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Journal Articles

Machine learning molecular dynamics reveals the structural origin of the first sharp diffraction peak in high-density silica glasses

Kobayashi, Keita; Okumura, Masahiko; Nakamura, Hiroki; Itakura, Mitsuhiro; Machida, Masahiko; Urata, Shingo*; Suzuya, Kentaro

Scientific Reports (Internet), 13, p.18721_1 - 18721_12, 2023/11

The first sharp peak diffraction peak (FSDP) in the structure factor of amorphous materials is thought to reflect the medium-range order structure in amorphous materials, and the structural origin of the FSDP has been a subject of ongoing debate. In this study, we employed machine learning molecular dynamics (MLMD) with nearly first-principles calculation accuracy to investigate the structural origin of the FSDP in high-density silica glass. First, we successfully reproduced various experimental data of high-density silica glass using MLMD. Furthermore, we revealed that the development (or reduction) of the FSDP in high-density silica glass is characterized by the deformation behavior of ring structures in Si-O covalent bond networks under compression.

Journal Articles

Mineralogical factors causing underestimation of $$K$$$$_{rm d}$$ values calculated from radiocesium interception potential

Uno, Koichiro*; Nakao, Atsushi*; Okumura, Masahiko; Yamaguchi, Akiko; Kogure, Toshihiro*; Yanai, Junta*

Nihon Dojo Hiryo Gaku Zasshi, 94(5), p.376 - 384, 2023/10

Radiocesium interception potential (RIP) has been widely used as a quantitative indicator of cesium (Cs) adsorption capacity of soil, but it has been found that RIP does not always correlate with the distribution coefficient ($$K$$$$_{rm d}$$) of Cs in the actual environment. In order to clarify the cause of this discrepancy, we measured Kd using more realistic solutions, compared it with RIP, and evaluated the mineral structure. As a result, it was found that the concentration of competing cations, such as potassium and ammonium ions, and the structural change of the mineral itself are important.

Journal Articles

R&D of digital technology on inverse estimation of radioactive source distributions and related source countermeasures; R&D status of digital platform including 3D-ADRES-indoor

Machida, Masahiko; Yamada, Susumu; Kim, M.; Okumura, Masahiko; Miyamura, Hiroko; Shikaze, Yoshiaki; Sato, Tomoki*; Numata, Yoshiaki*; Tobita, Yasuhiro*; Yamaguchi, Takashi; et al.

RIST News, (69), p.2 - 18, 2023/09

The contamination of radioactive materials leaked from the reactor has resulted in numerous hot spots in the Fukushima Daiichi Nuclear Power Station (1F) building, posing obstacles to its decommissioning. In order to solve this problem, JAEA has conducted research and development of the digital technique for inverse estimation of radiation source distribution and countermeasures against the estimated source in virtual space for two years from 2021 based on the subsidy program "Project of Decommissioning and Contaminated Water Management" performed by the funds from the Ministry of Economy, Trade and Industry. In this article, we introduce the results of the project and the plan of the renewal project started in April 2023. For the former project, we report the derivative method for LASSO method considering the complex structure inside the building and the character of the source and show the result of the inverse estimation using the method in the real reactor building. Moreover, we explain the platform software "3D-ADRES-Indoor" which integrates these achievements. Finally, we introduce the plan of the latter project.

Journal Articles

Dynamic interaction between dislocations and obstacles in BCC iron based on atomic potentials derived using neural networks

Mori, Hideki*; Tsuru, Tomohito; Okumura, Masahiko; Matsunaka, Daisuke*; Shiihara, Yoshinori*; Itakura, Mitsuhiro

Physical Review Materials (Internet), 7(6), p.063605_1 - 063605_8, 2023/06

The introduction of obstacles (e.g., precipitates) for controlling dislocation motion in molecular structures is a prevalent method for designing the mechanical strength of metals. Owing to the nanoscale size of the dislocation core ($$leq$$ 1 nm), atomic modeling is required to investigate the interactions between the dislocation and obstacles. However, conventional empirical potentials are not adequately accurate, in contrast to the calculations based on density functional theory (DFT). Therefore, the atomic-level details of the interactions between the dislocations and obstacles remain unclarified. To this end, this study applied an artificial neural network (ANN) framework to construct an atomic potential by leveraging the high accuracy of DFT. Using the constructed ANN potential, we investigated the dynamic interaction between the $$(a_0/2){110}$$ edge dislocation and obstacles in BCC iron. When the dislocation crossed the void, an ultrasmooth and symmetric half-loop was observed for the bowing-out dislocation. Except for the screw dislocation, the Peierls stress of all the dislocations predicted using the ANN was less than 100 MPa. More importantly, the results confirmed the formation of an Orowan loop in the interaction between a rigid sphere and dislocation. Furthermore, we discovered a phenomenon in which the Orowan loop disintegrated into two small loops during its interaction with the rigid sphere and dislocation.

