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Drax and Power Minerals partner on green cement material

Drax has signed a 20-year joint venture agreement with Power Minerals Ltd (PML) to develop a factory for processing legacy ash into supplementary cementitious material (SCM), or fly ash, an ingredient in low-carbon green cement. The factory will be built next to the Drax power station in Selby, Yorkshire on land leased from Drax. Under […]

Drax has signed a 20-year joint venture agreement with Power Minerals Ltd (PML) to develop a factory for processing legacy ash into supplementary cementitious material (SCM), or fly ash, an ingredient in low-carbon green cement.

The factory will be built next to the Drax power station in Selby, Yorkshire on land leased from Drax. Under the agreement, PML will build, own and operate the new facility, while Drax will sell its legacy pulverised fuel ash (PFA) to the joint venture and provide power to the factory.

The factory is due to enter service by the end of 2026, with an initial production capacity of 400,000 tonnes per year. According to the announcement, the facility will ultimately process millions of tonnes of PFA.

The move marks the latest shift for Drax, following the power station’s gradual conversion to biomass since the mid-2010s. Drax says it is the single largest generator of renewable electricity in the UK. However, the power station has also been found to be the largest emitter of carbon dioxide (CO2) in the UK by think-tank Ember Energy, based on an analysis of official data from the UK Emissions Trading Scheme registry and company annual reports.  Drax Group has also been fined by UK regulators for misreporting data on the forestry type and sawlog content it uses for its biomass.

Nonetheless, Drax is continuing its push to bolster its green credentials. The company is also proposing to add carbon capture and storage (CCS) to the power station site. However, this bioenergy with carbon capture and storage (BECCS) initiative still requires government funding, as well as a confirmed route to carbon storage, in order to go ahead.

The announcement on the fly ash partnership represents a further step in Drax’s green push. The company noted in the announcement that cement production accounts for around 8% of global CO2 emissions. It added that PML had estimated that use of PFA from Drax could reduce CO2 emissions by a minimum of 6m tonnes over the duration of their partnership, compared to using conventional cements.

“This is a landmark deal not only for Drax, but for the UK construction industry,” stated Drax’s chief operations officer, Lee Dawes. “Cement production is one of the most carbon-intensive processes in the world and through this partnership, we will be able to help the construction industry cut its carbon emissions in the years ahead,” he added.

“The opportunity to sell large volumes of PFA from Drax power station as part of a long-term JV is another way in which we can realise incremental value from the site whilst helping to reduce carbon emissions,” Dawes continued. “It is an exciting time for Drax as we continue to develop options for long-term investment in the site, including BECCS and a data centre.”

Meanwhile, Nils Jansen, the head of cementitious materials at PML’s parent company, EP Power Minerals, said the agreement positioned his company to become “the leading player in the UK fly ash market for the foreseeable future”.

Drax will share the profits of the joint venture’s sales of SCM. The company estimates that the project could generate incremental adjusted EBITDA of around £5m per year post-2027 until 2046.

Ash from the Drax power station has historically been deposited nearby, at Barlow Mound. Drax said the mound would be retained at its current height along the west and southwest of the site to continue to protect the views of local residents, while the remainder of the mound would be extracted down to surrounding ground levels and then restored.

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ADNOC, OMV advance formation of Borouge Group International

ADNOC and OMV Aktiengesellschaft signed an asset usage agreement for the Borouge 4 (B4) production complex, advancing the duo’s formation of Borouge Group International AG. The formation of Borouge Group International AG, through the combination of Borouge Plc and Borealis, and acquisition of Nova Chemicals, is progressing according to plan,

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Nile adds microsegmentation and native NAC to its secure NaaS platform

Identity is the authentication layer that feeds the NAC replacement. For users and employees, Nile pulls identity from Active Directory, including group and role membership, which maps directly to policy enforcement. Corporate devices can authenticate through RADIUS using certificates, which carry additional device metadata. For wired connections, Nile supports 802.1X

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IDC: Dell leads server market driven by AI infrastructure needs

For calendar year 2025 the market finished growing 80.4% compared to 2024, reaching a yearly record of $444.1 billion dollars revenue. Dell Technologies clearly leads the OEM market with $12.5 billion in total revenue share, accounting for 10% of total sales. IDC attributed this to outstanding growth on accelerated servers.

