Calculation of the Anisotropic Coefficients of Thermal Expansion: A First-Principles Approach

Predictions of the anisotropic coefficients of thermal expansion are needed to not only compare to experimental measurement, but also as input for macroscopic modeling of devices which operate over a large temperature range. While most current methods are limited to isotropic systems within the quasiharmonic approximation, our method uses first-principles calculations and includes anharmonic effects to determine the temperature-dependent properties of materials. These include the lattice parameters, anisotropic coefficients of thermal expansion, isothermal bulk modulus, and specific heat at constant pressure. Our method has been tested on two compounds (Cu and AlN) and predicts thermal properties which compare favorably to experimental measurement over a wide temperature range.Comment: 8 pages, 9 figures, 1 tabl

Enhancement of thermoelectric properties by energy filtering: Theoretical potential and experimental reality in nanostructured ZnSb

Energy filtering has been suggested by many authors as a means to improve thermoelectric properties. The idea is to filter away low-energy charge carriers in order to increase Seebeck coefficient without compromising electronic conductivity. This concept was investigated in the present paper for a specific material (ZnSb) by a combination of first-principles atomic-scale calculations, Boltzmann transport theory, and experimental studies of the same system. The potential of filtering in this material was first quantified, and it was as an example found that the power factor could be enhanced by an order of magnitude when the filter barrier height was 0.5~eV. Measured values of the Hall carrier concentration in bulk ZnSb were then used to calibrate the transport calculations, and nanostructured ZnSb with average grain size around 70~nm was processed to achieve filtering as suggested previously in the literature. Various scattering mechanisms were employed in the transport calculations and compared with the measured transport properties in nanostructured ZnSb as a function of temperature. Reasonable correspondence between theory and experiment could be achieved when a combination of constant lifetime scattering and energy filtering with a 0.25~eV barrier was employed. However, the difference between bulk and nanostructured samples was not sufficient to justify the introduction of an energy filtering mechanism. The reasons for this and possibilities to achieve filtering were discussed in the paper

The crystal structure of LiMgAlD 6 from combined neutron and synchrotron X-ray powder diffraction

Abstract LiMgAlH 6 is the intermediate phase when LiMg(AlH 4 ) 3 is heated. It contains 9.4 wt.% hydrogen, of which 4.8 wt.% is released during the decomposition step to MgH 2 and LiH. Deuterated LiMgAlD 6 was prepared by heat-treating LiMg(AlD 4 ) 3 at 130 • C. Powder neutron and synchrotron X-ray diffraction patterns were measured and the structure was refined using the Rietveld technique on both patterns simultaneously. LiMgAlD 6 crystallizes in the trigonal space group P321 with a = 7.9856(4)Å and c = 4.3789(3)Å. The structure consists of isolated AlD 6 octahedra connected through octahedrally coordinated Mg-and Li-atoms

Nanocomposites of few-layer graphene oxide and alumina by density functional theory calculations

The atomistic and electronic structure and oxygen stoichiometry of nanocomposites between alumina and graphene oxide were investigated by density functional theory calculations. The nanocomposite was described as interfaces between α-Al2O3 (0001) surfaces and graphene oxide; the latter was defined with oxygen bound as epoxy groups and a C:O atomic ratio of 4:1. The optimized composite structure with 1–3 layers of graphene oxide in between Al2O3 contains bridging Alsingle bondOsingle bondC bonds at the interface. Reduction of the composite was investigated by removal of oxygen from the interface Alsingle bondOsingle bondC bonds, within the graphene oxide layers and in Al2O3. It was found that removal of oxygen within the graphene oxide layers is essentially independent of the Al2O3 interface, i.e., the same as in pure graphene oxide. Oxygen was, however, more strongly bound in the interface Alsingle bondOsingle bondC bonds by 0.80 eV, and reduction of graphene oxide to graphene is accordingly preferred within the graphene oxide layers rather than at the oxide interface.acceptedVersio

Machine Learning for Novel Thermal-Materials Discovery: Early Successes, Opportunities, and Challenges

High-throughput computational and experimental design of materials aided by machine learning have become an increasingly important field in material science. This area of research has emerged in leaps and bounds in the thermal sciences, in part due to the advances in computational and experimental methods in obtaining thermal properties of materials. In this paper, we provide a current overview of some of the recent work and highlight the challenges and opportunities that are ahead of us in this field. In particular, we focus on the use of machine learning and high-throughput methods for screening of thermal conductivity for compounds, composites and alloys as well as interfacial thermal conductance. These new tools have brought about a feedback mechanism for understanding new correlations and identifying new descriptors, speeding up the discovery of novel thermal functional materials. ©2018Basic Science Center Program for Ordered Energy Conversion of the National Natural Science Foundation of China (No. 51888103)A*Star's Science and Engineering Research Council, on Accelerating Materials Development for Manufacturing (project no: A1898b0043)A*Star's AME Young Independent Research Grant project (no. A1884c0020