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Subjects: Fracture toughness; Glass-ceramics; Microstructure
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Source:
Sun , D , Du , T , Zhang , Q , Jensen , L R , Wang , D , Ding , J , Zhao , J & Smedskjær , M M 2024 , ' Toughening mechanism of barium titanosilicate glass-ceramics ' , Materials & Design , vol. 246
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Subjects: Bayesian optimization; cellular materials; interparticle interactions
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Source:
Liu , H , Li , L , Wei , Z , Smedskjaer , M M , Zheng , X R & Bauchy , M 2024 , ' De Novo Atomistic Discovery of Disordered Mechanical Metamaterials by Machine Learning ' , Advanced Science , vol. 11
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Subjects: Constitutive modelling; Copper nanoparticles sintering; High-temperature tensile test
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Source:
Hu , D , Qian , C , Liu , X , Du , L , Sun , Z , Fan , X , Zhang , G & Fan , J 2023 , ' High temperature viscoplastic deformation behavior of sintered nanocopper paste used in power electronics
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Subjects: Fracture behavior; Glassy electrolyte; Ionic conductivity
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Source:
Du , T , Chen , Z , Liu , H , Zhang , Q , Bauchy , M , Yue , Y & Smedskjær , M M 2023 , ' Controlling factor for fracture resistance and ionic conduction in glassy lithium borophosphate electrolytes
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Subjects: amorphous oxides; fracture; machine learning
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Source:
Du , T , Liu , H , Tang , L , Sørensen , S S , Bauchy , M & Smedskjær , M M 2021 , ' Predicting Fracture Propensity in Amorphous Alumina from Its Static Structure Using Machine Learning ' , ACS Nano
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Subjects: atomic-scale predicting; bioactive materials; silica-polymer hybrid
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Source:
Fan , W , Du , T , Droce , A , Jensen , L R , Youngman , R E , Ren , X , Gurevich , L , Bauchy , M , Kristensen , P , Xing , B , Yu , D & Smedskjær , M M 2022 , ' Resolving the Conflict between
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