a funded challenger can convert capital into share. Cooling is a trust business — operators are conservative about anything that puts liquid near multi-million-dollar hardware — and incumbents hold deep service networks and long-standing customer relationships. History in this industry suggests that well-funded specialists either scale into meaningful suppliers, get acquired by incumbents seeking their technology, or burn capital competing on price. A $100 million war chest buys time to find out which path applies; it does not guarantee the answer.
Reading a Report, Not a Press Release
It is worth being precise about the evidentiary status here. The source is a trade-press item flagged as a report — not a company announcement, not a regulatory filing. The figure could ultimately prove different in size, structure (equity versus debt), or timing. Trade reporting on private raises is often directionally right and precisely wrong. Until Wafr Technologies or its investors confirm the details, the responsible reading is: a credible industry publication believes a cooling vendor has attracted roughly $100 million, and that belief is consistent with everything else happening in the thermal-management market.
Background
For decades, data center cooling meant air: chillers, raised floors, and hot-aisle containment, handled largely by big industrial suppliers as one product line among many. The AI era upended that. Racks built around modern accelerators draw several times the power of traditional enterprise racks, pushing the industry toward direct-to-chip liquid cooling and immersion systems that can remove heat air cannot. That transition turned a mature, sleepy segment into one of the most supply-constrained corners of the infrastructure market, and capital has followed — into incumbents’ expansion and, increasingly, into independent specialists.
Wafr Technologies enters the public record here with little published history: the report available to us identifies it only as a cooling vendor. That thinness is itself common in this cycle, where private thermal-management companies often surface in trade press via funding reports before making detailed public disclosures.
China has brought online what is being described as the world’s first commercial underwater data center, according to a report published July 4, 2026 by the Spanish outlet OkDiario. The facility submerges sealed server modules in the ocean and uses the surrounding seawater as its cooling medium, an approach the report says sharply reduces the energy the facility consumes.
The report frames the launch as a template other coastal regions could adopt, naming Cartagena, Spain as the kind of Mediterranean port city where the model might be replicated. It does not disclose the operator, the facility’s capacity, or its precise location.
Executive Summary
The announcement matters because it moves underwater data centers from experiment to product. Submerging servers has been tested before — most famously by Microsoft — but a commercial deployment means paying customers are expected to run real workloads on seabed infrastructure, and that changes the questions from “does it work?” to “does it pencil out?”
The core appeal is cooling. Keeping servers from overheating is one of the largest energy costs in any data center, and the deep ocean offers a vast, stable heat sink at no mechanical-chilling cost. If seawater cooling delivers the efficiency the concept promises at commercial scale, it would arrive at a moment when AI-driven demand has made power and cooling the industry’s tightest constraints.
That said, the source report is brief and light on specifics. It attributes no capacity figures, energy metrics, customer names, or operator details. The launch is a genuine milestone in cooling infrastructure if the commercial framing holds — but the evidence available in this report is a claim of a first, not a documented performance record.
Why Put Servers on the Seabed?
Data centers spend an enormous share of their electricity not on computing but on removing the heat that computing generates. The industry measures this with PUE — power usage effectiveness, the ratio of total facility power to the power that actually reaches IT equipment. Conventional air-cooled facilities need chillers, fans, and often large volumes of water to hold safe temperatures, and in hot climates that overhead climbs steeply.
The ocean solves the problem passively. Below the surface, water temperature is low and remarkably stable year-round, and water conducts heat far better than air. A sealed capsule on the seabed can reject heat directly into an effectively unlimited sink, eliminating most mechanical cooling. Subsea deployment also removes evaporative water consumption — a growing point of friction between data centers and the communities that host them — and seabed real estate near dense coastal cities is not competing with housing or industry the way urban land is.
From Microsoft’s Experiment to Chinese Commercialization
The concept is not new; the commercial claim is. Microsoft’s Project Natick sank a sealed server vessel off Scotland’s Orkney Islands from 2018 to 2020 and reported that the submerged servers failed at a fraction of the rate of an equivalent land-based control group — likely because the nitrogen-filled, human-free capsule eliminated oxygen corrosion, humidity swings, and accidental knocks. Microsoft judged the experiment a technical success but never turned it into a product. China, meanwhile, has been running underwater data center pilots off its own coast for several years, so a progression from pilot to commercial service there is consistent with the trajectory — even though this report does not name the company involved.
If the commercial characterization is accurate, China would be first to market with a technology a US hyperscaler proved and shelved. That is a familiar pattern in infrastructure: the economics that don’t fit one company’s portfolio can fit another market’s constraints, particularly where coastal land, grid capacity, and water for cooling are all scarce at once.
The Hard Economics of Subsea Capacity
The obstacles are as real as the appeal. A submerged module cannot be serviced by a technician; a failed component stays failed until the entire vessel is raised, which pushes operators toward redundant hardware and infrequent, expensive retrieval cycles. Marine engineering, corrosion-resistant housings, subsea power and fiber connections, and specialized deployment vessels all add capital cost that the cooling savings must repay. Insurance, uptime guarantees, and repair logistics for seabed assets are largely uncharted territory for enterprise customers used to walking their auditors through a facility.
Environmental questions also need honest accounting. Rejecting heat into the ocean is thermodynamically unavoidable here, and while small-scale trials such as Natick reported minimal localized warming, the effect of dense clusters of commercial modules on marine ecosystems is site-specific and largely unstudied. Coastal permitting regimes — fisheries, shipping lanes, protected habitats — will shape where this model can actually go, and the report offers no detail on how the Chinese deployment cleared those hurdles.
