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津川 聖人*; 早川 頌*; 沖田 泰良*; 愛知 正温*; 板倉 充洋; 鈴木 克幸*
Computational Materials Science, 215, p.111806_1 - 111806_8, 2022/12
被引用回数：2 パーセンタイル：29.01(Materials Science, Multidisciplinary)Molecular dynamics simulations were conducted to evaluate the interactions between an edge dislocation and a rigid, impenetrable precipitate in Cu by changing the distance between the glide plane of the dislocation and the center of the precipitate (
). In these calculations, the precipitate was introduced as a super particle that moved according to the total force exerted by the matrix atoms on the precipitate atoms. When the center of the precipitate was close to the glide plane, an Orowan loop was formed around the precipitate after the dislocation detached, and the critical resolved shear stress (CRSS) was similar to the value evaluated by the results at 
. However, when the glide plane was far from the center of the precipitate, either a vacancy loop or loops generated through the Hirsch mechanism were formed, depending on whether the center of the precipitate was below or above the glide plane. The magnitude of the CRSS was not symmetric about . This study confirmed that it is necessary to analyze the CRSS by changing to construct a predictive model for the hardening caused by the formation of lattice defects, and that precipitate hardening appears to be smaller than the value estimated using the results at .
津川 聖人*; 早川 頌*; 岩瀬 祐樹*; 沖田 泰良*; 鈴木 克幸*; 板倉 充洋; 愛知 正温*
Computational Materials Science, 210, p.111450_1 - 111450_9, 2022/07
被引用回数：8 パーセンタイル：75.5(Materials Science, Multidisciplinary)Precipitation strengthening has been utilized to improve the properties of metallic materials so far. Since interactions between precipitates and dislocations are micro-mechanisms responsible for this phenomenon, a molecular dynamics (MD) simulation is a powerful tool for quantifying this phenomenon. In this study, we introduced a method to simulate a rigid and impenetrable precipitate against a direct contact with a dislocation using a single interatomic potential representing the bulk material. The total force exerted on all atoms in the precipitate region was divided by the number of atoms in the region. This average force was then applied to each atom in the region to simulate one super particle that moved depending on the total force exerted by the matrix atoms on the precipitate atoms. We used MD simulations to quantify the interaction of a precipitate with an edge dislocation. After the dislocation overcame the precipitate, an Orowan loop was formed along the outer circumference of the precipitate. The energy of the loop was 2.1 
0.1 eV/b, which was higher than that obtained using the elasticity. The hardening caused by the precipitate was larger than that caused by voids of the same size. The proposed method can be applied to simulate interactions of precipitates with dislocations in any type of metallic material, especially when a dislocation bypasses a precipitate without changing its structure, except when a strong repulsive force acts between them.
沖田 泰良*; 寺山 怜志*; 津川 聖人*; 小林 恵太; 奥村 雅彦; 板倉 充洋; 鈴木 克幸*
Computational Materials Science, 202, p.110865_1 - 110865_9, 2022/02
被引用回数：7 パーセンタイル：48.44(Materials Science, Multidisciplinary)In this study, a Neural Network Potential (NNP) using an Artificial Neural Network (ANN) was developed for Zr, which is used as fuel cladding material in light water reactors. The reference data were obtained through first-principles calculations of various quantities, such as strained hexagonal-closed-packed (hcp) cells, strained face-centered cubic cells, cells containing a vacancy, several vacancies, and surfaces and 
-surface energy on all five slip planes in the hcp structures. These data were converted to training data for the ANN, which were invariant to the rotation and translation of the atoms and independent of the number of atoms in the cells. The ANN was defined as a three-layer structure and the number of the nodes was set to 26-12-18-1. The NNP reproduced the first-principles calculations, particularly for the shear deformation, vacancy formation energy, surface energy, and -surface energy, with much higher accuracy than any of the existing potentials that have been developed for classical molecular dynamics simulations. The NNP was applied to identify the formation process of c-type dislocation loops in Zr, which is a key microstructure responsible for abrupt increases in hydrogen absorption. The formation process was determined by the balance of the vacancy formation energy, surface energy and the -surface energy on the basal plane, both of which were precisely reproduced only by the NNP developed in this study. The formation process was identified based on the atomistic behavior of the NNP.
津川 聖人*; 寺山 怜志*; 沖田 泰良*; 奥村 雅彦; 板倉 充洋
no journal, ,
BWRで使用されるZry-2では、燃焼度が一定値(
40GWd/t)を超すと、c-type転位ループが観察されることが知られている。c-type転位ループは、中性子照射下で形成した原子空孔が異方拡散し、六方晶底面上に集合体を形成し、これが潰れてできたものと考えられている。c-type転位ループが観察される燃焼度とほぼ同時にZry-2の水素吸収量が急激に増加し、水素脆化が誘起されることが確認されている。これらを踏まえると、c-type転位ループの形成過程を解明することは、水素脆化を抑制した材料設計のためにも重要な研究課題と位置付けられる。本研究では、機械学習ポテンシャル(MLP)を用いた分子動力学(MD)法により、c-type転位ループ形成過程を原子レベルの挙動から解明することを目的とする。