Journal Articles

Machine learning molecular dynamics simulations for evaluation of high-temperature properties of nuclear fuel materials

Kobayashi, Keita; Nakamura, Hiroki; Itakura, Mitsuhiro; Machida, Masahiko; Okumura, Masahiko

Materia, 62(3), p.175 - 181, 2023/03

no abstracts in English

Journal Articles

Machine learning potentials of kaolinite based on the potential energy surfaces of GGA and meta-GGA density functional theory

Kobayashi, Keita; Yamaguchi, Akiko; Okumura, Masahiko

Applied Clay Science, 228, p.106596_1 - 106596_11, 2022/10

 Times Cited Count:4 Percentile:74.7(Chemistry, Physical)

no abstracts in English

Journal Articles

Extended X-ray absorption fine structure spectroscopy measurements and ${it ab initio}$ molecular dynamics simulations reveal the hydration structure of the radium(II) ion

Yamaguchi, Akiko; Nagata, Kojiro*; Kobayashi, Keita; Tanaka, Kazuya; Kobayashi, Toru; Tanida, Hajime; Shimojo, Kojiro; Sekiguchi, Tetsuhiro; Kaneta, Yui; Matsuda, Shohei; et al.

iScience (Internet), 25(8), p.104763_1 - 104763_12, 2022/08

 Times Cited Count:3 Percentile:49.98(Multidisciplinary Sciences)

no abstracts in English

Journal Articles

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials; Case study of thorium dioxide

Kobayashi, Keita; Okumura, Masahiko; Nakamura, Hiroki; Itakura, Mitsuhiro; Machida, Masahiko; Cooper, M. W. D.*

Scientific Reports (Internet), 12(1), p.9808_1 - 9808_11, 2022/06

 Times Cited Count:1 Percentile:71.95(Multidisciplinary Sciences)

no abstracts in English

Journal Articles

Investigation of hydration and adsorption structures on clay minerals of radium by EXAFS

Yamaguchi, Akiko; Nagata, Kojiro*; Tanaka, Kazuya; Kobayashi, Keita; Kobayashi, Toru; Shimojo, Kojiro; Tanida, Hajime; Sekiguchi, Tetsuhiro; Kaneta, Yui; Matsuda, Shohei; et al.

Hosha Kagaku, (45), p.28 - 30, 2022/03

no abstracts in English

Journal Articles

Construction of machine-learning Zr interatomic potentials for identifying the formation process of c-type dislocation loops

Okita, Taira*; Terayama, Satoshi*; Tsugawa, Kiyoto*; Kobayashi, Keita; Okumura, Masahiko; Itakura, Mitsuhiro; Suzuki, Katsuyuki*

Computational Materials Science, 202, p.110865_1 - 110865_9, 2022/02

 Times Cited Count:5 Percentile:51.6(Materials Science, Multidisciplinary)

Journal Articles

Computational science studies on radiocesium adsorption on clay minerals

Okumura, Masahiko

Chikyu Kagaku, 55(4), p.110 - 121, 2021/12

no abstracts in English

Journal Articles

Hydration structures of barium ions; ${it Ab initio}$ molecular dynamics simulations using the SCAN meta-GGA density functional and EXAFS spectroscopy studies

Yamaguchi, Akiko; Kobayashi, Keita; Takahashi, Yoshio*; Machida, Masahiko; Okumura, Masahiko

Chemical Physics Letters, 780, p.138945_1 - 138945_5, 2021/10

 Times Cited Count:4 Percentile:39.7(Chemistry, Physical)

no abstracts in English

Journal Articles

Machine learning potentials for tobermorite minerals

Kobayashi, Keita; Nakamura, Hiroki; Yamaguchi, Akiko; Itakura, Mitsuhiro; Machida, Masahiko; Okumura, Masahiko

Computational Materials Science, 188, p.110173_1 - 110173_14, 2021/02

 Times Cited Count:12 Percentile:73.52(Materials Science, Multidisciplinary)

no abstracts in English

JAEA Reports

Status of study of long-term assessment of transport of radioactive contaminants in the environment of Fukushima (FY2018) (Translated document)

Nagao, Fumiya; Niizato, Tadafumi; Sasaki, Yoshito; Ito, Satomi; Watanabe, Takayoshi; Dohi, Terumi; Nakanishi, Takahiro; Sakuma, Kazuyuki; Hagiwara, Hiroki; Funaki, Hironori; et al.