Could Cartagena Be Next?
The report’s suggestion that coastal cities like Cartagena could follow is speculation, not an announced project, and it is worth being clear about that distinction. Still, the logic of the shortlist is sound: Mediterranean port cities combine dense populations that want low-latency services, constrained urban land and grids, warm climates that make conventional cooling expensive, and immediate deep water. Those are precisely the conditions under which subsea capacity is most competitive against land-based builds.
For European adoption, the gating factors would be EU environmental review, marine-spatial-planning approvals, and — not least — the geopolitics of importing a Chinese-proven infrastructure model into European digital sovereignty debates. Any operator pursuing it would more likely license the concept or develop it independently than deploy Chinese-operated modules in EU waters.
Background
Underwater data centers trace to Microsoft’s Project Natick, which began with a proof-of-concept in 2015 and culminated in a sealed vessel of several hundred servers operating off Scotland from 2018 to 2020. The retrieved servers had failed at a small fraction of the rate of an identical land-based group, validating the reliability case — but Microsoft ended the program without a commercial product. China picked up the thread with coastal pilot deployments in the years that followed, pursuing subsea capacity as an answer to scarce coastal land, strained grids, and the water consumption of conventional cooling.
The timing is not incidental. By 2026, explosive AI demand had made electricity and cooling the data center industry’s defining bottlenecks worldwide, pushing operators toward liquid cooling, novel sites, and any design that cuts overhead energy. A commercial subsea launch is China staking a claim to one of those frontiers first.
The Wall Street Journal published an investigation on July 3, 2026, reporting that AI data centers consume far more water than most major technology companies publicly acknowledge. The reporting targets the gap between the industry’s sustainability disclosures and the actual water draw of the facilities powering the AI boom — a gap with direct consequences for the communities, utilities, and regulators hosting these sites.
Executive Summary
According to the Journal’s headline finding, the water consumed by AI data centers substantially exceeds the figures most tech giants report. That claim lands at a sensitive moment: hyperscale operators are racing to build AI capacity at unprecedented scale, and many of the fastest-growing markets for that capacity are in water-stressed regions where every megawatt of cooling has a hydrological cost.
The significance is less about any single number and more about trust in the measurement system itself. Data center operators have spent a decade building sustainability reporting frameworks — water usage effectiveness metrics, replenishment pledges, “water positive” targets. An investigation asserting that disclosed figures materially understate real consumption challenges the credibility of that entire apparatus, and will sharpen scrutiny from permitting authorities, investors, and enterprise customers alike. It is worth noting up front that the material available at publication is the Journal’s headline claim; the underlying methodology and company-by-company figures sit behind the investigation itself, so our analysis focuses on how such a gap can exist and what it would mean if borne out.
Why Water Is the AI Boom’s Quiet Constraint
Data centers use water primarily for cooling. Evaporative systems — the most energy-efficient way to reject heat in many climates — work by evaporating water to carry heat out of the building, which means the water is genuinely consumed rather than borrowed and returned. AI workloads intensify this: training and inference clusters pack far more power into each rack than traditional enterprise computing, and every kilowatt of electricity ultimately becomes heat that must go somewhere.
Power availability has dominated the AI infrastructure conversation, but water is the constraint that most directly touches neighbors. A community can rarely see the grid strain a campus causes; it can see reservoir levels, well permits, and municipal supply contracts. That visibility is why water — more than carbon — has become the flashpoint in local data center opposition, and why a disclosure gap, if substantiated, matters commercially and not just reputationally.
How a Disclosure Gap Can Exist Without Anyone Lying
Water accounting has honest ambiguities that reporting can exploit or obscure. “Withdrawal” (water taken in) and “consumption” (water evaporated and lost) are different numbers. On-site cooling water is different from the much larger volumes evaporated at the power plants generating a facility’s electricity — a burden that rarely appears in corporate water figures. Companies may report global averages that dilute stress in specific basins, disclose only company-owned sites while leasing heavily from colocation providers, or treat site-level data as a trade secret in agreements with local utilities.
Each choice can be individually defensible and collectively misleading. If the Journal’s investigation shows real draw far above disclosed figures, the likeliest mechanism is not fabrication but selective scope: what gets counted, where, and at what level of aggregation. That is precisely why the methodology on both sides deserves scrutiny — an investigation comparing utility records of total withdrawal against corporate disclosures of net consumption would find a large gap even where reporting is technically accurate. Neither the companies’ frameworks nor the investigation’s comparisons should be taken on trust without seeing definitions aligned.
Winners, Losers, and the Coming Transparency Squeeze
If disclosure practices tighten — voluntarily or by mandate — the advantage shifts to operators who engineered for water frugality before it was scrutinized: closed-loop liquid cooling, dry coolers, air-side economization in suitable climates, and treated wastewater sourcing. Vendors of direct-to-chip and immersion cooling gain a stronger sales narrative, since liquid cooling at the rack can pair with water-free heat rejection outside. Operators dependent on open evaporative cooling in arid, fast-growing markets face the hardest repricing, because retrofits are costly and permitting timelines are long.
