Li2SnO3 as a Cathode Material for Lithium-ion Batteries:Defects, Lithium Ion Diffusion and Dopants

Tin-based oxide Li2SnO3 has attracted considerable interest as a promising cathode material for potential use in rechargeable lithium batteries due to its high- capacity. Static atomistic scale simulations are employed to provide insights into the defect chemistry, doping behaviour and lithium diffusion paths in Li2SnO3. The most favourable intrinsic defect type is Li Frenkel (0.75 eV/defect). The formation of anti-site defect, in which Li and Sn ions exchange their positions is 0.78 eV/defect, very close to the Li Frenkel. The present calculations confirm the cation intermixing found experimentally in Li2SnO3. Long range lithium diffusion paths via vacancy mechanisms were examined and it is confirmed that the lowest activation energy migration path is along the c-axis plane with the overall activation energy of 0.61 eV. Subvalent doping by Al on the Sn site is energetically favourable and is proposed to be an efficient way to increase the Li content in Li2SnO3. The electronic structure calculations show that the introduction of Al will not introduce levels in the band gap

A Neuron-Glial Perspective for Computational Neuroscience

International audienceThere is growing excitement around glial cells, as compelling evidence point to new, previously unimaginable roles for these cells in information processing of the brain, with the potential to affect behavior and higher cognitive functions. Among their many possible functions, glial cells could be involved in practically every aspect of the brain physiology in health and disease. As a result, many investigators in the field welcome the notion of a Neuron-Glial paradigm of brain function, as opposed to Ramon y Cayal's more classical neuronal doctrine which identifies neurons as the prominent, if not the only, cells capable of a signaling role in the brain. The demonstration of a brain-wide Neuron-Glial paradigm however remains elusive and so does the notion of what neuron-glial interactions could be functionally relevant for the brain computational tasks. In this perspective, we present a selection of arguments inspired by available experimental and modeling studies with the aim to provide a biophysical and conceptual platform to computational neuroscience no longer as a mere prerogative of neuronal signaling but rather as the outcome of a complex interaction between neurons and glial cells