We introduce atomate, an open-source Python framework for computational materials science simulation, analysis, and design with an emphasis on automation and extensibility. Built on top of open source Python packages already in use by the materials community such as pymatgen, FireWorks, and custodian, atomate provides well-tested workflow templates to compute various materials properties such as electronic bandstructure, elastic properties, and piezoelectric, dielectric, and ferroelectric properties. Atomate also enables the computational characterization of materials by providing workflows that calculate X-ray absorption (XAS), Electron energy loss (EELS) and Raman spectra. One of the major features of atomate is that it provides both fully functional workflows as well as reusable components that enable one to compose complex materials science workflows that use a diverse set of computational tools. Additionally, atomate creates output databases that organize the results from individual calculations and contains a builder framework that creates summary reports for each computed material based on multiple simulations.

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Thermoelectric effects, measured by the Seebeck coefficients, refer to the phenomena in which a temperature difference or gradient imposed across a thermoelectric material induces an electrical potential difference or gradient, and vice versa, enabling the direct conversion of thermal and electric energies. All existing understanding and first-principles calculations of Seebeck coefficients have been based on the Boltzmann kinetic transport theory. Here we demonstrate that the Seebeck coefficient is a well-defined thermodynamic quantity that can be determined from the change in the chemical potential of electrons induced by the temperature change and thus can be efficiently computed solely based on the electronic density of states through first-principles calculations at different temperatures. The proposed approach is demonstrated using the prototype PbTe and SnSe thermoelectric materials. The proposed thermodynamic approach dramatically simplifies the calculations of Seebeck coefficients, making it possible to search for high performance thermoelectric materials using highthroughput first-principles calculations. + yuw3@psu.edu; * lqc3@psu.edu

The software package ESPEI has been developed for efficient evaluation of thermodynamic model parameters within the CALPHAD method. ESPEI uses a linear fitting strategy to parameterize Gibbs energy functions of single phases based on their thermochemical data and refine the model parameters using phase equilibrium data through Bayesian optimization within a Markov Chain Monte Carlo machine learning approach. In this paper, the methodologies employed in ESPEI are discussed in detail and demonstrated for the Cu-Mg system down to 0 K using unary descriptions based on segmented regression. The model parameter uncertainties are quantified and propagated to the Gibbs energy functions. a − J J J , where J is the chemical potential of the target hyperplane calculated in step 1.

We have conducted a comprehensive thermodynamic analysis of the volatility of 128 binary oxides to evaluate their suitability as source materials for oxide molecular-beam epitaxy (MBE). 16 solid or liquid oxides are identified that evaporate nearly congruently from stable oxide sources to gas species: As2O3, B2O3, BaO, MoO3, OsO4, P2O5, PbO, PuO2, Rb2O, Re2O7, Sb2O3, SeO2, SnO, ThO2, Tl2O, and WO3. An additional 24 oxides could provide molecular beams with dominant gas species of CeO, Cs2O, DyO, ErO, Ga2O, GdO, GeO, HfO, HoO, In2O, LaO, LuO, NdO, PmO, PrO, PuO, ScO, SiO, SmO, TbO, Te2O2, U2O6, VO2, and YO2. The present findings are in close accord with available experimental results in the literature. For example, As2O3, B2O3, BaO, MoO3, PbO, Sb2O3, and WO3 are the only oxides in the ideal category that have been used in MBE. The remaining oxides deemed ideal for MBE awaiting experimental verification. We also consider two-phase mixtures as a route to achieve the desired congruent evaporation characteristic of an ideal MBE source. These include (Ga2O3 + Ga) to produce a molecular beam of Ga2O(g), (GeO2 + Ge) to produce GeO(g), (SiO2 + Si) to produce SiO(g), (SnO2 + Sn) to produce SnO(g), etc.; these suboxide sources enable suboxide MBE. Our analysis provides the vapor pressures of the gas species over the condensed phases of 128 binary oxides, which may be either solid or liquid depending on the melting temperature.