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The CCQM-K148.a comparison was coordinated by the BIPM on behalf of the CCQM Organic Analysis Working Group for NMIs and DIs which provide measurement services in organic analysis under the CIPM MRA. It was undertaken as a "Track A" comparison within the OAWG strategic plan. CCQM-K148.a demonstrates capabilities for assigning the mass fraction content of a solid organic compound having moderate molecular complexity, where the compound has a molar mass in the range (75 - 500) g/mol and is non-polar (pKow < −2), when present as the primary organic component in a neat organic solid and where the mass fraction content of the primary component in the material is in excess of 950 mg/g.
Participants were required to report the mass fraction of Bisphenol A present in one supplied unit of the comparison material. Participants using a mass balance method for the assignment were also required to report their assignments of the impurity components present in the material. Methods used by the seventeen participating NMIs or DIs were predominantly based on either stand-alone mass balance (summation of impurities) or qNMR approaches, or the combination of data obtained using both methods. The results obtained using thermal methods based on freezing-point depression methods were also reported by a limited number of participants. There was excellent agreement between assignments obtained using all three approaches to assign the BPA content.
The assignment of the values for the mass fraction content of BPA consistent with the KCRV was achieved by most of the comparison participants with an associated relative standard uncertainty in the assigned value in the range (0.1 - 0.5)%.
The MaterialDigital initiative represents a major driver toward the digitalization of material science. Next to providing a prototypical infrastructure required for building a shared data space and working on semantic interoperability of data, a core focus area of the Platform MaterialDigital (PMD) is the utilization of workflows to encapsulate data processing and simulation steps in accordance with findable, accessible, interoperable, and reusable principles. In collaboration with the funded projects of the initiative, the workflow working group strives to establish shared standards, enhancing the interoperability and reusability of scientific data processing steps. Central to this effort is the Workflow Store, a pivotal tool for disseminating workflows with the community, facilitating the exchange and replication of scientific methodologies. This article discusses the inherent challenges of adapting workflow concepts, providing the perspective on developing and using workflows in the respective domain of the various funded projects. Additionally, it introduces the Workflow Store’s role within the initiative and outlines a future roadmap for the PMD workflow group, aiming to further refine and expand the role of scientific workflows as a means to advance digital transformation and foster collaborative research within material science.
Segregation of alloying elements and impurities at grain boundaries (GBs) critically influences material behaviour by affecting cohesion. In this study, we present an ab initio high-throughput evaluation of segregation energies and cohesive effects for all elements up to Z=92 in the periodic table (Z = 1–92, H–U) across the substitutional sites in six model ferritic iron GBs using density functional theory (DFT). From these data, we construct comprehensive elemental maps for solute segregation tendencies and cohesion at GBs, providing guidance for segregation engineering. We systematically assess the cohesive effects of different elements in all segregating positions along multiple fracture paths with a quantum-chemistry bond-order method as well as a modified Rice–Thomson–Wang theory of interfacial cohesion. The effects of segregants on the cohesion of GBs are shown to vary drastically as a function of site character, and hence their induced cohesive effects must
be considered as a thermodynamic average over the spectral energy distribution. Thus, models that overlook these aspects may fail to accurately predict the impacts of varying alloying concentrations, thermal processing conditions, or GB types. The insights presented here, along with our accompanying dataset, are expected to advance our understanding of GB segregation in steels and other materials.