Latest news with #DmitryAksyonov
Scoop
10 hours ago
- Automotive
- Scoop
Neural Networks Speed Up Search For Solid-State Battery Materials For Safer Electric Cars With Extended Range
Press Release – Skoltech So far solid-state batteries have not been adopted by carmakers, but EV developers are looking to capitalize on the technology before competitors. The new type of energy storage could improve fire safety and boost EV range by up to 50%. Researchers from Skoltech and AIRI Institute have shown how machine learning can speed up the development of new materials for solid-state lithium-ion batteries. These are an emerging energy storage technology, which could theoretically replace conventional Li-ion batteries in electric vehicles and portable electronics, reducing fire hazards and extending battery life. In the Russian Science Foundation-backed study, published in npj Computational Materials, neural networks proved capable of identifying promising materials for the key component of these advanced batteries — the solid electrolyte — as well as for its protective coatings. Like its conventional counterpart, the solid-state battery incorporates an electrolyte, through which ions carrying the electric charge travel from one electrode to another. While in a conventional battery the electrolyte is a liquid solution, its solid-state analogue, as the name suggests, relies on solid electrolytes, such as ceramics, to conduct lithium ions. So far solid-state batteries have not been adopted by carmakers, but EV developers are looking to capitalize on the technology before competitors. The new type of energy storage could improve fire safety and boost EV range by up to 50%. The problem is that none of the currently available solid electrolytes meets all the technical requirements. So the search for new materials continues. 'We demonstrated that graph neural networks can identify new solid-state battery materials with high ionic mobility and do it orders of magnitude faster than traditional quantum chemistry methods. This could speed up the development of new battery materials, as we showed by predicting a number of protective coatings for solid-state battery electrolytes,' commented the lead author of the study, Artem Dembitskiy, a PhD student of Skoltech's Materials Science and Engineering program, a research intern at Skoltech Energy, and a junior research scientist at AIRI Institute. Study co-author, Assistant Professor Dmitry Aksyonov from Skoltech Energy explained the role of protective coatings: 'The metallic lithium of the anode is a strong reducing agent, so almost all existing electrolytes undergo reduction in contact with it. The cathode material is a strong oxidizing agent. When oxidized or reduced, electrolytes lose their structural integrity, which can degrade performance or even cause a short circuit. You can avoid this by introducing two protective coatings that are stable in contact with the anode and the electrolyte and the cathode and the electrolyte.' Machine learning algorithms make it possible to accelerate the calculation of ionic conductivity, a key property both for electrolytes and for protective coatings. It is among the most computationally challenging characteristics calculated in screening the candidate materials. For protective coatings, the list of properties that are checked at various stages of material selection includes thermodynamic stability, electronic conductivity, electrochemical stability, compatibility with electrode and electrolyte materials, ionic conductivity, and so on. Such screening happens in stages and gradually narrows down the list of perhaps tens of thousands of initial options to just a few materials. The authors of the study used their machine learning-accelerated approach to search for coating materials to protect one of the most promising solid-state battery electrolytes: Li10GeP2S12. The search identified multiple promising coating materials, among them the compounds Li3AlF6 and Li2ZnCl4.
Scoop
11 hours ago
- Science
- Scoop
Neural Networks Speed Up Search For Solid-State Battery Materials For Safer Electric Cars With Extended Range
Researchers from Skoltech and AIRI Institute have shown how machine learning can speed up the development of new materials for solid-state lithium-ion batteries. These are an emerging energy storage technology, which could theoretically replace conventional Li-ion batteries in electric vehicles and portable electronics, reducing fire hazards and extending battery life. In the Russian Science Foundation-backed study, published in npj Computational Materials, neural networks proved capable of identifying promising materials for the key component of these advanced batteries — the solid electrolyte — as well as for its protective coatings. Like its conventional counterpart, the solid-state battery incorporates an electrolyte, through which ions carrying the electric charge travel from one electrode to another. While in a conventional battery the electrolyte is a liquid solution, its solid-state analogue, as the name suggests, relies on solid electrolytes, such as ceramics, to conduct lithium ions. So far solid-state batteries have not been adopted by carmakers, but EV developers are looking to capitalize on the technology before competitors. The new type of energy storage could improve fire safety and boost EV range by up to 50%. The problem is that none of the currently available solid electrolytes meets all the technical requirements. So the search for new materials continues. 