Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Free, publicly-accessible full text available September 1, 2024
-
Abstract This work presents a new method for processing single-crystal semiconductors designed by a computational method to lower the process temperature. This research study is based on a CALPHAD approach (ThermoCalc) to theoretically design processing parameters by utilizing theoretical phase diagrams. The targeted material composition consists of Bi–Se2–Te–Sb (BSTS). The semiconductor alloy contains three phases, hexagonal, rhombohedral-1, and rhombohedral-2 crystal structures, that are presented in the phase field of the theoretical pseudo-binary phase diagram. The semiconductor is also evaluated by applying Hume–Rothery rules along with the CALPHAD approach. Thermodynamic modelling suggests that single-crystals of BSTS can be grown at significantly lower temperatures and this is experimentally validated by low-temperature growth of single crystalline samples followed by exfoliation, compositional analysis, and diffraction.
-
Free, publicly-accessible full text available May 9, 2024
-
In recent years, multi-phase materials capable of multi-ion transport have emerged as attractive candidates for a variety of electrochemical devices. Here, we provide experimental results for fabricating a composite electrolyte made up of a one-dimensional fast sodium-ion conductor, sodium zirconogallate, and an oxygen-ion conductor, yttria-stabilized zirconia. The composite is synthesized through a vapor phase conversion mechanism, and the kinetics of this process are discussed in detail. The samples are characterized using diffraction, electron microscopy, and electrochemical impedance spectroscopy techniques. Samples with a finer grain structure exhibit higher kinetic rates due to larger three-phase boundaries (TPBs) per unit area. The total conductivity is fitted to an Arrhenius type equation with activation energies ranging from 0.23 eV at temperatures below 550 ° C to 1.07 eV above 550 ° C . The electrochemical performance of multi-phase multi-species, mixed Na + and O 2 − conductor, is tested under both oxygen chemical potential gradient as well as sodium chemical potential gradient are discussed using the Goldman-Hodgkin-Kats (GHK) and the Nernst equation.Free, publicly-accessible full text available November 1, 2023
-
Abstract As the thickness of a three-dimensional (3D) topological insulator (TI) becomes comparable to the penetration depth of surface states, quantum tunneling between surfaces turns their gapless Dirac electronic structure into a gapped spectrum. Whether the surface hybridization gap can host topological edge states is still an open question. Herein, we provide transport evidence of 2D topological states in the quantum tunneling regime of a bulk insulating 3D TI BiSbTeSe2. Different from its trivial insulating phase, this 2D topological state exhibits a finite longitudinal conductance at ~2e2/h when the Fermi level is aligned within the surface gap, indicating an emergent quantum spin Hall (QSH) state. The transition from the QSH to quantum Hall (QH) state in a transverse magnetic field further supports the existence of this distinguished 2D topological phase. In addition, we demonstrate a second route to realize the 2D topological state via surface gap-closing and topological phase transition mechanism mediated by a transverse electric field. The experimental realization of the 2D topological phase in a 3D TI enriches its phase diagram and marks an important step toward functionalized topological quantum devices.
-
A large collection of element-wise planar densities for compounds obtained from the Materials Project is calculated using brute force computational geometry methods, where the planar density is given by the total fractional area of atoms intersecting a supercell's crystallographic plane divided by the area of the supercell's crystallographic plane. It is demonstrated that the element-wise maximum lattice plane densities can be useful as machine learning features. The methods described here are implemented in an open-source Mathematica package hosted at https://github.com/sgbaird/LatticePlane.