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Cloud providers seek to shape European sovereignty legislation

Finally, they say, there should be taxpayer-funded investments in cloud and AI infrastructure and support for the European development of key components such as memory and chips and the incorporation of strict environmental sustainability requirements. “It’s important to realize that the proposal is not just about the technical aspects but

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Then & Now: Oil prices, US shale, offshore, and AI—Deborah Byers on what changed since 2017

In this Then & Now episode of the Oil & Gas Journal ReEnterprised podcast, Managing Editor and Content Strategist Mikaila Adams reconnects with Deborah Byers, nonresident fellow at Rice University’s Baker Institute Center for Energy Studies and former EY Americas industry leader, to revisit a set of questions first posed in 2017. In 2017, the industry was emerging from a downturn and recalibrating strategy; today, it faces heightened geopolitical risk, market volatility, and a rapidly evolving technology landscape. The conversation examines how those earlier perspectives have aged—covering oil price bands and the speed of recovery from geopolitical shocks, the role of US shale relative to OPEC in balancing global supply, and the shift from scarcity to economic abundance driven by technology and capital discipline. Adams and Byers also compare the economics and risk profiles of shale and offshore development, including the growing role of Brazil, Guyana, and the Gulf of Mexico, and discuss how infrastructure and regulatory constraints shape market outcomes. The episode further explores where digital transformation—particularly artificial intelligence—is delivering tangible returns across upstream operations, from predictive maintenance and workforce planning to capital project execution. The discussion concludes with insights on consolidation and scale in the Permian basin, the strategic rationale behind recent megamergers, and the industry’s ongoing challenge to attract and retain next‑generation talent through flexibility, technical opportunity, and purpose‑driven work.

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Eni plans tieback of new gas discoveries offshore Libya

Eni North Africa, a unit of Eni SPA, together with Libya’s National Oil Corp., plans to develop two new gas discoveries offshore Libya as tiebacks to existing infrastructure. The gas discoveries were made offshore Libya, about 85 km off the coast in about 650 ft of water. Bahr Essalam South 2 (BESS 2) and Bahr Essalam South 3 (BESS 3), adjacent geological structures, were successfully drilled through the exploration well C1-16/4 and the appraisal well B2-16/4 about 16 km south of Bahr Essalam gas field, which lies about 110 km from the Tripoli coast. Gas-bearing intervals were encountered in both wells within the Metlaoui formation, the main productive reservoir of the area. The acquired data indicate the presence of a high-quality reservoir, with productive capacity confirmed by the well test already carried out on the first well. Preliminary volumetric estimates indicate that the BESS 2 and BESS 3 structures jointly contain more than 1 tcf of gas in place. Their proximity to Bahr Essalam field will enable rapid development through tie-back, the operator said. The gas produced will be supplied to the Libyan domestic market and for export to Italy. Bahr Essalam produces through the Sabratha platform to the Mellitah onshore treatment plant.

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Azule Energy launches first non-associated gas production offshore Angola

Azule Energy has started natural gas production from the New Gas Consortium (NGC)’s Quiluma shallow water field offshore Angola. Start-up of the gas delivery from Quiluma field follows the November 2025 introduction of gas into the onshore gas plant, marking the beginning of production operations. The initial gas export will be 150 MMscfd and will ramp up to 330 MMscfd by yearend, the operator said in a release Mar. 13.  In a separate release Mar. 17, NGC partner TotalEnergies said the startup marks the first development of a non-associated gas field in Angola, noting that the gas produced “will be a stable and important source of gas supply for the Angola LNG plant that is delivering LNG to both the European and Asian markets.” The non-associated gas of NGC Phase 1 will come from Quiluma and Maboqueiro shallow water fields with additional potential related to gas from Blocks 2, 3, and 15/14 areas. An onshore plant will process gas from the fields and connect to the Angola LNG plant, aimed at a reliable feedstock supply to the plant, sited near Soyo in the Zaire province in north Angola. The plant holds a capacity of 400MMscfd of gas and 20,000 b/d of condensates. Azule Energy, a 50-50 joint venture between bp and Eni, is operator of NGC project with 37.4% interest. Partners are TotalEnergies (11.8%), Cabinda Gulf Oil Co., a subsidiary of Chevron (31%), and Sonangol E&P (19.8%).

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Equinor eyes Barents Sea oil province expansion with potential oil discovery tieback

