News

Computer Science Research and Development Office: Past Updates†

| 2025†

• 2025-03-14 Dr. Akiko Yamaguchi received the CSED Young Researcher Award from the Computational Science and Engineering Division of the Atomic Energy Society of Japan.
• 2025-02-14 Version 2.7.0 of the open-source software 'PIMD' has been released, featuring newly added support for the n2p2 neural network potential package.
• 2025-02-06 A paper on the mechanism of radioactive cesium adsorption onto clay minerals in soil has been published in Science of the total environment, and a press release was issued.

| 2024†

• 2024-12-02 A paper on high-accuracy hydrogen calculations using machine learning molecular dynamics has been published in Physical Review Research.
• 2024-11-27 A paper on high-accuracy water calculations using machine learning molecular dynamics has been published in Journal of Chemical Physics.
• 2024-09-10 A paper on collaborative research related to material embrittlement has been published in Scripta Materialia.
• 2024-07-31 A paper on the effects of decontamination and cultivation activities on the reduction of ambient dose rates has been published in Journal of the Society for Remediation of Radioactive Contamination in the Environment.
• 2024-10-19 A paper on the creation of ambient dose rate maps by integrating data from different measurement methods in Fukushima has been published in Journal of Environmental Radioactivity.
• 2024-07-31 A paper on the mechanism of radioactive cesium adsorption onto clay minerals in soil has been published in Science of the total environment, and a press release was issued.
• 2024-07-31 A paper on improving the accuracy of numerical solutions for differential equations has been published in JSIAM Letters.
• 2024-05-20 A paper on the computational evaluation of the anti-embrittlement effects of aluminum alloys has been published in the International Journal of Hydrogen Energy.
• 2024-05-10 A paper on the results of calculations of novel properties of quasicrystalline materials using machine learning techniques has been published in Physical Review Letters, and its press release was issued. (Quasicrystals with strange physical properties brought about by six-dimensional fluctuations - Clarification by machine learning molecular kinetics simulations -)
• 2024-02-15 A paper on crack propagation in metallic materials obtained by machine learning molecular dynamics simulations is published in the Journal of Applied Physics and selected as Editor's Pick. The paper was also selected and introduced by the publisher on the paper introduction website.
• 2024-02-13 Press Release: "The Mystery of the Earth! What is the secret of metals in the soil? -Molecular Scale Simulations and Observations Reveal the Properties of Soil"
• 2024-01-04 New version (2.6.1) of the open source software "PIMD" is now available, supporting VASP-6.4.x.

| 2023†

• 2023-12-01 The open source software PIMD is now available for use with the Quloud material calculation cloud service.
• 2023-11-22 A paper on the distribution of air dose rates inside and outside wooden houses in Fukushima Prefecture is published.
• 2023-11-16 Press Release: "High-Speed and High-Precision Atomic Simulation Reproduces the Complex Atomic Structure of Glass! -Uncovering the Order Hidden in the Seemingly Disordered Structure of Glass-"
• 2023-09-15 A paper on the embrittlement of steel materials by hydrogen, co-authored with Nippon Steel and Sophia University, is published in the International Journal of Hydrogen Energy.
• 2023-06-27: A paper on machine learning molecular dynamics of iron is published in Physical Review Materials.
• 2023-06-01 Presentation about a patent on prevention of hydrogen embrittlement in Al-based alloy is given to industrial companies
• 2023-04-01 A paper about a large-scale first-principles calculation on "kink boundaries," believed to be the cause of the "millifeuille structure's" strengthening mechanism, were published.
• 2023-03-24 A paper on the modeling of silt-fence is published
• 2023-03-17 New version of PIMD released
• 2023-03-8 A paper on the application of machine learning-based atomic simulation method to particle simulations were published in Phys.Rev.D.