450 citations · 615 across the 5 of their papers we have counts for
5 papers
Calculations of Real-System Nanoparticles Using Universal Neural Network Potential PFP
Gerardo Valadez Huerta, Yusuke Nanba, Iori Kurata +4
It is essential to explore the stability and activity of real-system nanoparticles theoretically. While applications of theoretical methods for this purpose can be found in literat…
Towards Universal Neural Network Potential for Material Discovery Applicable to Arbitrary Combination of 45 Elements
So Takamoto, Chikashi Shinagawa, Daisuke Motoki +19
Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be p…
TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxations
So Takamoto, Satoshi Izumi, Ju Li
A universal interatomic potential for an arbitrary set of chemical elements is urgently needed in computational materials science. Graph convolution neural network (GCN) has rich e…
Elucidation of the atomic-scale mechanism of the anisotropic oxidation rate of 4H-SiC between the () Si-face and () C-face by using a new Si-O-C interatomic potential
So Takamoto, Takahiro Yamasaki, Takahisa Ohno +3
Silicon carbide (SiC) is an attractive semiconductor material for applications in power electronic devices. However, fabrication of a high-quality SiC/SiO interface has been…
Atomistic mechanism of graphene growth on SiC substrate: Large-scale molecular dynamics simulation based on a new charge-transfer bond-order type potential
So Takamoto, Takahiro Yamasaki, Jun Nara +4
Thermal decomposition of silicon carbide is a promising approach for the fabrication of graphene. However, the atomistic growth mechanism of graphene remains unclear. This paper de…