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With cars about to get more expensive, it might be time to start tinkering.

More than a decade ago, when I was a young editor at Popular Mechanics, we got a Nissan Leaf. It was a big deal. The magazine had always kept long-term test cars to give readers a full report of how they drove over weeks and months. A true test of the first true production electric vehicle from a major car company felt like a watershed moment: The future was finally beginning. They even installed a destination charger in the basement of the Hearst Corporation’s Manhattan skyscraper.
That Leaf was a bit of a lump, aesthetically and mechanically. It looked like a potato, got about 100 miles of range, and delivered only 110 horsepower or so via its electric motors. This made the O.G. Leaf a scapegoat for Top Gear-style car enthusiasts eager to slander EVs as low-testosterone automobiles of the meek, forced upon an unwilling population of drivers. Once the rise of Tesla in the 2010s had smashed that paradigm and led lots of people to see electric vehicles as sexy and powerful, the original Leaf faded from the public imagination, a relic of the earliest days of the new EV revolution.
Yet lots of those cars are still around. I see a few prowling my workplace parking garage or roaming the streets of Los Angeles. With the faded performance of their old batteries, these long-running EVs aren’t good for much but short-distance city driving. Ignore the outdated battery pack for a second, though, and what surrounds that unit is a perfectly serviceable EV.
That’s exactly what a new brand of EV restorers see. Last week, car site The Autopian covered DIYers who are scooping up cheap old Leafs, some costing as little as $3,000, and swapping in affordable Chinese-made 62 kilowatt-hour battery units in place of the original 24 kilowatt-hour units to instantly boost the car’s range to about 250 miles. One restorer bought a new battery on the Chinese site Alibaba for $6,000 ($4,500, plus $1,500 to ship that beast across the sea).
The possibility of the (relatively) simple battery swap is a longtime EV owner’s daydream. In the earlier days of the electrification race, many manufacturers and drivers saw simple and quick battery exchange as the solution for EV road-tripping. Instead of waiting half an hour for a battery to recharge, you’d swap your depleted unit for a fully charged one and be on your way. Even Tesla tested this approach last decade before settling for good on the Supercharger network of fast-charging stations.
There are still companies experimenting with battery swaps, but this technology lost. Other EV startups and legacy car companies that followed Nissan and Tesla into making production EVs embraced the rechargeable lithium-ion battery that is meant to be refilled at a fast-charging station and is not designed to be easily removed from the vehicle. Buy an electric vehicle and you’re buying a big battery with a long warranty but no clear plan for replacement. The companies imagine their EVs as something like a smartphone: It’s far from impossible to replace the battery and give the car a new life, but most people won’t bother and will simply move on to a new car when they can’t take the limitations of their old one anymore.
I think about this impasse a lot. My 2019 Tesla Model 3 began its life with a nominal 240 miles of range. Now that the vehicle has nearly six years and 70,000 miles on it, its maximum range is down to just 200, while its functional range at highway speed is much less than that. I don’t want to sink money into another vehicle, which means living with an EV’s range that diminishes as the years go by.
But what if, one day, I replaced its battery? Even if it costs thousands of dollars to achieve, a big range boost via a new battery would make an older EV feel new again, and at a cost that’s still far less than financing a whole new car. The thought is even more compelling in the age of Trump-imposed tariffs that will raise already-expensive new vehicles to a place that’s simply out of reach for many people (though new battery units will be heavily tariffed, too).
This is no simple weekend task. Car enthusiasts have been swapping parts and modifying gas-burning vehicles since the dawn of the automotive age, but modern EVs aren’t exactly made with the garage mechanic in mind. Because so few EVs are on the road, there is a dearth of qualified mechanics and not a huge population of people with the savvy to conduct major surgery on an electric car without electrocuting themselves. A battery-replacing owner would need to acquire not only the correct pack but also potentially adapters and other equipment necessary to make the new battery play nice with the older car. Some Nissan Leaf modifiers are finding their replacement packs aren’t exactly the same size, shape or weight, The Autopian says, meaning they need things like spacers to make the battery sit in just the right place.
A new battery isn’t a fix-all either. The motors and other electrical components wear down and will need to be replaced eventually, too. A man in Norway who drove his Tesla more than a million miles has replaced at least four battery packs and 14 motors, turning his EV into a sort of car of Theseus.
Crucially, though, EVs are much simpler, mechanically, than combustion-powered cars, what with the latter’s belts and spark plugs and thousands of moving parts. The car that surrounds a depleted battery pack might be in perfectly good shape to keep on running for thousands of miles to come if the owner were to install a new unit, one that could potentially give the EV more driving range than it had when it was new.
