Elucidating the Mechanism of Large Phosphate Molecule Intercalation Through Graphene-Substrate Heterointerfaces.

Intercalation is the process of inserting chemical species into the heterointerfaces of two-dimensional (2D) layered materials. While much research has focused on the intercalation of metals and small gas molecules into graphene, the intercalation of larger molecules through the basal plane of graphene remains challenging. In this work, we present a new mechanism for intercalating large molecules through monolayer graphene to form confined oxide materials at the graphene-substrate heterointerface. We investigate the intercalation of phosphorus pentoxide (P2O5) molecules directly from the vapor phase and confirm the formation of confined P2O5 at the graphene-substrate heterointerface using various techniques. Density functional theory (DFT) corroborates the experimental results and reveals the intercalation mechanism, whereby P2O5 dissociates into small fragments catalyzed by defects in the graphene that then permeates through lattice defects and reacts at the heterointerface to form P2O5. This process can also be used to form new confined metal phosphates (e.g., 2D InPO4). While the focus of this study is on P2O5 intercalation, the possibility of intercalation from predissociated molecules catalyzed by defects in graphene may exist for other types of molecules as well. This in-depth study advances our understanding of intercalation routes of large molecules via the basal plane of graphene as well as heterointerface chemical reactions leading to the formation of distinctive confined complex oxide compounds.

Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery.

Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. We trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.

Defect identification and statistics toolbox: automated defect analysis for scanning probe microscopy images.

Identifying and classifying defects in scanning probe microscopy (SPM) images is an important task that is tedious to perform by hand. In this paper we present the defect identification and statistics toolbox (DIST), an image processing toolbox for identifying and analyzing atomic defects in SPM images. DIST combines automation with user input to accurately and efficiently identify defects and automatically compute critical statistics. We describe using DIST for interactive image processing, generating contour plots for isolating extrema from an image background, and processes for identifying defects.

Progress, challenges, and opportunities in two-dimensional materials beyond graphene.

Graphene's success has shown that it is possible to create stable, single and few-atom-thick layers of van der Waals materials, and also that these materials can exhibit fascinating and technologically useful properties. Here we review the state-of-the-art of 2D materials beyond graphene. Initially, we will outline the different chemical classes of 2D materials and discuss the various strategies to prepare single-layer, few-layer, and multilayer assembly materials in solution, on substrates, and on the wafer scale. Additionally, we present an experimental guide for identifying and characterizing single-layer-thick materials, as well as outlining emerging techniques that yield both local and global information. We describe the differences that occur in the electronic structure between the bulk and the single layer and discuss various methods of tuning their electronic properties by manipulating the surface. Finally, we highlight the properties and advantages of single-, few-, and many-layer 2D materials in field-effect transistors, spin- and valley-tronics, thermoelectrics, and topological insulators, among many other applications.