Johannes T. Margraf

We report the characterization of carbon nanodots (CNDs) synthesized under mild and controlled conditions, that is, in a microwave reactor. The CNDs thus synthesized exhibit homogeneous and narrowly dispersed optical properties. They are thus well suited as a testbed for studies of the photophysics of carbon-based nanoscopic emitters. In addition to steady-state investigations, time-correlated single-photon counting, fluorescence up-conversion, and transient pump probe absorption spectroscopy were used to elucidate the excited-state dynamics. Moreover, quenching the CND-based emission with electron donors or acceptors helped shed light on the nature of individual states. Density functional theory and semiempirical configuration-interaction calculations on model systems helped understand the fundamental structure-property relationships for this novel type of material.

Covalent organic frameworks (COFs), formed by reversible condensation of rigid organic building blocks, are crystalline and porous materials of great potential for catalysis and organic electronics. Particularly with a view of organic electronics, achieving a maximum degree of crystallinity and large domain sizes while allowing for a tightly π-stacked topology would be highly desirable. We present a design concept that uses the 3D geometry of the building blocks to generate a lattice of uniquely defined docking sites for the attachment of consecutive layers, thus allowing us to achieve a greatly improved degree of order within a given average number of attachment and detachment cycles during COF growth. Synchronization of the molecular geometry across several hundred nanometers promotes the growth of highly crystalline frameworks with unprecedented domain sizes. Spectroscopic data indicate considerable delocalization of excitations along the π-stacked columns and the feasibility of donor-acceptor excitations across the imine bonds. The frameworks developed in this study can serve as a blueprint for the design of a broad range of tailor-made 2D COFs with extended π-conjugated building blocks for applications in photocatalysis and optoelectronics.

Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early ML force fields have largely been limited by: (i) the substantial computational and human effort of developing and validating potentials for each particular system of interest; and (ii) a general lack of transferability from one chemical system to the next. Here we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model - and its qualitative and at times quantitative accuracy - on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces and even the dynamics of a small protein. The model can be applied out of the box as a starting or "foundation" model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users get reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step towards democratising the revolution in atomic-scale modeling that has been brought about by ML force fields.