Charting the Lattice Thermal Conductivities of I–III–VI₂ Chalcopyrite Semiconductors

Abstract

Chalcopyrite-structured semiconductors have promising potential as low-cost thermoelectric materials, but their thermoelectric figures of merit must be increased for practical applications. Understanding their thermal properties is important for engineering their thermal conductivities and achieving better thermoelectric behavior. We present here a theoretical investigation of the lattice thermal conductivities of 20 chalcopyrite semiconductors with an ABX 2 composition (I−III−VI 2 ) (A = Cu or Ag; B = Al, Ga, In, or Tl; X = S, Se, or Te). To afford accurate predictions across this large family of compounds, we solve the Boltzmann transport equation with force constants derived from density functional theory calculations and machine learning-based regression algorithms, reducing by between 1 and 2 orders of magnitude the computational cost with respect to conventional approaches of the same accuracy. The results are in good agreement with available experimental data and allow us to rationalize the role of chemical composition, temperature, and nanostructuring in the thermal conductivities across this important family of semiconductors.

Enhanced Thermoelectric Efficiency through Li-Induced Phonon Softening in CuGaTe2

“…However, the mid-range optical phonons (∼12–18 meV) also have a large dispersion and high group velocities. The acoustic and low-frequency optical modes agree well with previously reported calculated values. ,,− The high acoustic and low-frequency optical phonon velocities are the principal reason that the room temperature thermal conductivity of pristine CuGaTe 2 is higher than the desired range for thermoelectric materials. However, the high-frequency optical modes exhibit a significantly lower frequency than experimental frequencies from Raman and infrared spectroscopy (Table S1).…”

“…A slightly lower thermal conductivity (∼5%) was predicted without the Hubbard- U correction than with the correction (Figure b). The lattice thermal conductivity of CuGaTe 2 was also recently computed using a machine learning-based approach and ShengBTE which overestimated the lattice thermal conductivity by more than 50% . The present calculation indicates a noteworthy enhancement in the lattice thermal conductivity prediction.…”

Unraveling the role of chemical composition in the lattice thermal conductivity of oxychalcogenides as thermoelectric materials

“…For instance, I–III–VI 2 chalcopyrite semiconductors follows a nonmonotonous variation of κ l , with selenides being the materials with the lowest values. 36 Substituting Se by S brings strong modifications in the phonon density of states, DOS (Fig. 2a and b).…”

“…The amplitude of the distortions applied to the atoms plays an important role in the calculation of the IFCS so a 2 steps approach was designed. 36 First, small random distortions were generated for all the atoms of 3 supercells and second and third-order IFCs were calculated using the HiPhive package. Then, eight new distorted supercells were created superimposing normal modes with random phase factors and amplitudes corresponding to 300 K. The recursive feature elimination RFE, algorithm was used to obtain the force constants from the DFT forces.…”

“…We have used a wrapper code for the hiPhive program that automates the distorted supercell creation, force calculation using VASP, and the construction of the ML IFCs, which is available for public use. 36,37…”