Vertical Conductivity and Topography in Electrostrictive Germanium Sulfide Microribbon via Conductive Atomic Force Microscopy.

Layered group IV monochalcogenides are two-dimensional (2D) semiconducting materials with unique crystal structures and novel physical properties. Here, we report the growth of single crystalline GeS microribbons using the chemical vapor transport process. By using conductive atomic force microscopy, we demonstrated that the conductive behavior in the vertical direction was mainly affected by the Schottky barriers between GeS and both electrodes. Furthermore, we found that the topographic and current heterogeneities were significantly different with and without illumination. The topographic deformation and current enhancement were also predicted by our density functional theory (DFT)-based calculations. Their local spatial correlation between the topographic height and current was established. By virtue of 2D fast Fourier transform power spectra, we constructed the holistic spatial correlation between the topographic and current heterogeneity that indicated the diminished correlation with illumination. These findings on layered GeS microribbons provide insights into the conductive and topographic behaviors in 2D materials.

Using Feature-Assisted Machine Learning Algorithms to Boost Polarity in Lead-Free Multicomponent Niobate Alloys for High-Performance Ferroelectrics.

To expand the unchartered materials space of lead-free ferroelectrics for smart digital technologies, tuning their compositional complexity via multicomponent alloying allows access to enhanced polar properties. The role of isovalent A-site in binary potassium niobate alloys, (K,A)NbO3 using first-principles calculations is investigated. Specifically, various alloy compositions of (K,A)NbO3 are considered and their mixing thermodynamics and associated polar properties are examined. To establish structure-property design rules for high-performance ferroelectrics, the sure independence screening sparsifying operator (SISSO) method is employed to extract key features to explain the A-site driven polarization in (K,A)NbO3 . Using a new metric of agreement via feature-assisted regression and classification, the SISSO model is further extended to predict A-site driven polarization in multicomponent systems as a function of alloy composition, reducing the prediction errors to less than 1%. With the machine learning model outlined in this work, a polarity-composition map is established to aid the development of new multicomponent lead-free polar oxides which can offer up to 25% boosting in A-site driven polarization and achieving more than 150% of the total polarization in pristine KNbO3 . This study offers a design-based rational route to develop lead-free multicomponent ferroelectric oxides for niche information technologies.

Going beyond the equilibrium crystal shape: re-tracing the morphological evolution in group 5 tetradymite nanocrystals.

Nanocrystals of group 5 tetradymites M2X3 (where M = Bi and Sb, X = Se and Te) are of high technological relevance in modern topological nanoelectronics. However, there is a current lack of a systematic understanding to predict the preferred nanocrystal morphology in experiments where commonly-used equilibrium thermodynamic models appear to fail. In this work, using first-principles DFT calculations with a rationally-extended ab initio atomistic thermodynamics approach coupled to implicit solvation models and Gibbs-Wulff shape constructions, we demonstrate that this absence of predictive power stems from the limitation of equilibrium thermodynamics. By re-tracing and carefully addressing with a more realistic chemical potential definition, we illustrate this shortcoming can be overcome and afford a more rational route to size-engineer and shape-design highly-functional group 5 tetradymite nanoparticles for targeted applications.