Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Hattori, Shinnosuke"'
Autor:
Zhu, Qiang, Hattori, Shinnosuke
With advancements in computational molecular modeling and powerful structure search methods, it is now possible to systematically screen crystal structures for small organic molecules. In this context, we introduce the Python package High-throughput
Externí odkaz:
http://arxiv.org/abs/2408.08843
Autor:
Hattori, Shinnosuke, Zhu, Qiang
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. Specifically, we developed a strategy to collect training configurat
Externí odkaz:
http://arxiv.org/abs/2404.11587
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 thermal conductivity using the homogeneous non-equilibrium molecular
Externí odkaz:
http://arxiv.org/abs/2403.14130
Non-equilibrium molecular dynamics (NEMD) techniques are widely used for investigating lattice thermal conductivity. Recently, machine learning force fields (MLFFs) have emerged as a promising approach to enhance the precision in NEMD simulations. Th
Externí odkaz:
http://arxiv.org/abs/2309.11026
Autor:
Ibayashi, Hikaru, Razakh, Taufeq Mohammed, Yang, Liqiu, Linker, Thomas, Olguin, Marco, Hattori, Shinnosuke, Luo, Ye, Kalia, Rajiv K., Nakano, Aiichiro, Nomura, Ken-ichi, Vashishta, Priya
Neural-network quantum molecular dynamics (NNQMD) simulations based on machine learning are revolutionizing atomistic simulations of materials by providing quantum-mechanical accuracy but orders-of-magnitude faster, illustrated by ACM Gordon Bell pri
Externí odkaz:
http://arxiv.org/abs/2303.08169
In recent years, certain molecular crystals have been reported to possess surprising flexibility by undergoing significant elastic or plastic deformation in response to mechanical loads. However, despite this experimental evidence, there currently ex
Externí odkaz:
http://arxiv.org/abs/2301.00307
Publikováno v:
Cryst. Growth Des. 2022, XXXX, XXX, XXX-XXX
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 short contact) from the centered molecule into a unit sphere according
Externí odkaz:
http://arxiv.org/abs/2207.12548
Akademický článek
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Akademický článek
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Autor:
Irie, Ayu, Aditya, Anikeya, Nomura, Ken-ichi, Fukushima, Shogo, Hattori, Shinnosuke, Kalia, Rajiv K., Nakano, Aiichiro, Rodin, Vadim, Shimojo, Fuyuki, Tomiya, Shigetaka, Vashishta, Priya
Publikováno v:
Journal of Physical Chemistry C; 9/26/2024, Vol. 128 Issue 38, p16172-16178, 7p
