Phase stability in the Fe–Ni system: Investigation by first-principles calculations and atomistic simulations

By Yuri Mishin, Michael J. Mehl, D. Papaconstantopoulos. 2005

308 citations recorded by the source corpus.

Subfields: Atmospheric Science, Atomic and Molecular Physics, and Optics, Condensed Matter Physics

View Paper: https://www.semanticscholar.org/paper/025834c7c3b65696a980a014da141840e8b47acd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. G. P. P. Pun
2. Yuri Mishin

In Atomic and Molecular Physics, and Optics

1. Yuri Mishin
2. G. P. P. Pun
3. Rohit Batra
4. Rampi Ramprasad

In Condensed Matter Physics

1. G. P. P. Pun
2. Yuri Mishin

Citations in the corpus

• Machine-Learning Interatomic Potentials for Materials Science (2021, methodology): “For example, the embedded-atom method (EAM) [4, 5, 48], the modified EAM (MEAM) [49], and the angular-dependent potential (ADP) [50] are specifically designed for metallic systems.”
• Physically informed artificial neural networks for atomistic modeling of materials (2018, methodology): “Several functional forms of interatomic potentials have been developed over the years, including the embedded-atom method (EAM) [1–3], the modified EAM (MEAM) [4], the angular-dependent potentials [5], the charge-optimized many-body potentials [6], reactive bond-order potentials [7–9], and reactive ”