Elucidating The Impact of Niobium Substitution in WSe₂ Nanosheets through Monochromated EELS, 4D-STEM and Deep Neural Networks

Adding an additional degree of freedom to two-dimensional layered materials through alloying emerges as a suitable technique to tailor its thermal and optoelectronic properties. [1] Unfortunately, the relative concentration of the film can change drastically at micron-length scales, [2] making it difficult to directly correlate the true stoichiometry of a material with its respective properties. In this contribution, we first use aberration-corrected scanning transmission electron microscopy (STEM) and 4D-STEM to map out atomic positions in Nb_1-xW_xSe₂ and the crystalline phase of the material. Next, we use monochromated electron energy loss spectroscopy (EELS) to measure lattice phonon modes over a range of the alloying content. Last, with the assistance of deep neural networks, we extract coordinates and type/class of the atoms to correlate localized atomic displacements of atoms in the WSe₂ nanosheet and statistical inference on the atomic distributions. This work aims to help understand the correlation between phase, stoichiometry, and lattice phonon modes in ternary alloys of layered materials.<br/><br/>References<br/>1. J. Yao and G. Yang. “2D Layered Material Alloys: Synthesis and Application in Electronic and Optoelectronic Devices.” Adv. Sci., 9, 2103036, 2022.<br/>2. Y. Zuo et al. “Robust growth of two-dimensional metal dichalcogenides and their alloys by active chalcogen monomer supply.” Nat. Comm., 13, 1007, 2022.