Publications (12)
Comparative Computational Study of the Energetics of Li, Na, and Mg Storage in Amorphous and Crystalline Silicon
Fleur Legrain, Oleksandr I. Malyi, Sergei Manzhos
To assess the potential of amorphous Si (a-Si) as an anode for Li, Na, and Mg-ion batteries, the energetics of Li, Na, and Mg atoms in a-Si are computed from first-principles and c…
The AFLOW Fleet for Materials Discovery
Cormac Toher, Corey Oses, David Hicks +48
The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the d…
AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
Eric Gossett, Cormac Toher, Corey Oses +8
Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis. As a result, a p…
Amorphous carbon a promising material for sodium ion battery anodes: a first principles study
Fleur Legrain, Konstantinos Kotsis, Sergei Manzhos
We present a comparative ab initio computational study of sodium and lithium storage in amorphous (glassy) carbon (a-C) vs. graphite. Amorphous structures are obtained by fitting s…
Aluminum doping improves the energetics of lithium, sodium, and magnesium storage in silicon
Fleur Legrain, Sergei Manzhos
While Si is an effective insertion type anode for Li-ion batteries, crystalline Si has been shown to be unsuitable for Na and Mg storage due, in particular, to insufficient binding…
Highly Accurate Local Pseudopotentials of Li, Na, and Mg for Orbital Free Density Functional Theory
Fleur Legrain, Sergei Manzhos
We present a method to make highly accurate pseudopotentials for use with orbital-free density functional theory (OF-DFT) with given exchange-correlation and kinetic energy functio…