The battery swap is still the domain of serious top-tier DIYers, and not for the mildly interested or faint of heart. But it is a sign of things to come. A market for very affordable used Teslas is booming as owners ditch their cars at any cost to distance themselves from Elon Musk. Old Leafs, Chevy Bolts and other EVs from the 2010s can be had for cheap. The generation of early vehicles that came with an unacceptably low 100 to 150 miles of range would look a lot more enticing if you imagine today’s battery packs swapped into them. The possibility of a like-new old EV will look more and more promising, especially as millions of Americans realize they can no longer afford a new car.
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Can AI help emergency managers make faster decisions when every second counts?
Meteorologists had nothing polite to say about Tropical Storm Bertha. The “weak, disorganized, and lopsided” system made initial landfall in Louisiana last week as a “hot, sheared mess,” one that forecasters doubted would reach Texas with much oomph at all. Still, the Galveston County Consolidated Drainage District — the local flood mitigation and drainage management entity for the state’s most flood-prone county — had stood at the ready, posting updates on the storm’s progress to its Facebook feed in the lead-up.
There had been action behind the scenes, too. Since this spring, the county has relied on a new “AI-powered flood warning solution” pilot program to help local administrators identify the gaps in their understanding of the county’s flood risk and monitor rising water levels in real time. In a crisis, a chatbot could even advise them on when to issue an evacuation order.
“Imagine you’re an operator and you have to tell people to leave their homes because of floods coming in,” Todd Barr, the CEO of Axonis Decision Intelligence, which has partnered with the smart water-level sensor company Simplicity Integration in Texas’ Galveston County, told me. Axonis provides AI-assisted decision-making tools to clients in a number of time-sensitive industries, and in every case, “You want a paper trail of the data you used to make the decision — the reasoning and the model you used — and our platform does all of that,” Barr went on.
Issuing evacuation notices is a famously thorny business, and one that has resulted in high-profile and high-casualty failures, including in the Paradise, California, and Maui wildfires. Particularly noteworthy were the 2025 Kerr County floods that killed more than 100 people in Texas’ Hill Country after local officials took 90 minutes to send phone alerts once they became aware of the rising river.
In many cases, particularly in more rural counties, the teams making the evacuation decisions are small and lack sufficient training not only on when to make such a call, but even on how to word it. “The people who are put in the position of issuing the messages are doing 20 other things at the same time,” Jeannette Sutton, a researcher at the University at Albany’s Emergency and Risk Communication Message Testing Lab, told me when I reported on evacuation notices after the Los Angeles fires.
As for Galveston, “100%” of the buildings on the densely populated island are at flood risk, with modeling suggesting a worst-case-scenario hurricane could produce 26 feet of storm surge. Much of the city’s stormwater infrastructure additionally predates modern climate-change-intensified rainfall probabilities, with the district in the midst of a $54 million drainage project aimed at mitigating future flooding by building a pump station and enlarging sewer lines.
As part of the region’s ongoing resiliency work, the Galveston County Consolidated Drainage District installed seven of Simplicity’s water-level sensors —the county’s first — at locations on the mainland. (There are no sensors currently on Galveston Island proper.) Simplicity’s Axonis-powered system, SI-Ai, also pulls in data from NOAA, the U.S. Geological Survey, and Houston’s Harris County to present residents of the entire region with a live flood-risk dashboard, complete with intuitive green-yellow-red indicators to evaluate their neighborhood hazard level in real time. Operators also have their own proprietary dashboard where they can monitor sensors and are prompted to ask questions to interpret readings and open “investigations” if something appears amiss.

“If I’m the municipality, I can say, ‘Okay, here’s what the forecast is looking like and what is potentially going to happen,” Alison Reese, the COO and co-founder of Simplicity, explained to me. “Then I could ask a question like, ‘Hey, what other locations in this watershed are at high risk for flash flooding?’”
That’s where Axonis, the artificial intelligence company, comes in. “Today you would have to be like, ‘Alright! Get the weather report, quick! What’s happening? What are the sensors saying? Okay Bill, now what’s the upstream sensor saying?’” Barr said, acting out the frantic scenario of trying to source data from multiple streams at once. “All of that is what we’re automating.” (Galveston’s Office of Emergency Management is “not the POC for the flood sensor operations,” a representative told me; the drainage district oversees the Axonis-Simplicity partnership, and did not return a request for an interview. The mayor of League City, a city 35-minutes north of Galveston that is also managed by the district, has publicly criticized the SI-Ai program as a separate sensor network that duplicates the work of the Harris County Flood Control District.)
