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Mechanistic insights of enhanced spin polaron conduction in CuO through atomic doping

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摘要 The formation of a“spin polaron”stems from strong spin-charge-lattice interactions in magnetic oxides,which leads to a localization of carriers accompanied by local magnetic polarization and lattice distortion.For example,cupric oxide(CuO),which is a promising photocathode material and shares important similarities with high Tc superconductors,conducts holes through spin polaron hopping with flipped spins at Cu atoms where a spin polaron has formed.The formation of these spin polarons results in an activated hopping conduction process where the carriers must not only overcome strong electron−phonon coupling but also strong magnetic coupling.Collectively,these effects cause low carrier conduction in CuO and hinder its applications.To overcome this fundamental limitation,we demonstrate from first-principles calculations how doping can improve hopping conduction through simultaneous improvement of hole concentration and hopping mobility in magnetic oxides such as CuO.Specifically,using Li doping as an example,we show that Li has a low ionization energy that improves hole concentration,and lowers the hopping barrier through both the electron−phonon and magnetic couplings'reduction that improves hopping mobility.Finally,this improved conduction predicted by theory is validated through the synthesis of Li-doped CuO electrodes which show enhanced photocurrent compared to pristine CuO electrodes.We conclude that doping with nonmagnetic shallow impurities is an effective strategy to improve hopping conductivities in magnetic oxides.
出处 《npj Computational Materials》 SCIE EI 2018年第1期154-161,共8页 计算材料学(英文)
基金 Y.P.acknowledges financial support from the National Science Foundation under grant no.DMR-1760260 and the Hellman Fellowship.T.J.S.acknowledges financial support from a GAANN fellowship This research used resources of the Center for Functional Nanomaterials,which is a U.S.DOE Office of Science Facility,and the Scientific Data and Computing Center,a component of the Computational Science Initiative,at Brookhaven National Laboratory under Contract No.DE-SC0012704 This work also used the Extreme Science and Engineering Discovery Environment(XSEDE),67 which is supported by National Science Foundation grant number ACI-1548562.K.-S C.acknowledges financial support from the Division of Chemical Sciences,Geosciences,and Biosciences,Office of Basic Energy Sciences of the U.S.Department of Energy through Grant DE-SC0008707.A.C.C was supported by the National Science Foundation Graduate Research Fellowship under Grant No.DGE-1256259.
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