Enterprise buyers and investors are the other lever. Cloud and colocation contracts increasingly carry sustainability reporting clauses, and a credible investigation gives procurement teams grounds to demand site-level water data rather than glossy aggregates. For host communities, the practical effect is likely to be harder-edged development agreements: metered disclosure requirements, drought curtailment provisions, and consumption caps as conditions of approval. The industry can resist that trend or get ahead of it; the second option is cheaper.
Background
Water has trailed energy as the second axis of data center sustainability for over a decade. Major operators publish water metrics alongside “water positive” replenishment pledges — commitments to restore more water to stressed basins than their operations consume. Those frameworks were designed in the era of conventional cloud computing; the AI buildout that accelerated from 2023 onward brought far denser facilities, faster construction, and expansion into hot, dry regions where land and power are cheap but water is contested.
Local friction has grown in step. Communities from the American Southwest to Europe and Latin America have challenged data center water allocations, and operators have responded with a mix of reclaimed-water sourcing, liquid cooling adoption, and — critics argue — selective disclosure. The Journal’s investigation lands squarely on that last point, testing whether the industry’s reported numbers describe the facilities actually being built.
Research publicized June 29, 2026 via Tech Xplore suggests that aquifers — naturally occurring layers of water-bearing rock underground — could serve as ‘thermal batteries’ for data centers, storing heat and cold across seasons. According to the report, the approach may reduce the cooling energy AI data centers consume and cut their water use, two of the industry’s fastest-growing environmental pressure points.
Executive Summary
The announcement is a research finding, not a product launch: scientists propose using aquifer thermal energy storage — pumping water underground to bank cold in one season and withdraw it in another — as a way to offset the enormous cooling loads created by AI computing. The headline claim is twofold: lower cooling energy demand and reduced water consumption compared with conventional approaches such as evaporative cooling, which loses large volumes of water to the atmosphere by design.
Why it matters: cooling is one of the largest non-compute energy costs in a data center, and water use has become a siting and permitting flashpoint in drought-prone regions. AI accelerators run hotter and denser than traditional servers, magnifying both problems. A storage-based approach that shifts cooling work to underground reservoirs — rather than burning electricity on chillers or evaporating potable water in real time — would attack both constraints at once. The open question, which the source headline’s own careful ‘may cut’ phrasing acknowledges, is whether the technique scales from research findings to the round-the-clock, high-density heat loads of production AI facilities.
Why Cooling Is the Quiet Crisis of the AI Buildout
Every watt a server consumes becomes heat that must be removed, and AI hardware has pushed rack power densities far beyond what legacy air-cooling systems were built for. Operators today choose among imperfect options: mechanical chillers, which are reliable but electricity-hungry; evaporative cooling, which trades electricity for significant water consumption; and liquid cooling, which moves heat efficiently at the rack but still needs somewhere to reject it. Cooling efficiency is captured in metrics like PUE (power usage effectiveness — total facility power divided by computing power), and shaving it has direct economic value at AI campus scale.
Water has arguably become the more politically sensitive constraint. Data center water consumption has drawn scrutiny from communities and regulators in water-stressed regions, and several jurisdictions now weigh water impact in permitting decisions. A cooling architecture that credibly reduces both energy and water use addresses the industry’s two most visible externalities simultaneously — which explains why a research result, rather than a commercial deployment, is drawing attention.
How an Aquifer Becomes a Battery
Aquifer thermal energy storage, often abbreviated ATES, is conceptually simple: use paired wells to circulate groundwater, storing thermal energy in the aquifer itself. In winter, cheap ambient cold is banked underground; in summer, that stored cold is withdrawn to absorb data center heat, with the warmed water returned to a separate zone of the aquifer for later use or dissipation. The ‘battery’ framing is apt — the aquifer shifts cooling capacity across time, much as an electrical battery shifts energy from cheap hours to expensive ones.
The underlying technique is not new. ATES has been deployed for decades in district heating and cooling systems, particularly in the Netherlands, where favorable geology and supportive regulation made it routine for buildings. What the new research explores is its application to a much harder customer: data centers, whose heat output is continuous, dense, and growing. Because the water circulates in a closed loop underground rather than evaporating into the air, the approach could sidestep the consumptive water losses that make evaporative cooling controversial.
Who Wins If It Works — and What Stands in the Way
The clearest beneficiaries would be operators in regions with suitable aquifer geology and strong seasonal temperature swings, where winter cold can be banked cheaply. Utilities and grid planners would welcome anything that flattens data center cooling load, since peak cooling demand coincides with summer grid stress. Drilling, geothermal, and groundwater engineering firms would gain a new market adjacent to the booming data center construction sector.
The obstacles are equally concrete. ATES only works where the geology cooperates — the right aquifer depth, permeability, and low natural groundwater flow — which makes it a siting-dependent solution, not a universal one. Groundwater is heavily regulated nearly everywhere, and injecting warmed water underground raises legitimate environmental review questions about thermal plumes and water chemistry. And AI’s heat load is continuous rather than seasonal, so an aquifer system would likely supplement, not replace, conventional cooling. None of these hurdles is disqualifying, but each stands between a promising research finding and a bankable design that a hyperscaler would commit to.
Background
Data center cooling has evolved through waves of pressure: from raised-floor air cooling, to hot/cold aisle containment, to economizers and evaporative systems, and most recently to direct liquid cooling as AI accelerators pushed rack densities beyond what air can handle. Each wave traded among the same three currencies — electricity, water, and capital — and the AI buildout has sharpened all three constraints at once, with water use in particular becoming a community and permitting issue in water-stressed markets.
