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Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We successfully interface off-the-shelf battery cycling hardware with the computational workflow management software AiiDA, allowing us to control experiments, while ensuring trust in the data by tracking its provenance. We design user interfaces compatible with this tooling, which span the inventory, experiment design, and result analysis stages. Other features, including monitoring of workflows and import of externally generated and legacy data are also implemented. Finally, the full software stack required for this work is made available in a set of open-source packages., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

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.

We employ X-ray absorption near-edge spectroscopy at the boron K-edge and the phosphorus L 2,3 -edge to study the structural properties of cubic boron phosphide (c-BP) samples. The X-ray absorption spectra are modeled from first-principles within the density functional theory framework using the excited electron core-hole (XCH) approach. A simple structural model of a perfect c-BP crystal accurately reproduces the P L 2,3 -edge, however it fails to describe the broad and gradual onset of the B K-edge. Simulations of the spectroscopic signatures in boron 1s excitations of intrinsic point defects and the hexagonal BP crystal phase show that these additions to the structural model cannot reproduce the broad pre-edge of the experimental spectrum. Calculated formation enthalpies show that, during the growth of c-BP, it is possible that amorphous boron phases can be grown in conjunction with the desired boron phosphide crystalline phase. In combination with experimental and theoretically obtained X-ray absorption spectra of an amorphous boron structure, which have a similar broad absorption onset in the B K-edge spectrum as the cubic boron phosphide samples, we provide evidence for the presence of amorphous boron clusters in the synthesized c-BP samples.

We present theoretically derived design rules for an absorbing resonance antireflection coating for the spectral range of 100 - 400 nm, applied here on top of a molybdenum-silicon multilayer mirror (Mo/Si MLM) as commonly used in extreme ultraviolet lithography. The design rules for optimal suppression are found to be strongly dependent on the thickness and optical constants of the coating. For wavelengths below λ ∼ 230 nm, absorbing thin films can be used to generate an additional phase shift and complement the propagational phase shift, enabling full suppression already with film thicknesses far below the quarter-wave limit. Above λ ∼ 230 nm, minimal absorption (k < 0.2) is necessary for low reflectance and the minimum required layer thickness increases with increasing wavelength slowly converging towards the quarter-wave limit.As a proof of principle, SixCyNz thin films were deposited that exhibit optical constants close to the design rules for suppression around 285 nm. The thin films were deposited by electron beam co-deposition of silicon and carbon, with N+ ion implantation during growth and analyzed with variable angle spectroscopic ellipsometry to characterize the optical constants. We report a reduction of reflectance at λ = 285 nm, from 58% to 0.3% for a Mo/Si MLM coated with a 20 nm thin film of Si0.52C0.16N0.29.