Disentangling the effect of doping chemistry on the energy storage properties of barium titanate ferroelectrics using data science tools
Ruihao Yuan, Deqing Xue, Jinshan Li, Dezhen Xue, Turab Lookman
Abstract
Using data science tools including machine learning and statistical analysis, the effects of multiple chemical doping on the energy storage performance of barium titanate based ceramics are investigated from both quantitative and qualitative perspectives.
Topics & Concepts
Barium titanateMaterials scienceDopingEnergy storageBariumCeramicNanotechnologyLithium titanateEnergy (signal processing)Computer data storageEngineering physicsComputer scienceOptoelectronicsThermodynamicsPhysicsComposite materialMetallurgyQuantum mechanicsPower (physics)Battery (electricity)Operating systemLithium-ion batteryFerroelectric and Piezoelectric MaterialsMachine Learning in Materials ScienceFerroelectric and Negative Capacitance Devices