JAEA-Research 2020-007, 249 Pages, 2020/10

JAEA-Research-2020-007.pdf:15.83MB

The accident of the Fukushima Daiichi Nuclear Power Station, Tokyo Electric Power Company Holdings, Inc. occurred due to the Great East Japan Earthquake, Sanriku offshore earthquake, of 9.0 magnitude and the accompanying tsunami. As a result, large amount of radioactive materials was released into the environment. Under these circumstances, Japan Atomic Energy Agency (JAEA) has been conducting "Long-term Assessment of Transport of Radioactive Contaminants in the Environment of Fukushima" concerning radioactive materials released in environment, especially migration behavior of radioactive cesium since November 2012. This report is a summary of the research results that have been obtained in environmental dynamics research conducted by JAEA in Fukushima Prefecture.

Journal Articles

Quantitative evaluation of effects of isomorphic substitutions on delamination energies of clay minerals

Yamaguchi, Akiko; Asano, Ikumi*; Kitagawa, Yuri*; Meng, C.*; Nakao, Atsushi*; Okumura, Masahiko

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.127 - 130, 2020/10

no abstracts in English

Journal Articles

Self-learning hybrid Monte Carlo; A First-principles approach

Nagai, Yuki; Okumura, Masahiko; Kobayashi, Keita*; Shiga, Motoyuki

Physical Review B, 102(4), p.041124_1 - 041124_6, 2020/07

 Times Cited Count:11 Percentile:65.53(Materials Science, Multidisciplinary)

no abstracts in English

Journal Articles

Self-learning Monte Carlo method with Behler-Parrinello neural networks

Nagai, Yuki; Okumura, Masahiko; Tanaka, Akinori*

Physical Review B, 101(11), p.115111_1 - 115111_12, 2020/03

 Times Cited Count:15 Percentile:74.57(Materials Science, Multidisciplinary)

no abstracts in English

Journal Articles

Recent status and future issues of molecular modeling studies for clay and fungi adsorbing cesium

Suno, Hiroya; Okumura, Masahiko; Machida, Masahiko

Jiban Kogakkai-Shi, 67(10), p.34 - 35, 2019/10

no abstracts in English

JAEA Reports

Status of study of long-term assessment of transport of radioactive contaminants in the environment of Fukushima (FY2018)

Nagao, Fumiya; Niizato, Tadafumi; Sasaki, Yoshito; Ito, Satomi; Watanabe, Takayoshi; Dohi, Terumi; Nakanishi, Takahiro; Sakuma, Kazuyuki; Hagiwara, Hiroki; Funaki, Hironori; et al.

JAEA-Research 2019-002, 235 Pages, 2019/08

JAEA-Research-2019-002.pdf:21.04MB

The accident of the Fukushima Daiichi Nuclear Power Station (hereinafter referred to 1F), Tokyo Electric Power Company Holdings, Inc. occurred due to the Great East Japan Earthquake, Sanriku offshore earthquake, of 9.0 magnitude and the accompanying tsunami. As a result, large amount of radioactive materials was released into the environment. Under these circumstances, JAEA has been conducting Long-term Environmental Dynamics Research concerning radioactive materials released in environment, especially migration behavior of radioactive cesium since November 2012. This report is a summary of the research results that have been obtained in environmental dynamics research conducted by JAEA in Fukushima Prefecture.

Journal Articles

Development of the ReaxFF methodology for electrolyte-water systems

Fedkin, M. V.*; Shin, Y. K.*; Dasgupta, N.*; Yeon, J.*; Zhang, W.*; van Duin, D.*; Van Duin, A. C. T.*; Mori, Kento*; Fujiwara, Atsushi*; Machida, Masahiko; et al.

Journal of Physical Chemistry A, 123(10), p.2125 - 2141, 2019/03

 Times Cited Count:38 Percentile:94.62(Chemistry, Physical)

no abstracts in English

256 (Records 1-20 displayed on this page)