Statistical study of defects caused by primary knock-on atoms in fcc Cu and bcc W using molecular dynamics

Warrier, M.; Bhardwaj, Utkarsh; Hemani, H.; Schneider, R.; Mutzke, A.; Valsakumar, M. C.

doi:10.1016/j.jnucmat.2015.09.025

Cited by 22 publications

(19 citation statements)

References 28 publications

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“…The averaging was done for 200 MD simulations of randomly directed PKA at each energy. It was seen that 200 random directions is sufficient for the variances in the number of defects produced to stabilize [15]. This can now be a realistic input for initializing defect positions in a KMC code (Section.4).…”

Section: Large Scale Data Analysis: MD Studies Of Directional Effectsmentioning

confidence: 99%

“…The collision cascade has a time scale of a few pico-secs. Typically, a 50 × 50 × 50 unit cell simulation of bcc W is sufficient to The defects were identified by an algorithm similar to the method of spheres [2] and is described in [16,15]. In this method, a interstitial-vacancy pair is said to have been created if the interstitial is away from its lattice position by a value r disp .…”

Section: Large Scale Data Analysis: MD Studies Of Directional Effectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…However better models are needed in modeling the creation of interstitials and vacancies [15]. We have used MD to study the directional effects of PKA bombardment on the number of displaced atoms in a collision cascade in crystal Cu, W and Fe [15,16] for modest PKA energies of 1-5 keV. We have carried out several thousand MD simulations with the PKA directed along random crystal directions and shown that typically a hundred random directions in the crystal have to be explored before the average number of displaced atoms become constant.…”

Section: Introductionmentioning

confidence: 99%

“…We have carried out several thousand MD simulations with the PKA directed along random crystal directions and shown that typically a hundred random directions in the crystal have to be explored before the average number of displaced atoms become constant. We have obtained the direction averaged (i) number of displacements, (ii) distributions of interstitials and vacancies and (iii) in-cascade cluster size distributions of these defects in [15]. The requirement for large scale post processing of several tera-bytes of data from the MD runs is described in Section.2.…”

Section: Introductionmentioning

confidence: 99%

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Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

Warrier¹,

Bhardwaj²,

Bukkuru³

2016

J. Phys.: Conf. Ser.

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Abstract. Modification of materials in nuclear reactors due to neutron irradiation is a multiscale problem. These neutrons pass through materials creating several energetic primary knock-on atoms (PKA) which cause localized collision cascades creating damage tracks, defects (interstitials and vacancies) and defect clusters depending on the energy of the PKA. These defects diffuse and recombine throughout the whole duration of operation of the reactor, thereby changing the micro-structure of the material and its properties. It is therefore desirable to develop predictive computational tools to simulate the micro-structural changes of irradiated materials. In this paper we describe how statistical averages of the collision cascades from thousands of MD simulations are used to provide inputs to Kinetic Monte Carlo (KMC) simulations which can handle larger sizes, more defects and longer time durations. Use of unsupervised learning and graph optimization in handling and analyzing large scale MD data will be highlighted.

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Section: Large Scale Data Analysis: MD Studies Of Directional Effectsmentioning

confidence: 99%

Section: Large Scale Data Analysis: MD Studies Of Directional Effectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

Warrier¹,

Bhardwaj²,

Bukkuru³

2016

J. Phys.: Conf. Ser.

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Study of transmutation, gas production, and displacement damage in chromium for fusion neutron spectrum

Rajput

Srinivasan

2020

Annals of Nuclear Energy

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Classification of clusters in collision cascades

Bhardwaj

Sand

Warrier

2020

Computational Materials Science

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The structure of defect clusters formed in a displacement cascade plays a significant role in the microstructural evolution during irradiation. Molecular dynamics simulations have been widely used to study collision cascades and subsequent clustering of defects. We present a novel method to pattern match and classify defect clusters. A cluster is characterized by the geometrical and topological histograms of its angles and distances which can then be used as similarity metrics. The technique is demonstrated by matching similar clusters for different cluster shapes like ring, crowdions etc. in a database of cascade damage configurations in Fe and W at different energies. We further use graph based dimensionality reduction techniques and unsupervised machine learning on the features of all the clusters present in the database to find classes of clusters. The classification successfully separates out many already known categories of clusters such as crowdions, planar crowdion pairs, rings and perpendicular crowdions. The dimensionality and size of different classes provides a broad categorization of classes. The distribution of different classes of shapes among cascades of different elements and energies shows the exclusivity of shapes to elements and energies. We discuss the key points and computational efficiency of the algorithms along with the various prominent results of their application. We discuss the motivation for using machine learning and statistics for the problems and compare different techniques. The algorithms along with the supporting analysis and visualizations give an unsupervised approach for classification and study of defect clusters in cascades. The distribution of cluster shapes and structures along with the shape properties like diffusivity, stability, etc. can be used as input to higher scale models in a multi-scale radiation damage study.The defects formed during the displacement cascades due to irradiation are the primary source of radiation damage [1,2,3,4,5,6,7]. The defects in metals with body-centered cubic structure are produced in the form of single point defects (interstitials and vacancies) or clusters of such defects. The point defects and glissile clusters diffuse after the cascade to either annihilate or form bigger defect clusters. The structural details of primary point defect clusters (formed as a direct consequence of the cascade) define the diffusion, recombination, thermal stability and their other characteristics [2,8,9,10] which in the long term determine the micro-structural changes in the material [11,12,13,14,15]. These properties have an affect on the results of higher scale models like Monte Carlo methods, rate theories etc. [13,14,7,16]. The glissile clusters can move and interact with other defects and grain boundaries whereas the sessile clusters can be nucleation centers for defect-growth. The interaction of these clusters with other defects will decide the micro-structural changes due to irradiation. Classification and taxonomy of all possible clusters in diff...

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Statistical study of defects caused by primary knock-on atoms in fcc Cu and bcc W using molecular dynamics

Cited by 22 publications

References 28 publications

Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

Study of transmutation, gas production, and displacement damage in chromium for fusion neutron spectrum

Classification of clusters in collision cascades

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