High throughput combinatorial method for fast and robust prediction of lattice thermal conductivity

Pinku Nath, Jose J. Plata, Demet Usanmaz, Cormac Toher, Marco Fornari, Marco Buongiorno Nardelli, Stefano Curtarolo

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


The lack of computationally inexpensive and accurate ab-initio based methodologies to predict lattice thermal conductivity, without computing the anharmonic force constants or time-consuming ab-initio molecular dynamics, is one of the obstacles preventing the accelerated discovery of new high or low thermal conductivity materials. The Slack equation is the best alternative to other more expensive methodologies but is highly dependent on two variables: the acoustic Debye temperature, θa, and the Grüneisen parameter, γ. Furthermore, different definitions can be used for these two quantities depending on the model or approximation. In this article, we present a combinatorial approach to elucidate which definitions of both variables produce the best predictions of the lattice thermal conductivity, κl. A set of 42 compounds was used to test the accuracy and robustness of all possible combinations. This approach is ideal for obtaining more accurate values than fast screening models based on the Debye model, while being significantly less expensive than methodologies that solve the Boltzmann transport equation.

Original languageEnglish
Pages (from-to)88-93
Number of pages6
JournalScripta Materialia
StatePublished - Mar 1 2017


  • Accelerated materials development
  • High-throughput
  • Lattice thermal conductivity
  • Quasi-harmonic approximation


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