Open Access

The 2010 CCQM-K79 'Comparison of value-assigned CRMs and PT materials: Ethanol in aqueous media' is the second key comparison directly testing the chemical measurement services provided to customers by National Metrology Institutes (NMIs) and Designated Institutes (DIs). CCQM-K79 compared the assigned ethanol values of proficiency test (PT) and certified reference materials (CRMs) using measurements made on these materials under repeatability conditions. Nine NMIs submitted 27 CRM or value-assigned PT materials for evaluation. These materials represent many of the higher-order reference materials then available for this commercially and forensically important measurand. The assigned ethanol mass fraction in the materials ranged from 0.1 mg/kg to 334 mg/kg. All materials were stored and prepared according the specifications provided by each NMI. Samples were processed and analyzed under repeatability conditions by one analytical team using a gas chromatography with flame ionization detection (GC-FID) method of demonstrated trueness and precision. Given the number of materials and the time required for each analysis, the majority of the measurements were made in two measurement campaigns ('runs'). Due to a shipping delay from one NMI, an unanticipated third campaign was required. In all three campaigns, replicate analyses (three injections of one preparation separated in time) were made for one randomly selected unit of each of the 27 materials. Nine of the 27 materials were gravimetrically diluted before measurement to provide solutions with ethanol mass fraction in the established linear range of the GC-FID method. The repeatability measurement value for each analyzed solution was estimated as the mean of all replicate values. The within- and between-campaign variance components were estimated using one-way ANOVA. Markov Chain Monte Carlo Bayesian analysis was used to estimate 95% level-of-confidence coverage intervals for the mean values. Uncertainty-weighted generalized distance regression was used to establish the key comparison reference function (KCRF) relating the assigned values to the repeatability measurements. On the basis of leave-one-out cross-validation, all of the assigned values for all 27 materials were deemed equivalent at the 95% level of confidence. These materials were used to define the KCRF. Parametric bootstrap Monte Carlo was used to estimate 95% level-of-confidence coverage intervals for the degrees of equivalence of materials, d ± U95(d), and of the participating NMIs, D ± U95(D). Because of the very wide range of ethanol mass fraction in the materials, these degrees of equivalence are expressed in percent relative form: %d ± U95(%d) and %D ± U95(%D). The median of the absolute values of the %D for the participating NMIs is less than 0.05% with a median U95(%D) of less than 1%. These results demonstrate that the participating NMIs have the ability to correctly value-assign CRMs and proficiency test materials for ethanol in aqueous media and similar measurands.

The identification of process-structure-property relationships of materials inevitably requires the combination of research data from different measurements. Therefore, the concepts related to FAIR (findable, accessible, interoperable, reusable) data handling, increasingly reported in literature, are particularly important in the materials science and engineering domain. However, they have not yet been integrated into a single, overarching methodological framework, particularly for reference data. Here, we introduce such a framework. Our concept covers data generation, documentation, handling, storage, sharing, data search and discovery, retrieval, and usage. Furthermore, we prototypically implement it using a real dataset with creep data of a single-crystal CMSX-6 Ni-based superalloy. The presented implementation is traceable and permanently accessible through open repositories. The individual elements considered in the framework ensure the functionality and usability of the data and, thus, the adherence to the FAIR principles. In conjunction with this, we present a definition for reference data of materials. Our definition underlines particularly the importance of a comprehensive documentation, e.g., on material provenance, data processing procedures, and the software and hardware used, including software-specific input parameters, as these details enable data users or independent parties to assess the quality of the datasets and to reuse and reproduce the results. Reference data that is managed according to the proposed framework can be used to advance knowledge in the materials science and engineering domain, e.g., by identifying new process-structure-property relations.

In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.