SKM 2023 –
            
              wissenschaftliches Programm
            
          
        
        
        
        
        
      
      
  
    
  
  MM 33: Topical Session: Fundamentals of Fracture – Amorphous Metals
  Mittwoch, 29. März 2023, 15:45–18:00, SCH A 215
  
    
  
  
    
      
        
          
            
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          15:45 | 
          MM 33.1 | 
          
            
            
              
                In situ measurement of plasticity accompanying Hydrogen induced cracking — Leonel Stermann, Loïc Vanel, and •Döme Tanguy
              
            
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          16:00 | 
          MM 33.2 | 
          
            
            
              
                Liquid metal induced fracture : modelling and supporting experiments — Thierry Auger, Antoine Clement, Marco Ezequiel, •Eva Héripré, Ingrid Serre, Zehoua Hamouche, Julie Bourgon, Eric Leroy, and Maxime Vallet
              
            
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          16:15 | 
          MM 33.3 | 
          
            
            
              
                Microscale fracture behavior of Laves phases in the Mg-Ca-Al ternary alloy system — •Anwesha Kanjilal, Uzair Rehman, James P. Best, and Gerhard Dehm
              
            
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          16:30 | 
          MM 33.4 | 
          
            
            
              
                Fracture mechanics concepts in application to functionally graded coatings (FGCs) and FGC structures — •Vera Petrova and Siegfried Schmauder
              
            
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          16:45 | 
          MM 33.5 | 
          
            
            
              
                Nonlinear elastic effect on interacting crack paths in PDMS films — •Loic Vanel, Osvanny Ramos, Thierry Biben, Stéphane Santucci, and Anthony Gravouil
              
            
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          17:00 | 
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              15 min. break
            
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          17:15 | 
          MM 33.6 | 
          
            
            
              
                Modelling mechanochemical reactions in epoxy resins under tensile load using hybrid QM/MM/MD approaches — •Christian R. Wick, Mattia Livraghi, Sampannah Pahi, Bariscan Arican, David M. Smith, and Ana-Sunčana Smith
              
            
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          17:30 | 
          MM 33.7 | 
          
            
            
              
                Machine Learning of fracture in glasses — Francesc Font-Clos, Marco Zanchi, Stefan Hiemer, •Silvia Bonfanti, Roberto Guerra, Michael Zaiser, and Stefano Zapperi
              
            
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          17:45 | 
          MM 33.8 | 
          
            
            
              
                Using deep neural networks to bridge the gap between statistical fractographic analysis and fracture toughness prediction for polymers — •Guillaume de Luca, Mohammed Idri, and Laurent Ponson
              
            
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