Litcius/Paper detail

Characterizing fracture stress of defective graphene samples using shallow and deep artificial neural networks

M.A.N. Dewapriya, R. K. N. D. Rajapakse, W. P. S. Dias

2020Carbon46 citationsDOI

Topics & Concepts

Artificial neural networkConvolutional neural networkGrapheneExtrapolationFracture (geology)Materials scienceArtificial intelligenceStress (linguistics)Computer scienceVacancy defectDurabilityBiological systemNanotechnologyMathematicsComposite materialMathematical analysisPhysicsCondensed matter physicsLinguisticsPhilosophyBiologyGraphene research and applicationsMachine Learning in Materials ScienceNon-Destructive Testing Techniques
Characterizing fracture stress of defective graphene samples using shallow and deep artificial neural networks | Litcius