Working from the assumption that emergency managers have to parse reams of data in short periods of time — flash floods can rise as much as 10 feet in an hour — Axonis provides what is essentially a chatbot for authorities to query potential decisions ranging from road closures to evacuation notices, based on feedback from the sensors. It stops short, however, of having a dialogue box that pops up to tell operators, EVACUATE THIS NEIGHBORHOOD NOW.
When Barr demoed the program to me, he had the tool configured to create a credit risk review memo for a would-be banking client. (Axonis also has customers in the banking and defense sectors.) The dashboard essentially functioned the same as it would for Galveston County, though, and his investigation returned the kind of simplified, emoji-studded one-sheet that users of large language model-powered AI interfaces would immediately recognize. In this case, the tool identified a “🔴Risk Alert CANDIDATE” — Barr said that would be a particular sensor, in the case of Galveston — and followed it with a summary and bullet-pointed sections breaking down “⚠️Credit Risk Indicators” and “💧Liquidity Position.” (In a screenshot of an example flood report for Simplicity, shared with me, those sections were replaced by “📍Site Location” and “💧Water Level — Last 72 Hours.” I wondered what else was possible: “🌊Historic hydraulic risk”? “💀Vulnerable Populations”? )

The system then takes operators through a four-step decision-making model based on the OODA Loop, a common workflow in military contexts that involves justifying actions through evidence-based observations. “We always keep a human in the loop on these things, at least today in 2026 — though who knows in two or three years,” Barr said. He clarified in a later conversation with me, though, that “Axonis and [AI] tools should never tell you to evacuate now. It should tell you the information you need to make that decision.”
That was a point Barr stressed numerous times during our conversation: That Axonis’ chatbot is intended as a brainstorming tool or sounding board, and one that keeps a careful paper trail, “cryptographically sealing” any eventual decisions for review and attestation later. I likened it to a police body camera, and Barr didn’t dispute the similarities. “It’s an accountability tool,” he told me.
Of course, that means the burden of decision-making still falls on potentially fallible humans. I worried in particular that by sharing the responsibility with AI, human operators might get lazy or fail to properly question a decision the program might be leading them toward, particularly in an instance of hallucinated data. To the latter point, Barr told me that this is part of what Axonis is designed to address. “You can’t just take the sensor data and throw it into Claude and be like, ‘Alright, go make a decision for me.’ You need to set guard rails,” he said.
As to the former point, Barr told me the chat includes a disclaimer reminding its users that AI can make mistakes, and that the company trains its customers on how LLM technology works. “At the end of the day, it’s a tool, not a decider,” he said, although he allowed that it might be used to automatically trigger warning lights, sirens, or barriers, such as closing a flooded roadway.
I also posed the concern about complacency to Ali Mostafavi, a professor who supervises the UrbanResilience.AL Lab at Texas A&M, which researches, among other things, how artificial intelligence might be utilized in emergency contexts. Mostafavi agreed that there is always a risk in cognitive outsourcing, but that there is a “counter-argument that is also valid — that without these technologies, we have seen what can happen. We had the catastrophic floods last year in Kerr County, and if a similar technology had existed back then, an automated system could have identified the flash flood, and many young children would be alive today.”
Still, Barr told me he isn’t aware of Axonis advising in an actual evacuation order yet. While it is operational, the predictive model remains untested against its highest-stakes use case: the extremes of a climate-changed world, where formerly unthinkable outcomes may be one storm away.
“The more we can stress-test these technologies in real operational settings and use that feedback loop to improve the technologies, the better,” Mostafavi said. “But that’s easier said than done, because to have a technology implemented in an operational setting it should already be stress-tested, right?”
Bertha, though, was not that reckoning; the gusty squalls blew through Galveston last week without even disturbing the dinner reservations at the marina. But although it was already back to 90 and sunny by Monday morning on the Texas Gulf, the drainage in Galveston County, as in many places around the country, remains outdated and easily overwhelmed. One day, inevitably, the water will come. Hopefully when it does, someone or something will be watching.
The large renewables developer changes tack “in response to federal energy objectives.”
Trump’s solar freeze is now so tough that at least one renewable energy developer has asked his administration to turn their permitting application into a data center and gas-fired power plant instead.
Renew Development HoldCo – an LLC created by Clearway Energy Group – wrote the Bureau of Land Management in April asking if they could amend their 2021 application to build the Amber solar project, a 500-megawatt solar project in the Nevada desert that would require building on federal land. Their requested change? “[T]o formally remove the proposed solar facility and replace it with the development of a proposed data center and natural gas facility,” according to a copy of the letter I obtained.
