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Artificial neural network approach for predicting tunneling-induced and frequency-dependent electrical impedances of conductive polymeric composites

Daeik Jang, Taegeon Kil, H.N. Yoon, Joonho Seo, Hammad R. Khalid

2021Materials Letters19 citationsDOI

Topics & Concepts

Materials scienceElectrical conductorElectrical impedanceQuantum tunnellingCarbon nanotubeAmplitudeComposite materialImpedance parametersElectrical resistivity and conductivityVoltageArtificial neural networkOptoelectronicsElectrical engineeringComputer scienceEngineeringPhysicsQuantum mechanicsMachine learningSmart Materials for ConstructionConducting polymers and applicationsAdvanced Sensor and Energy Harvesting Materials
Artificial neural network approach for predicting tunneling-induced and frequency-dependent electrical impedances of conductive polymeric composites | Litcius