mDCThermalC is a program written in Python for computing lattice thermal conductivity of crystalline bulk materials using the modified Debye-Callaway model. Building upon the traditional Debye-Callaway theory, the modified model obtains the lattice thermal conductivity by averaging the contributions from acoustic and optical branches based on their specific heat. The only inputs of this program are the phonon spectrum, phonon velocity and Grneisen parameter, all of which can be calculated using third-party ab initio packages, making the method fully parameter-free. This leads to a fast and accurate evaluation and enables high-throughput calculations of lattice thermal conductivity even in large and complex systems. In addition, this program calculates the specific heat and phonon relaxation times for different scattering processes, which will be beneficial for understanding the phonon transfer behavior.harmonic approximation requires a large number of calculations to construct the third-order force constants matrix, which could be prohibitively long time. Solution method: modified Debye-Callaway model, only phonon spectrum, phonon velocity and Grneisen parameter are needed. The acoustic branch and optic branch are both considered to obtain the final lattice thermal conductivity.
Efficient thermoelectric materials are highly desirable, and the quest for finding them has intensified as they could be promising alternatives to fossil energy sources. Here we present a general first-principles approach to predict, in multicomponent systems, efficient thermoelectric compounds. The method combines a robust evolutionary algorithm, a Pareto multiobjective optimization, density functional theory and a Boltzmann semi-classical calculation of thermoelectric efficiency. To test the performance and reliability of our overall framework, we use the well-known system Bi2Te3-Sb2Te3.
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