“This amendment is the result of a shift in our internal development priorities and an updated assessment of project timing, in order to better align with the goals of our Administration,” reads the letter, which is dated April 3 and signed by Clearway’s chief development officer John Woody. “The data center concept is in exploratory early stages and as such has a longer and more flexible development horizon, and we believe its schedule will better align with the Bureau’s current workload and staffing plans.”
Now, this swap is somewhat shocking but shouldn’t exactly be a surprise. Companies with federal energy leases are struggling to get their renewable projects permitted by a hostile Trump administration. We’ve already seen some offshore wind developers ditch their leases in favor of payouts and commitments to build more fossil infrastructure. Clearway Energy Group is owned by Global Infrastructure Partners and TotalEnergies, the latter of which struck such a deal in March.
But this does appear to represent an aberration for Clearway, one of the nation’s largest operators of renewable energy projects and whose marketing materials primarily focus on “clean energy.” Nearly all of the company’s portfolio is carbon-free power or energy storage generation sans a handful of “flexible generation” energy projects in California, according to an online map of their project pipeline. The company did not disclose in the documents I reviewed if the gas plant itself would power the data center, provide power to the wider grid, or both.
Candidly, I’ve been watching like a hawk to see if Trump’s chokehold on solar and wind permits would lead to more gas infrastructure and data centers on federal property instead. And companies are getting data center permits when they ask to swap out their solar farm for AI infrastructure. On Friday, I reported that a joint venture involving renewables developer Arevon and energy trader Bill Perkins got permission from BLM to switch an environmental permit tied to a solar farm for one allowing a new data center. Environmentalists plan to legally challenge BLM’s determination as they say it’s a test case for the future of federal land policy.
It’s unclear if Clearway would be the one to build and construct this hypothetical data center and power plant. I for one can’t find any evidence of Clearway developing data centers before. My best guess is that if they do move forward with this, it would look like the joint venture I covered on Friday, where Arevon distanced itself from the actual day-to-day operations of the development and a new firm specializing in data centers came in. But that’s just a hunch and there’s a saying about assumptions.
Nevertheless, Clearway is clearly handling the permitting side. Attached to the Clearway letter was an application also sent to BLM for constructing utility and telecommunications facilities on federal lands, a document technically known as an SF299. The application states Clearway considered using solar energy for the data center as well as using private land, but their alternative designs weren’t selected because they had “higher environmental and stakeholder conflicts.”
Also, in a section of the document requesting Clearway provide a “statement of need for the project,” the developer said it was submitting this proposal “in response to federal energy objectives” and specifically cited Trump’s Day 1 executive order which the company said “encourage[d] development of reliable energy projects on federal lands.”
I reached out to Clearway asking for more information on the letter and application. In response, the company claimed the solar project wasn’t being killed – it simply was moved to private land. They also declined to comment on the data center and gas project. Instead, I was provided a statement attributable to an unnamed spokesperson that “while we do not comment on any individual application while it moves through federal approval processes, we are pleased to be advancing more than 4 GW of solar and battery resources in Nevada on private and public lands and expect those projects to deliver tremendous economic benefits to the communities where they’re built.”
“Clearway values its strong working partnership with the BLM, its Southern Nevada office, and also with state and local interests in Nevada. Across all of these relationships, we continuously assess how best to develop and deliver infrastructure that meets needs and aligns with local and national policies and goals.”
Current conditions: Hurricane Genevieve formed into the first major storm of the season, strengthening to Category 4 off Mexico’s Pacific Coast on Sunday but steering clear of any land for now • Hurricane Fausto, meanwhile, is weakening as it heads toward Hawaii • China evacuated hundreds of thousands of people as Typhoon Noul made landfall.

Wildfires in France and Spain forced roughly 300,000 people to evacuate their homes in what the French Interior Minister Laurent Nuñez called an “unprecedented” blaze. In Spain, the central western province of Avila suffered what the broadcaster France24 described as its “worst blaze in recent history” as Prime Minister Pedro Sanchez directly linked the disaster to climate change. By Sunday evening, in France, flames had come within nine miles of the southwestern city of Bordeaux in the heart of the nation's storied winelands as President Emmanuel Macron vowed to “rebuild.” Others saw the disaster as a sign of overdue lifestyle and infrastructure changes in the face of a warming planet. In Le Monde, the newspaper of record, the philosopher Cynthia Fleury and the Socialist mayor of the town of Saint-Médard-en-Jalles, Stéphane Delpeyrat-Vincen, argued: “What is burning is not just forests, but a way of inhabiting the land that is no longer possible.” The fires come weeks after a series of historic heat waves in Europe, including the hottest June on record, which made tinderboxes of parched woodlands.
