Is Charge-Transfer Doping Possible at the Interfaces of Monolayer VSe2 with MoO3 and K?

When Machine Learning Meets 2D Materials: A Review

The availability of an ever-expanding portfolio of 2D materials with rich internal degrees of freedom (spin, excitonic, valley, sublattice, and layer pseudospin) together with the unique ability to tailor heterostructures made layer by layer in a precisely chosen stacking sequence and relative crystallographic alignments, offers an unprecedented platform for realizing materials by design. However, the breadth of multi-dimensional parameter space and massive data sets involved is emblematic of complex, resource-intensive experimentation, which not only challenges the current state of the art but also renders exhaustive sampling untenable. To this end, machine learning, a very powerful data-driven approach and subset of artificial intelligence, is a potential game-changer, enabling a cheaper - yet more efficient - alternative to traditional computational strategies. It is also a new paradigm for autonomous experimentation for accelerated discovery and machine-assisted design of functional 2D materials and heterostructures. Here, the study reviews the recent progress and challenges of such endeavors, and highlight various emerging opportunities in this frontier research area.

Two-Dimensional Crystals as a Buffer Layer for High Work Function Applications: The Case of Monolayer MoO3

We propose that the crystallinity of two-dimensional (2D) materials is a crucial factor for achieving highly effective work function (WF) modification. A crystalline 2D MoO₃ monolayer enhances substrate WF up to 6.4 eV for thicknesses as low as 0.7 nm. Such a high WF makes 2D MoO₃ a great candidate for tuning properties of anode materials and for the future design of organic electronic devices, where accurate evaluation of the WF is crucial. We provide a detailed investigation of WF of 2D α-MoO₃ directly grown on highly ordered pyrolytic graphite, by means of Kelvin probe force microscopy (KPFM) and ultraviolet photoemission spectroscopy (UPS). This study underlines the importance of a controlled environment and the resulting crystallinity to achieve high WF in MoO₃. UPS is proved to be suitable for determining higher WF attributed to 2D islands on a substrate with lower WF, yet only in particular cases of sufficient coverage. KPFM remains a method of choice for nanoscale investigations, especially when conducted under ultrahigh vacuum conditions. Our experimental results are supported by density functional theory calculations of electrostatic potential, which indicate that oxygen vacancies result in anisotropy of WF at the sides of the MoO₃ monolayer. These novel insights into the electronic properties of 2D-MoO₃ are promising for the design of electronic devices with high WF monolayer films, preserving the transparency and flexibility of the systems.