Understanding mechanical relaxation, such as primary（α） and secondary（β） relaxation, is key to unravel the intertwined relation between the atomic dynamics and non-equilibrium thermodynamics in metallic glasses....Understanding mechanical relaxation, such as primary（α） and secondary（β） relaxation, is key to unravel the intertwined relation between the atomic dynamics and non-equilibrium thermodynamics in metallic glasses. At a fundamental level, relaxation, plastic deformation, glass transition, and crystallization of metallic glasses are intimately linked to each other, which can be related to atomic packing, inter-atomic diffusion, and cooperative atom movement. Conceptually, βrelaxation is usually associated with structural heterogeneities intrinsic to metallic glasses. However, the details of such structural heterogeneities, being masked by the meta-stable disordered long-range structure, are yet to be understood. In this paper, we briefly review the recent experimental and simulation results that were attempted to elucidate structural heterogeneities in metallic glasses within the framework of β relaxation. In particular, we will discuss the correlation amongβ relaxation, structural heterogeneity, and mechanical properties of metallic glasses.展开更多
The compositional design of metallic glasses(MGs)is a long-standing issue in materials science and engineering.However,traditional experimental approaches based on empirical rules are time consuming with a low efficie...The compositional design of metallic glasses(MGs)is a long-standing issue in materials science and engineering.However,traditional experimental approaches based on empirical rules are time consuming with a low efficiency.In this work,we successfully developed a hybrid machine learning(ML)model to address this fundamental issue based on a database containing~5000 different compositions of metallic glasses(either bulk or ribbon)reported since 1960s.Unlike the prior works relying on empirical parameters for featurization of data,we designed modeling guided data descriptors in line with the recent theoretical models on amorphization in chemically complex alloys for the development of the hybrid classification-regression ML algorithms.Our hybrid ML modeling was validated both numerically and experimentally.Most importantly,it enabled the discovery of MGs(either bulk or ribbon)through the ML-aided deep search of a multitude of quaternary to scenery alloy compositions.The computational framework herein established is expected to accelerate the design of MG compositions and expand their applications by probing the complex and multi-dimensional compositional space that has never been explored before.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.51401192 and 51611130120)the Natural Science Foundation of Shaanxi Province,China(Grant No.2016JM5009)+5 种基金the Fundamental Research Funds for the Central Universities of China(Grant Nos.3102015ZY027 and 3102015BJ(Ⅱ)JGZ019)the Aeronautical Science Foundation of China(Grant No.2015ZF53072)supported by the Hong Kong Scholar Program of China(Grant No.XJ2015056)the support of MINECO(Grant No.FIS2014-54734-P)Generalitat de Catalunya(Grant No.2014SGR00581)supported by the Research Grant Council,the Hong Kong City of China,through the General Research Fund(Grant No.City U11214914)
文摘Understanding mechanical relaxation, such as primary（α） and secondary（β） relaxation, is key to unravel the intertwined relation between the atomic dynamics and non-equilibrium thermodynamics in metallic glasses. At a fundamental level, relaxation, plastic deformation, glass transition, and crystallization of metallic glasses are intimately linked to each other, which can be related to atomic packing, inter-atomic diffusion, and cooperative atom movement. Conceptually, βrelaxation is usually associated with structural heterogeneities intrinsic to metallic glasses. However, the details of such structural heterogeneities, being masked by the meta-stable disordered long-range structure, are yet to be understood. In this paper, we briefly review the recent experimental and simulation results that were attempted to elucidate structural heterogeneities in metallic glasses within the framework of β relaxation. In particular, we will discuss the correlation amongβ relaxation, structural heterogeneity, and mechanical properties of metallic glasses.
基金The research of YY is supported by the Research Grant Council,the Hong Kong Government,through the General Research Fund(GRF)with the grant numbers CityU11209317,CityU11213118,and CityU11200719Atom probe tomography research was conducted by Dr.JH LUAN at the Inter-University 3D Atom Probe Tomography Unit of City University of Hong Kong,which is supported by the CityU grant 9360161。
文摘The compositional design of metallic glasses(MGs)is a long-standing issue in materials science and engineering.However,traditional experimental approaches based on empirical rules are time consuming with a low efficiency.In this work,we successfully developed a hybrid machine learning(ML)model to address this fundamental issue based on a database containing~5000 different compositions of metallic glasses(either bulk or ribbon)reported since 1960s.Unlike the prior works relying on empirical parameters for featurization of data,we designed modeling guided data descriptors in line with the recent theoretical models on amorphization in chemically complex alloys for the development of the hybrid classification-regression ML algorithms.Our hybrid ML modeling was validated both numerically and experimentally.Most importantly,it enabled the discovery of MGs(either bulk or ribbon)through the ML-aided deep search of a multitude of quaternary to scenery alloy compositions.The computational framework herein established is expected to accelerate the design of MG compositions and expand their applications by probing the complex and multi-dimensional compositional space that has never been explored before.
