Tailoring Magnetism of Graphene Nanoflakes via Tip-Controlled Dehydrogenation.

Atomically precise graphene nanoflakes called nanographenes have emerged as a promising platform to realize carbon magnetism. Their ground state spin configuration can be anticipated by Ovchinnikov-Lieb rules based on the mismatch of π electrons from two sublattices. While rational geometrical design achieves specific spin configurations, further direct control over the π electrons offers a desirable extension for efficient spin manipulations and potential quantum device operations. To this end, we apply a site-specific dehydrogenation using a scanning tunneling microscope tip to nanographenes deposited on a Au(111) substrate, which shows the capability of precisely tailoring the underlying π-electron system and therefore efficiently manipulating their magnetism. Through first-principles calculations and tight-binding mean-field-Hubbard modeling, we demonstrate that the dehydrogenation-induced Au-C bond formation along with the resulting hybridization between frontier π orbitals and Au substrate states effectively eliminate the unpaired π electron. Our results establish an efficient technique for controlling the magnetism of nanographenes.

Hydrogen bonded trimesic acid networks on Cu(111) reveal how basic chemical properties are imprinted in HR-AFM images.

High resolution non-contact atomic force microscopy measurements characterize assemblies of trimesic acid molecules on Cu(111) and the link group interactions, providing the first fingerprints utilizing CO-based probes for this widely studied paradigm for hydrogen bond driven molecular self assembly. The enhanced submolecular resolution offered by this technique uniquely reveals key aspects of the competing interactions. Accurate comparison between full-density-based modeled images and experiment allows to identify key structural elements in the assembly in terms of the electron-withdrawing character of the carboxylic groups, interactions of those groups with Cu atoms in the surface, and the valence electron density in the intermolecular region of the hydrogen bonds. This study of trimesic acid assemblies on Cu(111) combining high resolution atomic force microscopy measurements with theory and simulation forges clear connections between fundamental chemical properties of molecules and key features imprinted in force images with submolecular resolution.

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance.

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.

Materials Cloud, a platform for open computational science.

Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts (1) archival and dissemination services for raw and curated data, together with their provenance graph, (2) modelling services and virtual machines, (3) tools for data analytics, and pre-/post-processing, and (4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow retracing and reproducing any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain.

Near-Enantiopure Trimerization of 9-Ethynylphenanthrene on a Chiral Metal Surface.

Enantioselectivity in heterogeneous catalysis strongly depends on the chirality transfer between catalyst surface and all reactants, intermediates, and the product along the reaction pathway. Herein we report the first enantioselective on-surface synthesis of molecular structures from an initial racemic mixture and without the need of enantiopure modifier molecules. The reaction consists of a trimerization via an unidentified bonding motif of prochiral 9-ethynylphenanthrene (9-EP) upon annealing to 500 K on the chiral Pd3 -terminated PdGa{111} surfaces into essentially enantiopure, homochiral 9-EP propellers. The observed behavior strongly contrasts the reaction of 9-EP on the chiral Pd1 -terminated PdGa{111} surfaces, where 9-EP monomers that are in nearly enantiopure configuration, dimerize without enantiomeric excess. Our findings demonstrate strong chiral recognition and a significant ensemble effect in the PdGa system, hence highlighting the huge potential of chiral intermetallic compounds for enantioselective synthesis and underlining the importance to control the catalytically active sites at the atomic level.

In Silico Discovery of Covalent Organic Frameworks for Carbon Capture.

We screen a database of more than 69 000 hypothetical covalent organic frameworks (COFs) for carbon capture using parasitic energy as a metric. To compute CO2-framework interactions in molecular simulations, we develop a genetic algorithm to tune the charge equilibration method and derive accurate framework partial charges. Nearly 400 COFs are identified with parasitic energy lower than that of an amine scrubbing process using monoethanolamine; more than 70 are better performers than the best experimental COFs and several perform similarly to Mg-MOF-74. We analyze the effect of pore topology on carbon capture performance to guide the development of improved carbon capture materials.

Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent-Organic Frameworks.

