Structural phase transitions in perovskite BaCeO3 with data mining and first-principles theoretical calculations
Farha Naaz, Manendra S. Chauhan, Kedar Yadav, Surender Singh, Ashok, Kumar, Dasari L. V. K. Prasad

TL;DR
This study combines data mining and first-principles calculations to predict and analyze the complex temperature-induced phase transitions of BaCeO3, resolving conflicting experimental observations and identifying novel intermediate phases.
Contribution
It introduces a comprehensive computational approach to predict polymorphs and phase transitions in BaCeO3, clarifying experimental discrepancies and revealing new metastable phases.
Findings
34 polymorphs predicted, with stability order matching neutron diffraction
Identified four novel phases at intermediate temperatures
Predicted phase transition temperatures closely align with experimental data
Abstract
Several experiments conducted over decades have revealed that the perovskite-structured BaCeO3 goes through a series of temperature-induced structural phase transitions. However, it has been frequently observed that the number of phases and the sequence in which they appear as a function of temperature differ between experiments. Insofar as neutron diffraction and Raman spectroscopy experiments are concern, four structures are well characterized with three transitions: Pnma to Imma [563 K] to R-3c [673 K] to Pm-3m [1173 K]. In contrast, thermoanalytical methods showed multiple singularities corresponding to at-least three more structural transitions at around 830 K, 900 K, and 1030 K. In account of these conflicting experimental findings, we computed free energy phase diagram for BaCeO3 employing crystal structure data mining in conjunction with first principles electronic structure and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Thermoelectric Materials and Devices · Machine Learning in Materials Science · Magnetic and transport properties of perovskites and related materials
