1.1k citations · 8.5k across the 156 of their papers we have counts for
159 papers
Machine-Learning-Assisted Construction of Ternary Convex Hull Diagrams
Hugo Rossignol, Michail Minotakis, Matteo Cobelli +1
In the search for novel intermetallic ternary alloys, much of the effort goes into performing a large number of ab-initio calculations covering a wide range of compositions and str…
Machine Learning Predictions of High-Curie-Temperature Materials
Joshua F. Belot, Valentin Taufour, Stefano Sanvito +1
Technologies that function at room temperature often require magnets with a high Curie temperature, , and can be improved with better materials. Discovering magnetic…
Machine-Learning Surrogate Model for Accelerating the Search of Stable Ternary Alloys
Michael Minotakis, Hugo Rossignol, Matteo Cobelli +1
The prediction of phase diagrams in the search for new phases is a complex and computationally intensive task. Density functional theory provides, in many situations, the desired a…
A theoretical perspective on the modification of the magnetocrystalline anisotropy at molecule-cobalt interfaces
Anita Halder, Sumanta Bhandary, David D. O'Regan +2
We study the modification of the magnetocrystalline anisotropy (MCA) of Co slabs induced by several different conjugated molecular overlayers, i.e., benzene, cyclooctatetraene, nap…
3D-imaging of Printed Nanostructured Networks using High-resolution FIB-SEM Nanotomography
Cian Gabbett, Luke Doolan, Kevin Synnatschke +10
Networks of solution-processed nanomaterials are important for multiple applications in electronics, sensing and energy storage/generation. While it is known that network morpholog…
Linear Jacobi-Legendre expansion of the charge density for machine learning-accelerated electronic structure calculations
Bruno Focassio, Michelangelo Domina, Urvesh Patil +2
Kohn-Sham density functional theory (KS-DFT) is a powerful method to obtain key materials' properties, but the iterative solution of the KS equations is a numerically intensive tas…