The present article addresses an early-stage attempt on replacing the analyticity-based sink strength terms in rate equations by surrogate models of machine learning representation. Here we emphasise, in the context of multiscale modelling, a combinative use of machine learning with scale analysis, through which a set of fine-resolution problems of partial differential equations describing the (quasi-steady) short-range individual sink behaviour can be asymptotically sorted out from the mean-field kinetics. Hence the training of machine learning is restrictively oriented, that is, to express the local and already identified, but analytically unavailable nonlinear functional relationships between the sink strengths and other local continuum field quantities. With the trained models, one is enabled to quantitatively investigate the biased effect shown by a void/bubble being a point defect sink, and the results are compared with existing ones over well-studied scenarios. Moreover, the faster diffusive mechanisms on crystalline interfaces are distinguishingly modelled by locally planar rate equations, and their linkages with rate equations for bulk diffusion are formulated through derivative jumps of point defect concentrations across the interfaces. Thus the distinctive role of crystalline interfaces as partial sinks and quick diffusive channels can be investigated. Methodologicalwise, the present treatment is also applicable for studying more complicated situation of long-term sink behaviour observed in irradiated materials.
CuCrZr heat-sink irradiation performance reveals new challenges for thermonuclear fusion reactors
Université Lorraine（洛林大学）；Montanuniversität Leoben（莱奥本矿业大学）；UKAEA (United Kingdom Atomic Energy Authority)（英国原子能管理局）；SCK CEN（比利时核研究中心）；Universidade de São Paulo Escola Politécnica（圣保罗大学理工学院）
Deconvoluting Mechanisms of Radiation-Induced Grain Boundary Segregation in Dilute Ni-X (X = Fe, Cr, Mn) Alloys via Ion Irradiation and Phase-field Modeling
Idaho National Laboratory（爱达荷国家实验室）；Texas A&M University（德克萨斯农工大学）
Absorption kinetics of vacancies by cavities in Aluminum: numerical characterization of sink strengths and first-passage statistics through Krylov subspace projection and eigenvalue deflation
Multi-scale modeling of the effects of temperature, radiation flux and sink strength on point-defect and solute redistribution in dilute Fe-based alloys
Cross-sectional helium irradiation reveals interface-controlled bubble evolution in Cr/CrAlSiN multilayer coatings on zirconium alloys
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences（中国科学院宁波材料技术与工程研究所）；Ningbo University of Technology（宁波工程学院）；Harbin Engineering University（哈尔滨工程大学）；Southwest University of Science and Technology（西南科技大学）；Czech Technical University in Prague（布拉格捷克理工大学）；Qianwan Institute of CNITECH（国创中心千湾研究院）；Advanced Energy Science and Technology Guangdong Laboratory（先进能源科学与技术广东省实验室）；University of Chinese Academy of Sciences（中国科学院大学）；University of Southampton（南安普顿大学）
Local chemical order suppresses grain boundary migration under irradiation in CrCoNi
University of California, Irvine（加州大学尔湾分校）；Hopkins Extreme Materials Institute, Johns Hopkins University（约翰斯·霍普金斯大学霍普金斯极端材料研究所）；Johns Hopkins University（约翰斯·霍普金斯大学）
Recrystallisation phenomena in an ultrafine-grained Al-Mg-Si alloy revealed by correlative in situ EBSD and TEM heating
Graz University of Technology（格拉茨工业大学）；Graz Centre for Electron Microscopy (FELMI-ZFE)（格拉茨电子显微镜中心）；Montanuniversität Leoben（莱奥本矿业大学）；Institute of Aeronautics and Space, Brazilian Air Force（巴西空军航空与航天研究所）
