High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation.

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases.

OPTIMADE, an API for exchanging materials data.

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages.

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution.

Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for. Computational modeling can aim to fulfill this expectation, thanks to the sustained growth of computing power and the collective engagement of the scientific community in developing more efficient and accurate workflows for predicting materials' performances.

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.

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 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 CO-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.

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 CO 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 CO parasitic energy via process modeling. The full workflow has been encoded in the Automated Interactive Infrastructure and Database for Computational Science (AiiDA).

Band Gap of Atomically Precise Graphene Nanoribbons as a Function of Ribbon Length and Termination.

We study the band gap of finite armchair graphene nanoribbons (7-AGNRs) on Au(111) through scanning tunneling microscopy/spectroscopy combined with density functional theory calculations. The band gap of 7-AGNRs with lengths of 8 nm and more is converged to within 50 meV of its bulk value of , while the band gap opens by several hundred meV in very short 7-AGNRs. We demonstrate that even an atomic defect, such as the addition of one hydrogen atom at the termini, has a significant effect - in this case, lowering the band gap.

Capturing chemical intuition in synthesis of metal-organic frameworks.

We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal-organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date.

Toward GW Calculations on Thousands of Atoms.

The GW approximation of many-body perturbation theory is an accurate method for computing electron addition and removal energies of molecules and solids. In a canonical implementation, however, its computational cost is [Formula: see text] in the system size N, which prohibits its application to many systems of interest. We present a full-frequency GW algorithm in a Gaussian-type basis, whose computational cost scales with N to N.

On-Surface Synthesis and Characterization of 9-Atom Wide Armchair Graphene Nanoribbons.

The bottom-up approach to synthesize graphene nanoribbons strives not only to introduce a band gap into the electronic structure of graphene but also to accurately tune its value by designing both the width and edge structure of the ribbons with atomic precision. We report the synthesis of an armchair graphene nanoribbon with a width of nine carbon atoms on Au(111) through surface-assisted aryl-aryl coupling and subsequent cyclodehydrogenation of a properly chosen molecular precursor. By combining high-resolution atomic force microscopy, scanning tunneling microscopy, and Raman spectroscopy, we demonstrate that the atomic structure of the fabricated ribbons is exactly as designed.

Giant edge state splitting at atomically precise graphene zigzag edges.

Zigzag edges of graphene nanostructures host localized electronic states that are predicted to be spin-polarized. However, these edge states are highly susceptible to edge roughness and interaction with a supporting substrate, complicating the study of their intrinsic electronic and magnetic structure. Here, we focus on atomically precise graphene nanoribbons whose two short zigzag edges host exactly one localized electron each.

On-surface synthesis of graphene nanoribbons with zigzag edge topology.

Graphene-based nanostructures exhibit electronic properties that are not present in extended graphene. For example, quantum confinement in carbon nanotubes and armchair graphene nanoribbons leads to the opening of substantial electronic bandgaps that are directly linked to their structural boundary conditions. Nanostructures with zigzag edges are expected to host spin-polarized electronic edge states and can thus serve as key elements for graphene-based spintronics.

On-Surface Synthesis of Atomically Precise Graphene Nanoribbons.

The surface-assisted polymerization and cyclodehydrogenation of specifically designed organic precursors provides a route toward atomically precise graphene nanoribbons, which promises to combine the outstanding electronic properties of graphene with a bandgap that is sufficiently large for room-temperature digital-logic applications. Starting from the basic concepts behind the on-surface synthesis approach, this report covers the progress made in understanding the different reaction steps, in synthesizing atomically precise graphene nanoribbons of various widths and edge structures, and in characterizing their properties, ending with an outlook on the challenges that still lie ahead.

On-Surface Synthesis of BN-Substituted Heteroaromatic Networks.

We report on the bottom-up fabrication of BN-substituted heteroaromatic networks achieved by surface-assisted polymerization and subsequent cyclodehydrogenation of specifically designed BN-substituted precursor monomers based on a borazine core structural element. To get insight into the cyclodehydrogenation pathway and the influence of molecular flexibility on network quality, two closely related precursor monomers with different degrees of internal cyclodehydrogenation have been employed. Scanning tunneling microscopy shows that, for both monomers, surface-assisted cyclodehydrogenation allows for complete monomer cyclization and the formation of covalently interlinked BN-substituted polyaromatic hydrocarbon networks on the Ag(111) surface.

Graphene nanoribbon heterojunctions.

Despite graphene's remarkable electronic properties, the lack of an electronic bandgap severely limits its potential for applications in digital electronics. In contrast to extended films, narrow strips of graphene (called graphene nanoribbons) are semiconductors through quantum confinement, with a bandgap that can be tuned as a function of the nanoribbon width and edge structure. Atomically precise graphene nanoribbons can be obtained via a bottom-up approach based on the surface-assisted assembly of molecular precursors.

Termini of bottom-up fabricated graphene nanoribbons.

Atomically precise graphene nanoribbons (GNRs) can be obtained via thermally induced polymerization of suitable precursor molecules on a metal surface. This communication discusses the atomic structure found at the termini of armchair GNRs obtained via this bottom-up approach. The short zigzag edge at the termini of the GNRs under study gives rise to a localized midgap state with a characteristic signature in scanning tunneling microscopy (STM).