Aquifer thermal energy storage sits within a broader family of underground thermal techniques, alongside borehole storage and geothermal heat pumps. ATES matured in northern Europe over several decades as a building heating-and-cooling technology; the research reported here represents an attempt to carry that mature concept into the much more demanding environment of AI computing infrastructure.
Microsoft is claiming water positivity across its data center operations, according to a June 27, 2026 report from Data Center Dynamics. Water positivity means an operator replenishes more water to stressed watersheds than its facilities consume — a milestone Microsoft first committed to reaching by 2030 when it announced its water-positive pledge in 2020.
The claim spans one of the world’s largest cloud footprints, and it arrives at a moment when AI-driven capacity growth has put data center water consumption under intense public and regulatory scrutiny. The available report is headline-level, so the scope, accounting method, and verification behind the claim remain to be detailed.
Executive Summary
Microsoft has publicly positioned its data center operations as water positive — consuming less water, net of replenishment projects, than it returns to the watersheds where it operates. If the claim holds up under scrutiny, it would represent the first time a hyperscale cloud operator has asserted that its fleet, as a whole, has crossed that line, and it would land years ahead of the company’s stated 2030 target.
Why it matters: water has become the second front, after power, in the fight over data center siting. Communities from Arizona to the Netherlands have pushed back on facilities that draw millions of gallons for evaporative cooling, and regulators increasingly ask for water commitments alongside grid commitments. A credible water-positive benchmark from the market’s second-largest cloud provider would reset expectations for every operator negotiating a site — including colocation and wholesale providers who compete for the same land, power, and permits.
The operative word is credible. Water positivity is an accounting construct, not a physical description of any single site, and its value depends entirely on scope, measurement, and where the replenishment actually happens. The source reporting available at publication does not yet answer those questions, and they are the right ones to ask of any operator making a similar claim.
What “Water Positive” Actually Means — and What It Doesn’t
Water positivity is a ledger claim: over a defined period, the volume of water an operator restores — through wetland restoration, leak-repair programs, irrigation efficiency projects, aquifer recharge, and similar investments — exceeds the volume its operations consume. Consumption here typically means water evaporated or otherwise not returned to the source, which for data centers is dominated by evaporative cooling, the technique of cooling air or water by letting some of it evaporate, trading water for large electricity savings.
What the construct does not mean is that any individual data center stopped drawing water. A facility in a drought-stressed basin can keep consuming while the corporate ledger balances with a restoration project elsewhere. That is not inherently bad-faith accounting — carbon markets work on a similar logic — but water is far more local than carbon. A gallon replenished in one river basin does nothing for the aquifer under a different one. The strongest version of a water-positive claim is basin-matched: replenishment in the same watersheds where consumption happens, weighted toward the most stressed ones. Whether Microsoft’s claim is basin-matched is exactly the kind of detail the headline-level reporting leaves open, and it is the difference between a milestone and a marketing line.
The Cooling Economics Behind the Claim
Data centers face a three-way trade among water, energy, and capital. Evaporative cooling is cheap and energy-efficient but water-hungry. Closed-loop and air-cooled designs eliminate most on-site water consumption but raise electricity use or capital cost, and in hot climates they can strain the power budget that operators are already fighting to secure. Microsoft has spent several years publicizing designs that move toward zero-water cooling for new builds, alongside efficiency metrics like WUE — water usage effectiveness, the liters of water consumed per kilowatt-hour of IT load.
A fleet-level water-positive result, if achieved early, most plausibly reflects three levers working together: newer builds consuming less per megawatt, replenishment portfolios scaling faster than consumption, and — the uncomfortable variable — how fast AI capacity growth adds consumption to the denominator. The AI buildout cuts both ways here. High-density AI halls increasingly use direct liquid cooling, which circulates coolant in a closed loop and can actually reduce on-site water consumption per unit of compute, but the sheer volume of new capacity can swamp per-unit gains. Any operator’s water math in 2026 is a race between those two curves.
A Benchmark With Teeth — If the Methodology Is Public
The industry consequence of this claim depends less on Microsoft than on procurement. Enterprise cloud buyers and public-sector tenders already ask for carbon disclosures; a hyperscaler asserting water positivity gives sustainability teams a new line item to demand from every provider. Google and Amazon have announced their own 2030-era water goals, so competitive pressure to demonstrate progress — not just pledge it — will rise. Colocation operators, who often lack the balance sheet for large replenishment portfolios, may feel the squeeze most: their water story is largely their cooling design, not an offsetting ledger.
For communities and regulators, the useful move is to treat the claim as an invitation to standardize. Today there is no universally accepted audit standard for water positivity comparable to the frameworks maturing around carbon. Claims are only comparable across operators if consumption scope (owned versus leased capacity, construction water, upstream power-generation water), replenishment crediting rules, and basin matching are disclosed. An early, well-documented claim from a market leader could seed that standard. A thinly documented one would invite the same greenwashing skepticism that has dogged renewable energy certificates — and would make life harder for operators doing the work rigorously.
Background
Microsoft is one of the world’s largest data center operators, running cloud infrastructure across dozens of countries to serve its Azure, Microsoft 365, and AI businesses. In 2020 the company pledged to become water positive by 2030 as part of a broader sustainability program that also targets carbon-negative operations, and it has since promoted lower-water cooling designs for new facilities alongside a portfolio of watershed replenishment projects.
