Journal
PHYSICAL REVIEW B
Volume 102, Issue 21, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevB.102.214102
Keywords
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Funding
- National Natural Science Foundation of China [91833303, 61974043, 61674057, 51562004, 61571142]
- National Key Research and Development Program of China [2019YFB2203400, 2017YFA0303403]
- Projects of Science and Technology Commission of Shanghai Municipality [18JC1412400, 18YF1407200, 19511120100]
- China Postdoctoral Science Foundation [2020TQ0099, 2020M681222]
- Guangxi Natural Science Outstanding Youth Foundation [2016GXNSFFA380007]
- Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning
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Ferroelectric lead-free KxNa1-xNbO3 (KNN) perovskite, as the representative of the preferred oxides with good dielectric and piezoelectric behaviors, has attracted broad attentions in recent years. Here we systematically investigate the complete process of temperature dependent structural evolution in manganese (Mn)-doped K0.5Na0.5NbO3-LiBiO3 single crystals, presenting the ultrahigh piezoelectric coefficient of about 1050 pC N-1 and the excellent dielectric and ferroelectric performances, by demonstrating phonon thermodynamics associated with all Raman active modes at a wide temperature range of 80-800 K. All-round unpolarized and polarized scattering characteristics reflecting various phonon and structure properties are specified in detail. Symmetry difference, symmetry breaking, and structure rearrangement among the molecular vibrations have been proven to be related to a multiphase coexistence and the discontinuity of first-order phase transition. In comparison with the lattice dynamics, a complete phase transition ordering and the shift of transition point have been observed in KNN-LiBiO3 crystals with the different Mn contents. This work aims at deeply revealing the details of good ferroelectric/dielectric performance, structure, and phonon thermodynamics, as well as understanding the mechanisms of first-order phase transition under the doping manipulation in KNN systems.
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