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.
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 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.
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.
Near‐enantiopure trimerization of an initial racemic mixture of prochiral molecules proceeds on an intrinsically chiral intermetallic PdGa{111} surface. This process demonstrates the immense potential of PdGa for asymmetric heterogeneous catalysis.
Abstract
The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available ...simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.
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