Artificial intelligence is a double-edged sword for the energy sector. The rapid buildout of data centers to support widespread integration of large language models in virtually every economic sector imaginable, from our energy grids to your electric toothbrush – yes, really – is pushing energy demand growth projections to unprecedented levels, threatening to far outpace energy capacity additions and imperil energy security on a global scale. On the other hand, artificial intelligence holds enormous promise for improving energy efficiency in a wide range of systems and may hold the key to unlocking next-gen clean energy methods and technologies that could be integral to enabling feasible decarbonization pathways.In the clean energy sector, artificial intelligence is being used to improve forecasting models for more sophisticated and accurate predictions of energy supply and demand, leading to greater grid stability at a time when our electricity grids have never been more stressed. Researchers are also increasingly using large language models to conduct "needle in a haystack" type inquiries to find the best methods and materials for certain use cases, accomplishing in months what would take a whole team of scientists years to achieve through trial and error methodologies.“Finding new materials, catalysts or processes that can produce stuff more efficiently is the sort of ‘’needle in a haystack’ problem that AI is ideally suited to,” the Financial Times reported last year in an article musing about “How AI might save more energy than it soaks up.”Set OilPrice.com as a preferred source in Google here.In China, for example, scientists used large language models to identify a new molecule, lithium trifluoromethanesulfinate (LiSO2CF3), capable of replenishing lithium ions in dead electric vehicle batteries for thousands of recharge cycles, significantly extending their lifespan. “We had no idea what kinds of molecules could do that job or what their chemical structures would be, so we used machine learning to help us,” Chihao Zhao, part of the research team at Fudan University, was quoted by Scientific American last year.In nuclear fusion research, artificial intelligence is coming in handy for rapidly modelling how different materials will stand up to the extreme temperatures involved in creating and maintaining plasma, an integral component of the fusion process. The scientists at the Ames National Laboratory in Ames, Iowa who have created the modelling tool, called DuctGPT, say that the use of AI has slashed a monthslong process down to just hours of computation. “Now when you ask it, ‘I want to design a material for fusion that has all x, y, z properties that are critical for use in fusion reactors. Tell me the combination of elements which satisfy the criteria,’ it will give you those combinations of elements with properties,” Ames Lab Scientist Prashant Singh told Interesting Engineering.Just this month, researchers at University of Toronto Engineering have announced that they used large language models to successfully develop six new metal alloys that could transform the functionality and durability of extreme environments including jet engines and nuclear power plants. The AI-powered system identified all six alloys in just a few weeks, an incredible feat compared to traditional scientific methods.“There’s enormous demand for materials that can stand up to huge swings of temperature and pressure, such as what you would find inside a jet engine or in the steam generators inside nuclear power plants, anywhere conventional steel just can’t survive,” Yu Zou, who led the project, told Interesting Engineering.These breakthroughs, and the speed that they are being achieved in, could be transformative for the deployment of next-gen clean energy. By slashing research timelines and finding materials that improve the performance and durability of clean energy infrastructure, experimental technologies that would have otherwise been prohibitively expensive to design, test, and develop can now be made scalable and commercially viable. And the timing could not be better, as we draw closer to major global decarbonization deadlines.By Haley Zaremba for Oilprice.comLNG Importers Seek Lower Qatar and UAE Prices as War Upends DealsIndia’s Fuel Exports Set to Soar in July as Refining Margins JumpBrent Breaks $96 as U.S. Strikes Iran for 12th Consecutive Night