Login / Signup

Investigation of thermal control in phase-changing ABO 3 perovskites via first-principles predictions: general mechanism of emittance.

Liping TongNianao XuHongchao LiLan YangZhongyang WangQi Xin GuoTongxiang Fan
Published in: Physical chemistry chemical physics : PCCP (2023)
Phase-change thermal control has recently seen increased interest due to its significant potential for use in smart windows, building insulation, and optoelectronic devices in spacecraft. Tunable variation in infrared emittance can be achieved by thermally controlling the phase transitions of materials at different temperatures. A high emittance in the mid-infrared region is usually caused by resonant phonon vibrational modes. However, the fundamental mechanism of emittance variation during the phase-change process remains elusive. In this work, the electronic bandgaps, phononic structures, optical-spectrum properties, and formation energies of 76 kinds of phase-changing ABO 3 perovskites were predicted based on first-principles calculations in the mid-infrared region. The variation in emittance between two phases of a single material was found to have an exponential correlation with the bandgap difference ( R 2 ∼ 0.92). Furthermore, a strong linear correlation ( R 2 ∼ 0.92) was found between the emittance variation and the formation-energy difference, and the emittance variation was also strongly correlated with the volume-distortion rate ( R 2 ∼ 0.90). Finally, it was concluded that a large lattice vibrational energy, a high formation energy, and a small cell volume are conducive to high emittance. This work provides a strong dataset for training machine-learning models, and it paves the way for further use of this novel methodology to seek efficient phase-change materials for thermal control.
Keyphrases
  • machine learning
  • density functional theory
  • molecular dynamics simulations
  • risk assessment
  • energy transfer
  • deep learning
  • artificial intelligence
  • solar cells
  • high speed
  • virtual reality