'We demonstrated that graph neural networks can identify new solid-state battery materials with high ionic mobility and do it orders of magnitude faster than traditional quantum chemistry methods. This could speed up the development of new battery materials, as we showed by predicting a number of protective coatings for solid-state battery electrolytes,' commented the lead author of the study, Artem Dembitskiy, a PhD student of Skoltech's Materials Science and Engineering program, a research intern at Skoltech Energy, and a junior research scientist at AIRI Institute. Study co-author, Assistant Professor Dmitry Aksyonov from Skoltech Energy explained the role of protective coatings: 'The metallic lithium of the anode is a strong reducing agent, so almost all existing electrolytes undergo reduction in contact with it. The cathode material is a strong oxidizing agent. When oxidized or reduced, electrolytes lose their structural integrity, which can degrade performance or even cause a short circuit. You can avoid this by introducing two protective coatings that are stable in contact with the anode and the electrolyte and the cathode and the electrolyte.' Machine learning algorithms make it possible to accelerate the calculation of ionic conductivity, a key property both for electrolytes and for protective coatings. It is among the most computationally challenging characteristics calculated in screening the candidate materials. For protective coatings, the list of properties that are checked at various stages of material selection includes thermodynamic stability, electronic conductivity, electrochemical stability, compatibility with electrode and electrolyte materials, ionic conductivity, and so on. Such screening happens in stages and gradually narrows down the list of perhaps tens of thousands of initial options to just a few materials. The authors of the study used their machine learning-accelerated approach to search for coating materials to protect one of the most promising solid-state battery electrolytes: Li10GeP2S12. The search identified multiple promising coating materials, among them the compounds Li3AlF6 and Li2ZnCl4.
Yahoo
21-04-2025
- Science
- Yahoo
Scientists make critical discovery after zapping next-gen batteries with X-rays: 'An example of great synergy'
Russian researchers may have saved other battery scientists some time by ruling out at least one cause of lithium-rich cathode degradation. It seems that oxygen gas molecules that had been blamed for cell performance problems were formed by the X-ray scans that found them, according to the findings. The discovery happened at the Skolkovo Institute of Science and Technology, or Skoltech, with aid from international labs. "Thankfully, our latest study relegates the molecular oxygen hypothesis to history," assistant professor Dmitry Aksyonov said in a news release. He co-authored the report. "By examining the data from major X-ray scattering experiments, we have demonstrated that the O2 molecules trapped in the cathode material and supposedly responsible for its worsening performance are likely the artifact of the experiment." When batteries operate, ions move between the anode and cathode through the electrolyte. Experts in labs around the world are trying to find cheaper, more planet-friendly parts while improving performance. As a result, substances, including potassium, silicon, and sodium, are being tapped for various types of packs. Nickel-manganese-cobalt, or NMC, cathodes are among the promising components being studied. Skoltech said that the electrode could provide for 30% more energy storage, a boon for electric vehicles and other battery-reliant tech if the bugs are worked out. Success is vital to advancing the transition to a cleaner energy system and eliminating heat-trapping air pollution, which is impacting even our food system, according to a farm production and rising temperature study published by Wiley. Now, experts examining NMC cathodes can cross oxygen off the list of culprits behind voltage fade and capacity drop. The findings "suggest that the issue of … deterioration be approached from a different angle," per the release. It's good news, because the oxygen is entrenched after forming, making it tough to mitigate. "Stabilizing cathode materials … will be easier than if the molecular oxygen hypothesis had proved right," the release stated. Should the U.S. invest more in battery innovations? Absolutely Depends on the project We're investing enough We should invest less Click your choice to see results and speak your mind. For their part, lithium-ion batteries are already charging faster than ever before. They can provide hundreds of miles in about 15 minutes if using a fast hookup, such as one of Tesla's 60,000-plus Superchargers. They are now available to most rides with an adapter. And the U.S. Department of Energy reported that the median EV range increased to 283 miles for model year 2024. What's more, costs are expected to drop. Goldman Sachs estimated that pack prices could plummet by 50% next year thanks to better tech, cheaper parts, and more recycling. It's a great time to switch, too, as tax breaks worth $4,000 and $7,500 for used and new EVs remain available. That's in addition to the $1,500 you can bank annually in gas and maintenance costs, and the thousands of pounds of air pollution the DOE estimated will be prevented when parking your gas car. At Skoltech, the team credited modeling experiments — originating from across the continent at the Collège de France and University of Montpellier — for making the cathode findings possible. Even better batteries could soon be a result. "This study is an example of great synergy between experiments, theory, and computer modeling," research scientist Andrey Geondzhian said. Join our free newsletter for weekly updates on the latest innovations improving our lives and shaping our future, and don't miss this cool list of easy ways to help yourself while helping the planet.
