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by exploiting foundational machine-learning potentials such as MACE, SevenNet, or Orb-V3. The predictions will then be progressively refined and verified by DFT and, ultimately, tested experimentally
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technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in
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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 2 months ago
solution for deploying accessible embedded AI-based real-time audio DSP systems will be explored. Smartphones provide a large amount of computational power (including AI accelerators in some recent models