The claim lands in an industry racing to build AI capacity while facing growing scrutiny over resource consumption. Water has joined electricity as a gating factor for new data center permits, and no common audit standard yet exists for corporate water-positivity claims — which makes the methodology behind any such announcement as consequential as the announcement itself.
Research highlighted by Phys.org on June 26, 2026 warns that rising global temperatures and humidity are undermining one of the data center industry’s most important energy-efficiency strategies: free cooling, the practice of using cool outside air or water to remove server heat instead of running energy-hungry mechanical chillers. As more hours of the year become too hot or too humid for outside air to do the job, facilities worldwide face growing cooling energy demand.
The finding lands at a sensitive moment. Data center construction is accelerating to serve AI workloads, and cooling is typically the largest energy consumer in a facility after the IT equipment itself — so any climate-driven loss of free-cooling hours compounds an already steep power challenge.
Executive Summary
The core claim is straightforward: free cooling only works when the outside environment is cooler and drier than the conditions servers require, and climate change is steadily reducing the number of hours per year when that is true. Heat is only half the story — humidity matters just as much, because evaporative cooling systems, which cool air by evaporating water, lose effectiveness as the air becomes more saturated. Regions that were designed around thousands of free-cooling hours a year are watching that budget shrink.
Why it matters: efficiency assumptions made at design time are baked into a data center for decades. A facility engineered in a climate that no longer exists will either consume more energy than its models promised, lean harder on water, or require retrofit investment. For an industry under scrutiny over electricity and water consumption, the research reframes climate not as a sustainability talking point but as an engineering input — one that belongs in site selection, cooling-system choice, and capacity planning from day one.
Free Cooling Was the Industry’s Efficiency Workhorse
For the past fifteen years, the biggest gains in data center efficiency — reflected in falling PUE, the ratio of total facility power to IT power — came largely from using the outdoors as a heat sink. Air-side economizers pull in filtered outside air; water-side economizers and evaporative systems use cooling towers to shed heat with modest energy input. Hyperscale operators famously sited facilities in cool climates precisely to maximize these hours.
The research reported by Phys.org attacks the durability of that playbook. If the number of hours cool and dry enough for economization declines, chillers run more, and the efficiency gap between a well-sited facility and a poorly sited one narrows in the wrong direction. The gains of the last decade were real, but they were partly a loan from a stable climate — and the terms of that loan are changing.
Humidity Is the Underappreciated Variable
Public discussion of data center cooling fixates on temperature, but wet-bulb temperature — a combined measure of heat and humidity that sets the floor for evaporative cooling — is the more binding constraint. When wet-bulb temperatures rise, evaporative systems must work harder and consume more water for less cooling effect, and in extreme conditions they cannot reach the setpoints servers need at all. That pushes operators back toward mechanical refrigeration exactly when grid demand for air conditioning also peaks.
This has a second-order consequence: the trade-off between energy and water gets sharper. Evaporative cooling saves electricity but consumes water; dry coolers and chillers save water but consume electricity. Rising humidity degrades the attractiveness of the water-based option in many regions, forcing a choice between two increasingly expensive resources — often in communities already contesting data center water use.
Winners: Liquid Cooling, Cool Geographies, and Honest Modeling
If outside air can carry less of the load, the premium shifts to technologies that tolerate warmer heat rejection. Direct-to-chip liquid cooling and immersion cooling move heat in water or fluid rather than air, allowing higher operating temperatures and, in many designs, year-round heat rejection without compressors even in warm climates. The AI build-out was already pushing the industry toward liquid cooling for density reasons; climate trends add an efficiency rationale.
Geography gains value too. Sites in cool, dry, or high-latitude regions — the Nordics, parts of Canada, high-altitude locations — become relatively more attractive, though they bring their own constraints in connectivity, latency, and power availability. And engineering firms that model cooling against forward-looking climate projections rather than historical weather files gain a real advantage: a 25-year asset should be designed for the climate of 2040, not 2010.
Risks: Stranded Efficiency and Rising Operating Costs
The losers in this shift are facilities whose economics depend on free-cooling assumptions that no longer hold — particularly older air-cooled sites in regions warming fastest. Their operating costs drift upward without any change in workload, and their sustainability reporting deteriorates through no operational fault. For colocation providers, whose customers increasingly scrutinize PUE and water metrics in procurement, that drift is a competitive problem, not just an engineering one.
There is also a grid-level risk. The hours when data centers lose free cooling are the same hot hours when regional grids are most stressed. Climate-driven cooling demand is therefore correlated demand — it arrives when power is scarcest and most carbon-intensive, which is precisely the scenario utilities and regulators planning for data center growth need to model.
Background
Data center cooling has evolved through distinct eras. Early facilities ran cold and relied almost entirely on mechanical chillers. From roughly 2010 onward, hyperscale operators drove a revolution in economization — siting in cool climates, using outside air and evaporative systems, and widening acceptable server temperature ranges — which pushed the best facilities’ PUE from around 2.0 toward 1.1. That efficiency story became central to the industry’s answer to critics of its energy footprint.
The current AI build-out is testing every part of that model: rack power densities have jumped severalfold, cooling loads are climbing, and communities are scrutinizing both electricity and water consumption. Research showing that climate change is eroding free cooling adds a structural pressure on top of a cyclical boom — and helps explain the industry’s accelerating shift toward liquid cooling and climate-aware site selection.
