8 citations · 29 across the 10 of their papers we have counts for
10 papers
Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices
Taufeq Mohammed Razakh, Thomas Linker, Ye Luo +12
Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electro…
Beyond Scaling: Chemical Intuition as Emergent Ability of Universal Machine Learning Interatomic Potentials
Shinnosuke Hattori, Kohei Shimamura, Aiichiro Nakano +3
Machine Learning Interatomic Potentials (MLIPs) have successfully demonstrated scaling behavior, i.e. the power-law improvement in training performance, however the emergence of no…
Allegro-FM: Towards Equivariant Foundation Model for Exascale Molecular Dynamics Simulations
Ken-ichi Nomura, Shinnosuke Hattori, Satoshi Ohmura +6
We present a foundation model for exascale molecular dynamics simulations by leveraging an E(3) equivariant network architecture (Allegro) and a set of large-scale organic and inor…
Automated High-throughput Organic Crystal Structure Prediction via Population-based Sampling
Qiang Zhu, Shinnosuke Hattori
With advancements in computational molecular modeling and powerful structure search methods, it is now possible to systematically screen crystal structures for small organic molecu…
Study of Entropy-Driven Polymorphic Stability for Aspirin Using Accurate Neural Network Interatomic Potential
Shinnosuke Hattori, Qiang Zhu
In this study, we present a systematic computational investigation to analyze the long debated crystal stability of two well known aspirin polymorphs, labeled as Form I and Form II…
Thermal Conductivity Calculation using Homogeneous Non-equilibrium Molecular Dynamics Simulation with Allegro
Kohei Shimamura, Shinnosuke Hattori, Ken-ichi Nomura +2
In this study, we derive the heat flux formula for the Allegro model, one of machine-learning interatomic potentials using the equivariant deep neural network, to calculate lattice…
Atomic cluster expansion force field based thermal property material design with density functional theory level accuracy in non-equilibrium molecular dynamics calculations over sub-million atoms
Takumi Araki, Shinnosuke Hattori, Toshio Nishi +1
Non-equilibrium molecular dynamics (NEMD) techniques are widely used for investigating lattice thermal conductivity. Recently, machine learning force fields (MLFFs) have emerged as…
Allegro-Legato: Scalable, Fast, and Robust Neural-Network Quantum Molecular Dynamics via Sharpness-Aware Minimization
Hikaru Ibayashi, Taufeq Mohammed Razakh, Liqiu Yang +8
Neural-network quantum molecular dynamics (NNQMD) simulations based on machine learning are revolutionizing atomistic simulations of materials by providing quantum-mechanical accur…
Bending Deformation Driven by Molecular Rotation
Pedro A. Santos-Florez, Shinnosuke Hattori, Qiang Zhu
In recent years, certain molecular crystals have been reported to possess surprising flexibility by undergoing significant elastic or plastic deformation in response to mechanical…
Quantification of Crystal Packing Similarity from Spherical Harmonic Transform
Qiang Zhu, Weilun Tang, Shinnosuke Hattori
In this work, we present a new computational approach to characterize and classify molecular packing in the solid states. The key idea is to project each neighboring molecule (or s…