In recent decades, researchers have devoted tremendous effort into the rational design and controlled synthesis of metal nanomaterials with well‐defined size, morphology …
Machine learning of the quantitative relationship between local environment descriptors and the potential energy surface of a system of atoms has emerged as a new frontier in the …
WM Choi, YH Jo, SS Sohn, S Lee, BJ Lee - Npj Computational Materials, 2018 - nature.com
Although high-entropy alloys (HEAs) are attracting interest, the physical metallurgical mechanisms related to their properties have mostly not been clarified, and this limits wider …
The vacancy production behavior for a broad range of incident ion-target combinations were examined by using both the full cascade (FC) and quick calculation of damage (QC) options …
Bimetallics are emerging as important materials that often exhibit distinct chemical properties from monometallics. However, there is limited access to homogeneously alloyed …
Highly optimized embedded-atom-method (EAM) potentials have been developed for 14 face-centered-cubic (fcc) elements across the periodic table. The potentials were developed …
Covalent organic frameworks (COFs) are an emerging material family having several potential applications. Their porous framework and redox-active centers enable gas/ion …
A neural network model is developed to search vast compositional space of high entropy alloys (HEAs). The model predicts the mechanical properties of HEAs better than several …
Phase transitions in nickel-titanium shape-memory alloys are investigated by means of atomistic simulations. A second nearest-neighbor modified embedded-atom method …