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.
Nvidia has announced a liquid cooling system for AI data centers that circulates water described as running “hotter than a hot tub,” a design the company says can reduce electricity consumption and cut water use by up to 100%. The announcement, reported June 24, 2026 by Tom’s Hardware, targets one of the AI build-out’s most scrutinized side effects: the enormous water and energy appetite of the facilities that host Nvidia’s chips. The same report notes that sustainability challenges remain despite the headline claims.
Executive Summary
Nvidia, the dominant supplier of AI accelerators, is moving further down the stack — from chips and rack-scale systems into the cooling infrastructure that keeps them running. The newly announced system uses hot-water liquid cooling: instead of chilling coolant to low temperatures before it reaches the hardware, the loop runs deliberately warm, hotter than the roughly 40°C (104°F) at which a typical hot tub is kept, which is the comparison Nvidia’s framing invites.
Why does that matter? Warmer coolant is the key that unlocks both of the claimed benefits. If the water returning from the chips is already hot, a facility can often reject that heat to the outside air with simple dry coolers rather than energy-hungry chillers — cutting electricity — and without evaporative cooling towers, which consume water by design. That is the engineering logic behind the “up to 100%” water-reduction figure. The claim is significant if it holds up at scale, but as reported it is a vendor claim with important qualifiers, and the source coverage itself flags that sustainability challenges remain.
Water Is Becoming AI’s Second Resource Fight
Electricity has dominated the AI infrastructure debate, but water is close behind. Many conventional data centers cool themselves with evaporative systems: they literally evaporate water to carry heat away, because evaporation is cheap and effective. As hyperscale and AI campuses have multiplied, their water draw has become a flashpoint in drought-prone regions and a recurring obstacle in permitting and community relations.
Nvidia has a direct commercial stake in defusing that fight. Its rack-scale AI systems concentrate so much heat that air cooling is no longer practical, which already pushed the industry toward liquid cooling. If the company can also credibly claim its reference designs eliminate on-site cooling water, it removes an objection that slows down the very data center projects that buy its chips. In that sense this is as much a market-access play as an engineering one.
The Counterintuitive Physics of Cooling with Hot Water
“Hot-water cooling” sounds like a contradiction, but it rests on straightforward thermodynamics. A chip does not need cold coolant; it needs coolant that is cooler than the chip and flowing fast enough to carry heat away. Liquid is far denser than air as a heat-transfer medium, so even warm water can hold chip temperatures within limits.
The payoff comes at the other end of the loop. Cold-water systems need chillers — essentially industrial refrigerators — whose compressors are among the largest energy consumers in a data center. Evaporative towers avoid some of that electricity but spend water instead. A loop that returns water hotter than the outdoor air can shed its heat through dry coolers, closed radiators that use neither compressors nor evaporation. That is the mechanism behind both claims in the announcement: less electricity because chillers shrink or disappear, and less water because nothing is evaporated. Hotter return water is also more useful for heat reuse, such as district heating, though the reporting here does not say whether Nvidia is claiming that benefit.
Reading the “Up to 100%” Claim Carefully
“Up to 100%” is a ceiling, not a promise. Real-world results will depend on climate — dry cooling gets harder on very hot days, when some designs fall back on water assist — as well as on facility design and how much of a site’s load actually sits on the new system. The reported claim does not, on its face, distinguish between a best-case new build in a favorable climate and a typical deployment.
There is also a boundary question. Eliminating on-site cooling water does not eliminate a data center’s water footprint, because the power plants that generate its electricity often consume water themselves. Reduced electricity consumption helps on that front too, but “water-free” at the fence line is not the same as water-free end to end. The source’s own caveat — that sustainability challenges remain — is best read in this light: the announcement addresses a real problem without dissolving it.
Who Feels This Announcement
Cooling incumbents and the liquid-cooling supply chain feel it first. When the dominant chip vendor blesses a particular thermal architecture, it tends to become the default for new AI capacity, shaping demand for cold plates, coolant distribution units, and dry coolers, and putting pressure on vendors invested in evaporative or chilled-water designs. Operators, meanwhile, gain a potential permitting and siting advantage: a campus that can credibly promise near-zero cooling-water draw is an easier sell to water-stressed municipalities.
The open competitive question is whether this arrives as an open reference design others can build on or as another layer of the Nvidia-specified stack. The reporting available here does not say. Either way, buyers should expect warm-water readiness — higher allowable coolant temperatures across IT hardware — to show up in procurement requirements, because the economics above only materialize if the whole rack tolerates the heat.
Background
Nvidia is the world’s leading supplier of the GPUs (graphics processing units) that train and run modern AI models, and its data center business has grown into one of the largest in the technology industry. As its systems evolved from individual chips into full pre-integrated racks drawing unprecedented power, the company has taken an increasingly active role in specifying the surrounding infrastructure — power delivery and cooling included — because its hardware roadmap now depends on facilities that can handle the heat.
Data center cooling has historically split between air cooling, chilled-water systems, and evaporative designs that trade water for electricity. AI’s density has pushed the industry rapidly toward direct liquid cooling, and water consumption has become a headline issue in siting battles. Warm-water liquid cooling — long used in some high-performance computing installations — is the established engineering idea this announcement scales up and brands for the AI era.
