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Machine learning-based prediction of nonlinear optical rectification in GaAs/AlGaAs tetrapod core/shell quantum dots under pressure and central hydrogenic impurity effects

N. Zeiri, A. Ed‐Dahmouny, David B. Hayrapetyan, P. Başer, A. Sali, Mohamed E. El Sayed, Ahmed Samir, Carlos A. Duque

2025Materials Science in Semiconductor Processing9 citationsDOI

Topics & Concepts

RectificationMaterials scienceImpurityQuantum dotCore (optical fiber)Shell (structure)Nonlinear systemNonlinear opticalCondensed matter physicsOptoelectronicsComposite materialPhysicsVoltageQuantum mechanicsSemiconductor Quantum Structures and DevicesSemiconductor Lasers and Optical DevicesAdvanced Semiconductor Detectors and Materials
Machine learning-based prediction of nonlinear optical rectification in GaAs/AlGaAs tetrapod core/shell quantum dots under pressure and central hydrogenic impurity effects | Litcius