Publications

List of publications in which nap was used. Let us know if you want to add your publications in which nap was used.

• K. Gocho, M. Hamai, N. Tanibata, H. Takeda, M. Nakayama, M. Karasuyama, and R. Kobayashi, “Causal Analysis of Factors for Li Ionic Conductivity in Olivine-Type LiMXO4 Materials Using LiNGAM”, J. Phys. Chem. C, xxx, xxx-xxx (2025)
• N. Tanibata, S. Aizu, M. Koga, H. Takeda, R. Kobayashi, and M. Nakayama, “Guidelines for designing high-deformability materials for all-solid-state lithium-ion batteries”, Journal of Materials Chemistry A, 12, 15601-15607 (2024)
• R. Kobayashi, S. Takemoto, R. Ito, "Influence of nano-crystallization on Li-ion conductivity in glass Li3PS4: a molecular dynamics study", Journal of Solid State Electrochemistry, 28, 4389-4399 (2024)
• Koki Matsunoshita, Yudai Yamaguchi, Masato Hamaie, Motoki Horibe, Naoto Tanibata, Hayami Takeda, Masanobu Nakayama, Masayuki Karasuyama and Ryo Kobayashi, “Optimization of Force-field Potential parameters using conditional variational autoencoder”, Science and Technology of Advanced Materials: Methods, 0, 2253713 (2023)
• Shin Aizu, Shuta Takimoto, Naoto Tanibata, Hayami Takeda, Masanobu Nakayama, Ryo Kobayashi, “Screening chloride Li-ion conductors using high-throughput force-field molecular dynamics”, Journal of the American Ceramic Society, 106, 3035-3044 (2023)
• Kobayashi, R., Nakano, K. & Nakayama, M. Non-equilibrium molecular dynamics study on atomistic origin of grain boundary resistivity in NASICON-type Li-ion conductor. Acta Mater. 226, 117596 (2022)
• Nakano, K. et al. Molecular Dynamics Simulation of Li-Ion Conduction at Grain Boundaries in NASICON-Type LiZr2(PO4)3 Solid Electrolytes. J. Phys. Chem. C 125, 23604–23612 (2021)
• Yang, Z. et al. Exploring the diffusion mechanism of Li ions in different modulated arrangements of La(1-X)/3LixNbO3 with fitted force fields obtained via a metaheuristic algorithm. Solid State Ionics 366-367, 115662 (2021)
• Kobayashi, R. nap: A molecular dynamics package with parameter-optimization programs for classical and machine-learning potentials. J. Open Source Softw. 6, 2768 (2021)
• Kobayashi, R., Miyaji, Y., Nakano, K. & Nakayama, M., High-throughput production of force-fields for solid-state electrolyte materials. APL Materials 8, 081111 (2020)
• Nakano, K. et al. Exhaustive and informatics-aided search for fast Li-ion conductor with NASICON-type structure using material simulation and Bayesian optimization Exhaustive and informatics-aided search for fast Li-ion conductor with NASICON-type structure using material. APL Materials 041112, 041112 (2020)
• Kobayashi, R., Giofré, D., Junge, T., Ceriotti, M. & Curtin, W. A. Neural network potential for Al-Mg-Si alloys. Physical Review Materials 1, 53604--53611 (2017)
• Kobayashi, R., Hattori, T., Tamura, T. & Ogata, S. A molecular dynamics study on bubble growth in tungsten under helium irradiation. J. Nucl. Mater. 463, 1071--1074 (2015)
• Kobayashi, R., Ohba, N., Tamura, T. & Ogata, S. A Monte Carlo study of host-material deformation effect on Li migration in graphite. J. Phys. Soc. Jpn. 82, (2013)
• Kobayashi, R., Nakamura, T. & Ogata, S. A Coupled Molecular Dynamics/Coarse-Grained-Particle Method for Dynamic Simulation of Crack Growth at Finite Temperatures. Mater. Trans. 52, 1603--1610 (2011)