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WiSE electrolytes for lithium-ion batteries: a machine learning study
Stage M2CEA Saclay, (91) Essonne, FranceFebruary 3 20256 monthDomain, Specialties: Physical chemistry Keywords: theoretical chemistry, artificial intelligence, machine learning Research Unit: NIMBE / LSDRM For this internship, the trainee will build and apply artificial neural networks able to simulate at atomic scale the structural and dynamic properties of superconcentrated lithium salt electrolytes for lithium-ion batteries. Research focused on aqueous super-concentrated lithium salt electrolytes…
PhD thesis
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Interfaces in super-concentrated aqueous electrolytes: machine learned simulations at the exascale era
LSDRM : Physical chemistry and electrochemistryParis-Saclay Sciences Chimiques: Molécules, Matériaux, Instrumentation et Biosystèmes (2MIB) SaclayImproving the performance of liquid electrolytes is one of today’s major challenges in the field of batteries, with the aim of improving efficiency, safety and economy. Recent advances include… -
Hyperpolarized Xenon NMR to probe the functionality of biological barriers
LSDRM : Medical imagingParis-Saclay Sciences Chimiques: Molécules, Matériaux, Instrumentation et Biosystèmes (2MIB) SaclayOptical pumping of xenon, giving rise to an intense NMR signal, is a specialty of the LSDRM team. Xenon, which is soluble in biological media, has a wide range of chemical shifts, which we use here…