Data Center Knowledge published a report on June 18, 2026 examining why the data center industry continues to rely on evaporative cooling — a heat-rejection method that consumes large volumes of water — even as public and regulatory backlash over water use intensifies. The piece frames the industry’s position as hesitation rather than refusal: operators broadly acknowledge the water problem but have been slow to abandon a technology that remains cheaper and more energy-efficient than the alternatives.
Executive Summary
The report’s core subject is a tension the industry has lived with for years and that the AI build-out has sharpened: evaporative cooling rejects heat by evaporating water, which makes it highly energy-efficient but water-hungry, while the main alternatives — dry (air-cooled) systems and refrigerant-based chillers — save water at the cost of higher electricity consumption, larger equipment footprints, or both. In markets where power is the scarcest commodity a data center can buy, trading water savings for a bigger electrical load is not a simple upgrade; it is a genuine engineering and economic trade-off.
That trade-off is why the headline speaks of hesitation. Operators face mounting pressure from drought-affected communities, local governments, and sustainability commitments to cut water use, and technologies such as closed-loop liquid cooling and hybrid systems are maturing. But retrofitting existing facilities is expensive, and for new builds the calculus depends heavily on local climate, water price, and power availability — variables that differ from one metro to the next. The result is an industry moving unevenly rather than uniformly, which is precisely the dynamic worth understanding for anyone siting capacity or evaluating operators’ sustainability claims.
The Water-for-Energy Trade at the Heart of Cooling
Every data center must move heat from chips to the outside world, and the physics offers no free option. Evaporative systems — cooling towers and their variants — exploit the fact that evaporating water absorbs enormous amounts of heat, which lets a facility reject heat with comparatively little electricity. Dry coolers and air-cooled chillers avoid consuming water but must push heat into the air mechanically, which takes more fan and compressor power, especially on hot days when the temperature difference working in the operator’s favor shrinks. In plain terms: saving water usually means burning more electricity, and in an era when grid connections are the binding constraint on data center growth, extra megawatts spent on cooling are megawatts not available for revenue-generating compute.
This is the economic logic the Data Center Knowledge piece points at with its framing of industry hesitation. An operator that switches a large campus from evaporative to dry cooling is not just paying for new equipment; it is accepting a permanently higher power draw — degrading power usage effectiveness, the industry’s standard efficiency metric — and potentially reducing the sellable IT capacity of a power-constrained site. Where water is cheap and power is scarce, the incumbent technology keeps winning on spreadsheets even as it loses in public opinion.
Why the Backlash Is Getting Harder to Price at Zero
For most of the industry’s history, water was effectively an afterthought in site selection — abundant, inexpensive, and invisible to the public. That has changed. Data center water consumption has become a recurring flashpoint in drought-prone regions, a subject of local permitting fights, and a standard line of questioning for journalists and community groups evaluating new projects. Operators now routinely publish water usage effectiveness figures and, in some cases, commit to becoming “water positive” — replenishing more water than they consume.
The practical consequence is that water carries a growing shadow price beyond the utility bill: longer permitting timelines, conditions attached to approvals, reputational exposure, and in the worst case the loss of a site altogether. The report’s premise — that the industry hesitates rather than transitions — suggests that many operators still judge those risks manageable relative to the hard costs of switching. Whether that judgment holds depends largely on how regulators and communities act next, which varies enormously by jurisdiction.
The Alternatives Are Real, but Not Drop-In
The transition options are well understood in engineering terms. Dry cooling eliminates onsite water evaporation at the cost of energy and space. Hybrid systems run dry most of the year and evaporate water only during peak heat, cutting consumption substantially without the full energy penalty. Direct-to-chip liquid cooling and immersion cooling — increasingly common in AI deployments because high-density chips demand them — move heat in closed loops that consume little or no water onsite, though the heat still has to be rejected somewhere, and that final stage can itself be wet or dry. None of these is a simple swap for an operating facility: cooling infrastructure is capital-intensive, deeply integrated with a building’s design, and typically replaced on decade-plus cycles.
That replacement cycle is the quiet variable in the whole debate. The realistic path for the industry is less about retrofitting the installed base and more about what gets designed into the enormous wave of new construction now underway. If new AI-era facilities standardize on low-water designs where climate and economics allow, the fleet’s water profile shifts over years, not quarters. If they default to evaporative cooling because power constraints dominate, the backlash the report describes is likely to intensify.
Winners, Losers, and the Siting Chessboard
The cooling transition redistributes advantage. Cooler, water-rich regions gain appeal because they make both wet and dry cooling cheaper; hot, arid markets that boomed on cheap land and power face the sharpest version of the water-versus-energy dilemma. Vendors of hybrid and liquid cooling systems benefit from every tightening of water rules. Utilities and municipalities gain leverage, since water service is becoming a negotiated element of large deals rather than a formality. And operators that invested early in low-water designs acquire a permitting and public-relations asset that is difficult for laggards to replicate quickly. Buyers of colocation and cloud capacity should read cooling architecture as a proxy for siting risk: a facility’s water dependence is now part of its long-term cost and continuity profile.
