Amorphous carbon and its surfaces

Reactivity of Amorphous Carbon Surfaces: Rationalizing the Role of Structural Motifs in Functionalization Using Machine Learning

Systematic atomistic studies of surface reactivity for amorphous materials have not been possible in the past because of the complexity of these materials and the lack of the computer power necessary to draw representative statistics. With the emergence and popularization of machine learning (ML) approaches in materials science, systematic (and accurate) studies of the surface chemistry of disordered materials are now coming within reach. In this paper, we show how the reactivity of amorphous carbon (a-C) surfaces can be systematically quantified and understood by a combination of ML interatomic potentials, ML clustering techniques, and density functional theory calculations. This methodology allows us to process large amounts of atomic data to classify carbon atomic motifs on the basis of their geometry and quantify their reactivity toward hydrogen- and oxygen-containing functionalities. For instance, we identify subdivisions of sp and sp² motifs with markedly different reactivities. We therefore draw a comprehensive, both qualitative and quantitative, picture of the surface chemistry of a-C and its reactivity toward -H, -O, -OH, and -COOH. While this paper focuses on a-C surfaces, the presented methodology opens up a new systematic and general way to study the surface chemistry of amorphous and disordered materials.

Engineering graphene mechanical systems

We report a method to introduce direct bonding between graphene platelets that enables the transformation of a multilayer chemically modified graphene (CMG) film from a "paper mache-like" structure into a stiff, high strength material. On the basis of chemical/defect manipulation and recrystallization, this technique allows wide-range engineering of mechanical properties (stiffness, strength, density, and built-in stress) in ultrathin CMG films. A dramatic increase in the Young's modulus (up to 800 GPa) and enhanced strength (sustainable stress ≥1 GPa) due to cross-linking, in combination with high tensile stress, produced high-performance (quality factor of 31,000 at room temperature) radio frequency nanomechanical resonators. The ability to fine-tune intraplatelet mechanical properties through chemical modification and to locally activate direct carbon-carbon bonding within carbon-based nanomaterials will transform these systems into true "materials-by-design" for nanomechanics.