Equinor Energy AS and partners will consider a tie back of a new oil discovery to Johan Castberg field in the Barents Sea, 220 km northwest of Hammerfest. Preliminary discovery volume estimates at the in the Polynya Tubåen prospect are 2.3–3.8 million std cu m of recoverable oil equivalent (14–24 MMboe). Wildcat well 7220/7-5, the 17th exploration well in production license 532, was drilled about 16 km southwest of discovery well 7220/8-1 well by the COSL Prospector rig in 361 m of water, according to the Norwegian Offshore Directorate. The well was drilled to a vertical depth of 1,119 m subsea. It was terminated in the Fruholmen formation from the Upper Triassic. The objective was to prove petroleum in Lower Jurassic reservoir rocks in the Tubåen formation. The well encountered a 26-m gas column and a 26-m oil column in the Tubåen formation in reservoir rocks totaling 39 m, with good to very good reservoir quality. The total thickness in the Tubåen formation is 125 m. The gas-oil contact was encountered at 972 m subsea, and the oil-water contact was encountered at 998 m subsea. The well was not formation-tested, but extensive volumes of data and samples were collected. It will now be permanently plugged. ‘New’ Barents Sea oil province The discovery comes as Equinor aims to increase volumes in the Johan Castberg area—originally estimated at 500–700 million bbl—by an additional 200–500 million bbl, with plans to drill 1-2 exploration wells per year in the region, Equinor said. “With Johan Castberg, we opened a new oil province in the Barents Sea one year ago. It is encouraging that we are now making new discoveries in the area,” said Grete Birgitte Haaland, area director for Exploration and Production North at Equinor. Production at Johan Castberg began in 2025.  In June 2025, the Drivis

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Westcott named Woodside CEO

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US DOE authorizes Venture Global to boost exports from Plaquemines LNG by 13%

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Nvidia overhauls the data center for OpenClaw era

Nvidia’s products for data centers now encompass a full stack with all the pieces, said Sandeep Gupta, executive managing director and head of global strategic alliances at NTT Data. “From a customer perspective, if they believe in an integrated stack, it makes things simple,” Gupta said. The integrated data center cuts complexity and improves efficiency across cooling, networking and storage. “It is driven by the sentiment of an enterprise on how dependent they want to be on one provider versus mix and match,” Gupta said. AI complexity has gone up manifold with multi-agent systems and technologies like OpenClaw, which Huang said is as big a deal as HTML and Linux. Those technologies will generate tokens at an unprecedented pace and strain network, memory and storage simultaneously. AI data also has context, and moving it inefficiently wastes power and cost. A new networking and storage layer is needed to move data intelligently and efficiently. A technology called KV Cache holds the contextual memory necessary for processing agentic AI systems. “It’s going to pound on memory really hard… It’s going to be pounding on the storage system really really hard, which is the reason why we reinvented the storage system,” Huang said. Nvidia’s blueprint turns data centers into one giant AI GPU. It is spearheaded by the GPU known as Rubin and CPU called Vera, which were announced at GTC. Nvidia also slipped in a new inference chip; the Groq LPU has significantly more memory bandwidth than GPUs and is designed for low-latency token generation.

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Nvidia joins push for data centers in space

For example, instead of sending down raw image data, which can take hours, or even days, a satellite can transmit the information that, say, a particular bridge is down, or that a certain road is having issues—actionable information of immediate business value. “AI can also help satellites navigate low earth orbit much more confidently, avoid other satellites, and operate much more autonomously,” says Su. And it can be used for other heavy workloads as well. For example, Kepler Communications is using Jetson Orin in its satellite communication network. That helps the company make its satellites smarter, CEO Mina Mitry said in a statement, “allowing us to intelligently manage and route data across our constellation.” The Jetson Orin is already bringing data center-level compute capability to space, Su says, and, with the new chips, there will be even more real-time capability for the next generation of satellites. According to Gartner analyst Bill Ray, orbital data centers are a waste of time and money. “The rush to develop orbital data centers has reached a period of peak insanity,” he wrote in a recent report. “For all the hype around them, these space-based data centers will not be able to deliver on the promise of useful analysis of terrestrial data for terrestrial applications for decades, and may not ever be able to do so.” But that’s not where today’s use cases are, Su points out. “It is edge computing workloads,” he says. “It’s AI inference for multi-dimensional data for disaster recovery and weather forecasting.”

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Microsoft’s laser-free cable tech promises to slash AI data center power bills in half

The power problem, Microsoft argues, starts with the cables themselves. How MOSAIC works Copper interconnects top out at roughly two meters at high data rates, limiting them to within a single rack. Laser-based fiber optic cables go further but consume more power and are sensitive to temperature and dust, Microsoft said in the post. MOSAIC reaches up to 50 meters while drawing less power than either, the company added. “Imaging fiber looks like a standard fiber, but inside it has thousands of cores,” Paolo Costa, a Microsoft partner research manager and the project’s lead researcher, wrote in the post. “That was the missing piece. We finally had a way to carry thousands of parallel channels in one cable.” MOSAIC is not Microsoft’s only optical networking bet, and it is not the one furthest along. HCF is already in production across Azure regions MOSAIC arrives alongside Hollow Core Fiber (HCF), a complementary technology Microsoft is already deploying globally. HCF carries optical signals through air rather than glass, delivering up to 47% faster data transmission and 33% lower latency than conventional single-mode fiber, according to published research from the University of Southampton cited by Microsoft. Frank Rey, Microsoft’s general manager of Azure Hyperscale Networking, said in the post that the two technologies are complementary — HCF for long-distance inter-datacenter links, MOSAIC for in-facility GPU and server connectivity.