President Donald Trump last week announced a landmark deal with Saudi Arabia to help build the kingdom’s first nuclear power station, besting the Russians and the Chinese in a race to tap into one of the world’s most coveted new export markets for atomic power technology. While the White House has yet to release all the details on the geopolitically meteoric agreement with Riyadh, sources with knowledge of the deal have confirmed to me what’s been reported elsewhere — that the deal will almost certainly include new large-scale Westinghouse AP1000s. Over the weekend, The New York Times identified another element to the partnership: Trump’s family and personal friends may benefit. The newspaper pointed to ties between a firm owned by Secretary of Commerce Howard Lutnick’s sons and Westinghouse; links between Eric Trump and Donald Trump Jr.’s investments into quantum computing and former Texas Governor Rick Perry’s Fermi America project to build AP1000s in Texas; and suggested that TAE Technologies, the fusion company merging with the corporate parent of Trump’s Truth Social platform, could see potential benefits from the Saudi deal. “There is no evidence at this point that Mr. Trump’s friends or family helped orchestrate the Saudi nuclear deal,” reporters Eric Lipton and Kate Kelly wrote. “Yet a number of the president’s allies and relatives, including members of his cabinet, stand to benefit if his big bet on nuclear power pays off. Certain investors with ties to these deals are positioned to profit, even if the delivery of large new loads of nuclear-powered electricity remains years away.”
The Trump administration is, in fact, making a real attempt at building new AP1000s at home. As my colleague Robinson Meyer wrote last month, a major Department of Energy deal would help utilities buy the parts needed to build more Westinghouse reactors.
Chip giant Nvidia is considering providing a $250 billion backstop to fund OpenAI’s data center project in southern Ohio, The Wall Street Journal reported on Sunday. The deal would guarantee up to half of the capital needed to lease SoftBank’s 10-gigawatt data center to supply computing power to the ChatGPT maker.
GE Vernova’s backlog of orders for gas turbines, meanwhile, now stretches to 2031 and accounts for a cumulative 116 gigawatts of power-producing capacity. In its latest earnings call, covered in Utility Dive at the end of last week, the company posted double-digit revenue and order growth in the division that supplies equipment for gas, hydro, nuclear, and grid facilities.
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Back in February, I told you that Japan was stepping up its efforts to extract rare earths from seabed minerals. On Friday, Tokyo confirmed it had discovered that medium and heavy rare earth elements accounted for about 54% of the rare earths mined from mud recovered from a remote Pacific island, Mining.com reported. The finds come after the government-backed vessel Chikyu sucked nearly 50 metric tons of mud from Minamitori Island, an uninhabited atoll located closer to Wake Island than Tokyo. Heavy rare earths, such as dysprosium, terbium, and yttrium — and medium rare earths such as samarium, europium, and gadolinium — are trickier to process. China controls the market for both categories by a wider margin than for light rare earths. That makes Japan’s discovery so exciting. Separating metals out of the mud could be an easier process than from other ores, potentially supplying the democratic world with a new source of non-Chinese minerals.
When the Biden administration tried putting rules in place for producing clean hydrogen, as my colleague Emily Pontecorvo explained nicely at the time, the regulations posed a problem for efforts to make fuel through nuclear-powered electrolysis. That’s because the incentives to ensure developers built new solar and wind rather than cannibalizing existing grid resources for hydrogen production made it impossible for nuclear reactors to qualify. Companies such as Constellation Energy, which had the nation’s leading experiment in nuclear-powered hydrogen production, protested. It all turned out to be for nought, since Trump ultimately wiped out the tax credits. As with so much nuclear technology that faces political tumult in America, South Korea is moving in to try its hand at hydrogen fuel production. Korea Hydro & Nuclear Power, the country’s state-owned nuclear giant, said it will launch a pilot program to produce hydrogen using heat and electricity from reactors, Hydrogen Insight reported last week.
India, meanwhile, is beefing up its plans for small modular reactors. Earlier this month, I reminded you about New Delhi’s plans to open its nuclear sector to foreign investments after years of icing out all but Russia’s state nuclear vendor. That isn’t to say India isn’t looking to continue building its own indigenously-designed units. On Friday, NucNet reported that the country plans to develop and operate at least five of its own SMR designs by 2033.
Last week, Heatmap editorial fellow Ameya Hadap broke news that Koloma, a startup seeking to spur natural production of hydrogen, had inked a deal to look for gas deposits across 817 square miles of the Philippines’ largest island, Luzon. It’s not the only subsurface search for clean energy. Last week, the country’s Economy and Development Council approved the Philippines’ first financing package to de-risk geothermal investments, Think Geo Energy reported.