A data-driven approach combining together the experimental laser soldering,finite element analysis and machine learning,has been utilized to predict the morphology of interracial intermetallic compound(IMC) in Sn-xAg-...A data-driven approach combining together the experimental laser soldering,finite element analysis and machine learning,has been utilized to predict the morphology of interracial intermetallic compound(IMC) in Sn-xAg-yCu/Cu(SAC/Cu) system.Six types of SAC solders with varying weight proportion of Ag and Cu,have been processed with fiber laser at different magnitudes of power(30-50 W) and scan speed(10-240 mm/min),and the resultant IMC morphologies characterized through scanning electron microscope are categorized as prismatic and scalloped ones.For the different alloy composition and laser parameters,finite element method(FEM) is employed to compute the transient distribution of temperature at the interface of solder and substrates.The FEM-generated datasets are supplied to a neural network that predicts the IMC morphology through the quantified values of temperature dependent Jackson parameter(αJ).The numerical value of αJ predicted from neural network is validated with experimental IMC morphologies.The critical scan speed for the morphology transition between prismatic and scalloped IMC is estimated for each solder composition at a given power.Sn-0.7 Cu having the largest critical scan speed at 30 W and Sn-3.5 Ag alloy having the largest critical scan speed at input power values of 40 W and 50 W,thus possessing the greatest likelihood of forming prismatic interfacial IMC during laser soldering,can be inferred as most suitable SAC solders in applications exposed to shear loads.展开更多
Is the evolution of how science is done primarily heuristic or driven by policy makers?Reading the intriguing story of the inception of the European Open Science Cloud(EOSC)by J-C Burgelman one could assume the latter...Is the evolution of how science is done primarily heuristic or driven by policy makers?Reading the intriguing story of the inception of the European Open Science Cloud(EOSC)by J-C Burgelman one could assume the latter.But the story also reveals that the policy makers’shaping of concepts and planning of funding models is a mere reaction to the turns of the broad stream of research.展开更多
基金supported financially by the China Postdoctoral Science Foundation (No. 2017M611215)Research Fund for International Young Scientistsfif the National Natural Science Foundation of China (No. 51750110504)National Natural Science Foundation of China (No. 51871040)。
文摘A data-driven approach combining together the experimental laser soldering,finite element analysis and machine learning,has been utilized to predict the morphology of interracial intermetallic compound(IMC) in Sn-xAg-yCu/Cu(SAC/Cu) system.Six types of SAC solders with varying weight proportion of Ag and Cu,have been processed with fiber laser at different magnitudes of power(30-50 W) and scan speed(10-240 mm/min),and the resultant IMC morphologies characterized through scanning electron microscope are categorized as prismatic and scalloped ones.For the different alloy composition and laser parameters,finite element method(FEM) is employed to compute the transient distribution of temperature at the interface of solder and substrates.The FEM-generated datasets are supplied to a neural network that predicts the IMC morphology through the quantified values of temperature dependent Jackson parameter(αJ).The numerical value of αJ predicted from neural network is validated with experimental IMC morphologies.The critical scan speed for the morphology transition between prismatic and scalloped IMC is estimated for each solder composition at a given power.Sn-0.7 Cu having the largest critical scan speed at 30 W and Sn-3.5 Ag alloy having the largest critical scan speed at input power values of 40 W and 50 W,thus possessing the greatest likelihood of forming prismatic interfacial IMC during laser soldering,can be inferred as most suitable SAC solders in applications exposed to shear loads.
文摘Is the evolution of how science is done primarily heuristic or driven by policy makers?Reading the intriguing story of the inception of the European Open Science Cloud(EOSC)by J-C Burgelman one could assume the latter.But the story also reveals that the policy makers’shaping of concepts and planning of funding models is a mere reaction to the turns of the broad stream of research.