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Beyond the fan: Crossing the liquid cooling rubicon

At 20 kW per rack, the airflow velocity required to maintain safe operating temperatures triggers two failure modes. First, the acoustic vibration becomes severe enough to damage equipment. Organizations learn this lesson the hard way — high-frequency vibration from upgraded CRAC units causing bit errors in high-density Non-Volatile Memory Express (NVMe) storage arrays. The signature is mechanical resonance in drive enclosures. Fans shake storage infrastructure to death. Second, the power required for that airflow becomes self-defeating. At 100 kW densities, nearly 30 percent of the total facility power goes to fans alone — before accounting for compressors and chillers working overtime to cool the air. According to Uptime Institute research, data centers spend an estimated $1.9 to $2.8 million per MW annually on operations, with cooling-related costs consuming nearly $500,000 of that figure. The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) TC 9.9 guidelines governing data center thermal management were written for a 15 kW world. Many organizations now operate so far outside those parameters that the guidelines have become irrelevant. One moment crystallized this reality. A single CRAC unit failed in a training cluster. Within eight minutes, hot-aisle temperatures exceeded 120°F. Monitoring systems triggered automatic throttling on millions of dollars of compute infrastructure. A multi-day processing run crashed and restarted from a checkpoint. Standing in that sweltering aisle watching temperature readouts climb, the conclusion was inescapable: air had carried the industry as far as it could go. Crossing the Rubicon: Cold plates versus rear-door heat exchangers Bringing liquid into a data center is terrifying. Water — or water-adjacent fluids — enters rooms filled with equipment worth tens of millions of dollars. Equipment that fails catastrophically when wet. “Crossing the Rubicon” captures the commitment: once started down this path, there is no returning to the comfortable certainty of

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System-level ‘coopetition’: Why Nvidia’s DGX Rubin NVL8 runs on Intel Xeon 6

Not a strategic alliance Despite working together at the system level, the relationship between the two companies does not amount to a formal strategic alliance. “The Intel–Nvidia dynamic is best understood as system-level coopetition. Long-standing collaboration persists across data center and PC ecosystems, with Intel CPUs paired alongside Nvidia GPUs forming standardized AI server architectures and enabling deeper integration,” said Manish Rawat, semiconductor analyst at TechInsights. However, competition is accelerating structurally. Even though Nvidia dominates the GPU space, the company is also expanding its presence across more layers of the data-center stack. It has been developing its own CPUs, such as the Grace CPU, aimed at tighter integration between compute, memory, and interconnect. The company has also launched Vera CPU, purpose-built for agentic AI at GTC 2026. This reflects Nvidia’s broader approach of building more of the system in-house, spanning both hardware and software, even as it continues to incorporate external components where required. “Nvidia’s push into CPUs (Grace, Vera) and tightly integrated, NVLink-based systems signals a shift toward full-stack ownership spanning compute, networking, and software. This challenges Intel’s traditional dominance in CPUs and system control. In essence, Nvidia is partnering tactically to sustain ecosystem adoption while strategically positioning to displace incumbents and capture greater control of next-generation AI infrastructure,” added Rawat.

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Nvidia announces Vera Rubin platform, signaling a shift to full-stack AI infrastructure

The transition reflects a deeper move from optimizing individual components to engineering entire systems for scalability and efficiency, said Sanchit Vir Gogia, chief analyst at Greyhound Research. “Compute, memory behavior, interconnect bandwidth, and workload orchestration are being engineered together,” Gogia said. “Even physical design choices such as rack modularity, serviceability, and assembly efficiency are now part of performance engineering. Infrastructure is beginning to resemble an appliance at scale, but one that operates at extreme density and complexity.” Industry observers said rack-scale systems, including Nvidia’s NVL72 and open standards such as OCP Open Rack, are enabling more flexible pooling and orchestration of infrastructure resources for AI and machine learning workloads. “I am also seeing other operators are increasingly adopting chip-to-grid strategies, integrating onsite power generation (microgrids, batteries), advanced cooling technologies, and co-packaged optics to effectively manage power spikes, reduce conversion losses, and support rack densities exceeding 100kW,” said Franco Chiam, VP of Cloud, Datacenter, Telecommunication, and Infrastructure Research Group at IDC Asia Pacific. “This collective industry response to adapt to the needs for higher power and thermal demands is further reinforced by leading vendors and hyperscalers aligning around open standards, facilitating scalable, gigawatt-class datacenter deployments,” Chiam added. Networking takes center stage Networking is emerging as a central component of AI infrastructure, as platforms such as Vera Rubin place greater emphasis on how data moves across systems rather than treating connectivity as a supporting layer.

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Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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