We show the ability to map the phase diagram of a relaxor-ferroelectric system as a function of temperature and composition through local hysteresis curve acquisition,with the voltage spectroscopy data being used as a...We show the ability to map the phase diagram of a relaxor-ferroelectric system as a function of temperature and composition through local hysteresis curve acquisition,with the voltage spectroscopy data being used as a proxy for the(unknown)microscopic state or thermodynamic parameters of materials.Given the discrete nature of the measurement points,we use Gaussian processes to reconstruct hysteresis loops in temperature and voltage space,and compare the results with the raw data and bulk dielectric spectroscopy measurements.The results indicate that the surface transition temperature is similar for all but one composition with respect to the bulk.Through clustering algorithms,we recreate the main features of the bulk diagram,and provide statistical confidence estimates for the reconstructed phase transition temperatures.We validate the method by using Gaussian processes to predict hysteresis loops for a given temperature for a composition unseen by the algorithm,and compare with measurements.These techniques can be used to map phase diagrams from functional materials in an automated fashion,and provide a method for uncertainty quantification and model selection.展开更多
基金The synthesis and characterization of samples work was supported by DoD-AFOSR(Grant#FA9550-16-1-0295)D.K.P.and S.K.acknowledge IFN(NSF Grant No.EPS-01002410)for fellowshipN.L.acknowledges support from the Eugene P.Wigner Fellowship program at Oak Ridge National Lab.D.K.P.and R.S.K.acknowledge CNMS facilities through CNMS user Proposal ID:CNMS2014-095.E.S.acknowledges support under the Cooperative Research Agreement between the University of Maryland and the National Institute of Standards and Technology Center for Nanoscale Science and Technology,Award 70NANB10H193,through the University of Maryland.
文摘We show the ability to map the phase diagram of a relaxor-ferroelectric system as a function of temperature and composition through local hysteresis curve acquisition,with the voltage spectroscopy data being used as a proxy for the(unknown)microscopic state or thermodynamic parameters of materials.Given the discrete nature of the measurement points,we use Gaussian processes to reconstruct hysteresis loops in temperature and voltage space,and compare the results with the raw data and bulk dielectric spectroscopy measurements.The results indicate that the surface transition temperature is similar for all but one composition with respect to the bulk.Through clustering algorithms,we recreate the main features of the bulk diagram,and provide statistical confidence estimates for the reconstructed phase transition temperatures.We validate the method by using Gaussian processes to predict hysteresis loops for a given temperature for a composition unseen by the algorithm,and compare with measurements.These techniques can be used to map phase diagrams from functional materials in an automated fashion,and provide a method for uncertainty quantification and model selection.
