Switching it up: New mechanisms revealed in wurtzite-type ferroelectrics.

Wurtzite-type ferroelectrics have drawn increasing attention due to the promise of better performance and integration than traditional oxide ferroelectrics with semiconductors such as Si, SiC, and III-V compounds. However, wurtzite-type ferroelectrics generally require enormous electric fields, approaching breakdown, to reverse their polarization. The underlying switching mechanism(s), especially for multinary compounds and alloys, remains elusive.

A database of computed Raman spectra of inorganic compounds with accurate hybrid functionals.

Raman spectroscopy is widely applied in identifying local structures in materials, but the interpretation of Raman spectra is non-trivial. An accurate computational database of reference spectra calculated with a consistent level of theory can significantly aid in interpreting measured Raman spectra. Here, we present a database of Raman spectra of inorganic compounds calculated with accurate hybrid functionals in density functional theory.

Material descriptors for thermoelectric performance of narrow-gap semiconductors and semimetals.

Thermoelectric (TE) cooling is an environment-friendly alternative to vapor compression cooling. New TE materials with high coefficients of performance are needed to further advance this technology. Narrow-gap semiconductors and semimetals have garnered interest for Peltier cooling, yet large-scale computational searches often rely on material descriptors that do not account for bipolar conduction effects.

A search for new back contacts for CdTe solar cells.

There is widespread interest in reaching the practical efficiency of cadmium telluride (CdTe) thin-film solar cells, which suffer from open-circuit voltage loss due to high surface recombination velocity and Schottky barrier at the back contact. Here, we focus on back contacts in the superstrate configuration with the goal of finding new materials that can provide improved passivation, electron reflection, and hole transport properties compared to the commonly used material, ZnTe. We performed a computational search among 229 binary and ternary tetrahedrally bonded structures using first-principles methods and transport models to evaluate critical material design criteria, including phase stability, electronic structure, hole transport, band alignments, and p-type dopability.

YTe: A New n-Type Thermoelectric Material.

Rare-earth chalcogenides ( = La, Pr, Nd, = S, Se, and Te) have been extensively studied as high-temperature thermoelectric (TE) materials owing to their low lattice thermal conductivity (κ) and tunable electron carrier concentration cation vacancies. In this work, we introduce YTe, a rare-earth chalcogenide with a rocksalt-like vacancy-ordered structure, as a promising n-type TE material. We computationally evaluate the transport properties, optimized TE performance, and doping characteristics of YTe.

Computational design of thermoelectric alloys through optimization of transport and dopability.

Alloying is a common technique to optimize the functional properties of materials for thermoelectrics, photovoltaics, energy storage Designing thermoelectric (TE) alloys is especially challenging because it is a multi-property optimization problem, where the properties that contribute to high TE performance are interdependent. In this work, we develop a computational framework that combines first-principles calculations with alloy and point defect modeling to identify alloy compositions that optimize the electronic, thermal, and defect properties. We apply this framework to design n-type BaSrCdP Zintl thermoelectric alloys.

Predicting energy and stability of known and hypothetical crystals using graph neural network.

The discovery of new inorganic materials in unexplored chemical spaces necessitates calculating total energy quickly and with sufficient accuracy. Machine learning models that provide such a capability for both ground-state (GS) and higher-energy structures would be instrumental in accelerated screening. Here, we demonstrate the importance of a balanced training dataset of GS and higher-energy structures to accurately predict total energies using a generic graph neural network architecture.

Thermoelectricity in transition metal compounds: the role of spin disorder.

At room temperature and above, most magnetic materials adopt a spin-disordered (paramagnetic) state whose electronic properties can differ significantly from their low-temperature, spin-ordered counterparts. Yet computational searches for new functional materials usually assume some type of magnetic order. In the present work, we demonstrate a methodology to incorporate spin disorder in computational searches and predict the electronic properties of the paramagnetic phase.

Mechanism and energetics of O and O2 adsorption on polar and non-polar ZnO surfaces.

Polar surfaces of semiconducting metal oxides can exhibit structures and chemical reactivities that are distinct from their non-polar surfaces. Using first-principles calculations, we examine O adatom and O2 molecule adsorption on 8 different known ZnO reconstructions including Zn-terminated (Zn-ZnO) and O-terminated (O-ZnO) polar surfaces, and non-polar surfaces. We find that adsorption tendencies are largely governed by the thermodynamic environment, but exhibit variations due to the different surface chemistries of various reconstructions.

A novel, layered phase in Ti-rich SrTiO3 epitaxial thin films.

Sr2Ti7O14, a new phase, is synthesized by leveraging the innate chemical and thermo-dynamic instabilities in the SrTiO3-TiO2 system and non-equilibrium growth techniques. The chemical composition, epitaxial relationships, and orientation play roles in the formation of this novel layered phase, which, in turn, possesses unusual charge ordering, anti-ferromagnetic ordering, and low, glass-like thermal conductivity.