Background
Cooling is one of the two great resource demands of data centers, alongside electricity: every watt a server consumes becomes heat that must be removed. For decades, evaporative cooling towers have been a workhorse of large-scale heat rejection across many industries because evaporating water is thermodynamically cheap. Data centers adopted the approach widely as the industry scaled through the cloud era, and it helped drive the sector’s headline efficiency gains. The AI construction boom that accelerated through the mid-2020s raised the stakes on both sides of the equation — far denser computing produces far more heat, while the communities hosting these facilities have grown increasingly vocal about local water and power impacts. Trade publication Data Center Knowledge, which published the report discussed here, has tracked this cooling debate as one of the defining infrastructure questions of the AI build-out.
Google has unveiled an open-source liquid-to-air cooling sidecar designed for air-cooled data center environments, as reported by Data Center Dynamics on June 17, 2026. The design targets one of the most pressing constraints in the industry: modern AI accelerators increasingly require direct liquid cooling, while the vast majority of existing data center floor space was built to move heat with air alone.
A sidecar of this type is a heat-exchanger cabinet that sits beside a rack of liquid-cooled servers, circulating coolant through the chips in a closed loop and then rejecting that heat into the room’s existing airflow — no facility water piping required. By publishing the design openly, Google is inviting vendors and operators to build and adapt it rather than keeping it proprietary.
Executive Summary
The announcement matters less for what the hardware is than for where it lets liquid cooling go. Direct-to-chip liquid cooling has become effectively mandatory for the densest AI training hardware, but deploying it normally requires facility-level infrastructure — coolant distribution units, piping loops, and water connections that most operating data centers simply do not have. A liquid-to-air sidecar sidesteps that requirement: the liquid loop stays local to the rack, and the building’s existing air-handling systems carry the heat away as they always have.
That makes this a retrofit play. Enterprises, colocation tenants, and smaller operators sitting on air-cooled capacity gain a path to host at least some liquid-cooled equipment without construction projects. It is also a continuation of Google’s recent posture of contributing cooling designs to the open hardware ecosystem rather than treating them as competitive secrets — a bet that standardizing the plumbing layer accelerates the whole market Google’s cloud and AI businesses depend on.
The report available at the time of writing is brief, and the announcement as covered leaves key engineering and availability details unstated — including the design’s cooling capacity, its publication venue and license, and whether it reflects hardware Google runs in production. Those specifics will determine whether this is a broadly useful reference design or a niche one.
The Retrofit Gap Is the Industry’s Quiet Bottleneck
Headlines about AI data centers focus on new gigawatt-scale campuses, but most of the world’s installed data center capacity is older, air-cooled space designed for racks drawing 5 to 15 kilowatts. Current AI server racks can draw many times that, and the chips inside them ship with cold plates that expect liquid, not airflow. Operators of existing facilities face an unattractive menu: leave AI workloads to someone else, undertake disruptive plumbing retrofits in live buildings, or find a bridge technology.
Liquid-to-air sidecars are that bridge. Because the liquid never leaves the immediate vicinity of the rack, the facility itself does not need water loops, external coolant distribution plants, or new mechanical rooms. The trade-off is physics: the room’s air systems still have to absorb every watt the sidecar rejects, so total rack density remains bounded by the building’s air-handling and power envelope. A sidecar extends the life of air-cooled space; it does not turn a legacy building into a frontier AI facility.
Why Give the Design Away?
Google has form here. The company has run liquid-cooled custom TPU accelerators internally since roughly 2018, and in 2025 it announced it would contribute a production coolant distribution unit design to the Open Compute Project, the industry body through which hyperscalers share hardware specifications. Open-sourcing a sidecar fits the same logic: cooling hardware is not where Google differentiates, but an immature, fragmented cooling supply chain slows everyone — including Google and the customers of its cloud business.
Open designs give equipment manufacturers a common reference to build against, which tends to lower prices, improve interoperability, and widen the vendor pool. For Google there is also a soft-power dividend: hyperscaler-authored designs shape industry standards, and the ecosystem that grows up around them tends to stay compatible with the author’s infrastructure choices. None of that makes the contribution less useful — but it is worth understanding open-source hardware as strategy, not charity.
Winners, Losers, and the Honest Limits
The clearest beneficiaries are operators of existing air-cooled facilities — enterprise server rooms, regional colocation providers, and edge sites — who gain an on-ramp to liquid-cooled hardware without capital construction. Cooling-equipment manufacturers get a design they can productize; some may welcome the demand signal, while vendors selling proprietary sidecar and rear-door heat exchanger products now face an open alternative that could compress margins.
The honest caveat is that the announcement, as reported, is a design release, not a product with published performance data. Until the specification’s capacity, tested configurations, and licensing terms are public and third parties have built against it, the practical impact is prospective. Open hardware contributions have a mixed track record: some become de facto standards, others languish without a manufacturing ecosystem. Which path this design takes depends on details the initial coverage does not yet supply.
Background
Google is one of the world’s largest data center operators and has cooled its custom TPU AI accelerators with liquid since roughly 2018 — years before liquid cooling became an industry-wide necessity. In 2025 it began contributing pieces of that cooling stack to the open hardware ecosystem, announcing a production coolant distribution unit design for the Open Compute Project, the body through which hyperscalers share server and infrastructure specifications.
The backdrop is a market-wide squeeze: AI hardware demand is rising far faster than new liquid-ready facilities can be built, leaving a large installed base of air-cooled data centers unable to host the densest equipment. Bridge technologies that bring liquid cooling into air-cooled buildings — sidecars and rear-door heat exchangers among them — have become one of the fastest-moving segments of data center engineering.
