Scale-invariant machine-learning model accelerates the discovery of quaternary chalcogenides with ultralow lattice thermal conductivity

We design an advanced machine-learning(ML)model based on crystal graph convolutional neural network that is insensitive to volumes(i.e.,scale)of the input crystal structures to discover novel quaternary chalcogenides,AMM′Q3(A/M/M'=alkali,alkaline earth,post-transition metals,lanthanides,and Q=chalcogens).These compounds are shown to possess ultralow lattice thermal conductivity(κ_(l)),a desired requirement for thermal-barrier coatings and thermoelectrics.Upon screening the thermodynamic stability of~1 million compounds using the ML model iteratively and performing density-functional theory(DFT)calculations for a small fraction of compounds,we discover 99 compounds that are validated to be stable in DFT.Taking several DFT-stable compounds,we calculate theirκl using Peierls–Boltzmann transport equation,which reveals ultralowκ_(l)(<2 Wm^(−1)K^(−1)at room temperature)due to their soft elasticity and strong phonon anharmonicity.Our work demonstrates the high efficiency of scale-invariant ML model in predicting novel compounds and presents experimental-research opportunities with these new compounds.

Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity

The development of efficient thermal energy management devices such as thermoelectrics and barrier coatings often relies on compounds having low lattice thermal conductivity(κl).Here,we present the computational discovery of a large family of 628 thermodynamically stable quaternary chalcogenides,AMM′Q_(3)(A=alkali/alkaline earth/post-transition metals;M/M′=transition metals,lanthanides;Q=chalcogens)using high-throughput density functional theory(DFT)calculations.We validate the presence of lowκl in these materials by calculatingκl of several predicted stable compounds using the Peierls–Boltzmann transport equation.Our analysis reveals that the lowκl originates from the presence of either a strong lattice anharmonicity that enhances the phononscatterings or rattler cations that lead to multiple scattering channels in their crystal structures.Our thermoelectric calculations indicate that some of the predicted semiconductors may possess high energy conversion efficiency with their figure-of-merits exceeding 1 near 600 K.Our predictions suggest experimental research opportunities in the synthesis and characterization of these stable,low κ_(l) compounds.