We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal's postcombustion flue gases. This workflow is applied to a database of 324 covalent-organic frameworks (COFs) reported in the literature, to characterize their CO2 adsorption properties using the following steps: (1) optimization of the crystal structure (atomic positions and unit cell) using density functional theory, (2) fitting atomic point charges based on the electron density, (3) characterizing the pore geometry of the structures before and after optimization, (4) computing carbon dioxide and nitrogen isotherms using grand canonical Monte Carlo simulations with an empirical interaction potential, and finally, (5) assessing the CO2 parasitic energy via process modeling. The full workflow has been encoded in the Automated Interactive Infrastructure and Database for Computational Science (AiiDA). Both the workflow and the automatically generated provenance graph of our calculations are made available on the Materials Cloud, allowing peers to inspect every input parameter and result along the workflow, download structures and files at intermediate stages, and start their research right from where this work has left off. In particular, our set of CURATED (Clean, Uniform, and Refined with Automatic Tracking from Experimental Database) COFs, having optimized geometry and high-quality DFT-derived point charges, are available for further investigations of gas adsorption properties. We plan to update the database as new COFs are being reported.

On-Surface Synthesis of Antiaromatic and Open-Shell Indeno[2,1-b]fluorene Polymers and Their Lateral Fusion into Porous Ribbons.

Polycyclic hydrocarbons have received great attention due to their potential role in organic electronics and, for open-shell systems with unpaired electron densities, in spintronics and data storage. However, the intrinsic instability of polyradical hydrocarbons severely limits detailed investigations of their electronic structure. Here, we report the on-surface synthesis of conjugated polymers consisting of indeno[2,1-b]fluorene units, which are antiaromatic and open-shell biradicaloids. The observed reaction products, which also include a nonbenzenoid porous ribbon arising from lateral fusion of unprotected indeno[2,1-b]fluorene chains, have been characterized via low-temperature scanning tunneling microscopy/spectroscopy and noncontact atomic force microscopy, complemented by density-functional theory calculations. These polymers present a low band gap when adsorbed on Au(111). Moreover, their pronounced antiaromaticity and radical character, elucidated by ab initio calculations, make them promising candidates for applications in electronics and spintronics. Further, they provide a rich playground to explore magnetism in low-dimensional organic nanomaterials.

On-Surface Synthesis of Indenofluorene Polymers by Oxidative Five-Membered Ring Formation.

On-surface synthesis is a successful approach to the creation of carbon-based nanostructures that cannot be obtained via standard solution chemistry. In this framework, we have established a novel synthetic pathway to one-dimensional conjugated polymers composed of indenofluorene units. Our concept is based on the use of ortho-methyl groups on a poly( para-phenylene) backbone. In this situation, surface-assisted oxidative ring closure between a methyl and the neighboring aryl moiety gives rise to a five-membered ring. The atomically precise structures and electronic properties of the obtained indenofluorene polymers have been unambiguously characterized by STM, nc-AFM, and STS, supported by theoretical calculations. This unprecedented synthetic protocol can potentially be extended to other polyphenylenes and eventually graphene nanoribbons, to incorporate five-membered rings at desired positions for the fine-tuning of electronic properties.

Hidden Beneath the Surface: Origin of the Observed Enantioselective Adsorption on PdGa(111).

We unravel the origin of the recently observed striking enantioselectivity of the PdGa(111) surface with respect to the adsorption of a small organic molecule, 9-ethynylphenanthrene, using first-principles calculations. It turns out that the key ingredient to understand the experimental evidence is the appropriate description of van der Waals interactions beyond the widely employed atomic pairwise approximation. A recently developed van der Waals-inclusive density functional method, which encompasses dielectric screening effects, reveals the origin of the experimentally observed enantioselectivity and provides conclusive evidence of chiral recognition on a bimetallic surface driven by dispersion interactions. The incorporation of dielectric screening leads to a renormalization of the dispersion interaction range, allowing for the appropriate weighting of the molecule-substrate interactions at intermediate distances between 2.5 and 5 Å. Our findings have implications for the structure and stability of complex organic/inorganic systems where dielectric screening effects are expected to be of general importance.