Nanoindentation is a widely used surface technique to measure mechanical properties of materials at small scale [1]. Recently, high-speed indentation is becoming more popular as real-time, in-line, and online testing are used to collect large datasets, on the load-depth response of materials, samples, and (also intermediate) products for quality control and quick manufacturing characterization of test specimens. Such approach can be for example extremely relevant to gain further insights into the process–structure–property correlations of highly heterogeneous materials [2]. However, large amount of data is usually generated during such experiments, requiring in parallel metadata storage for reproduction and reuse of such information. Indeed, in addition to the traditional nanoindentation approach of storing only the calibrated load–displacement curve, the metadata contain all the information on the sample, user, environmental conditions, calibration procedure and related data, raw data, analysis process and finally the analyzed data. In this way, a new data management strategy designed for nanoindentation results must be developed. To tackle this challenge, the EU H2020 RIA funded project NanoMECommons (Grant Agreement 952869) has started in February 2021 [3]. With a consortium of 19 partners (11 from industry and 8 academia and research), coming from 10 countries and led by the National Technical University of Athens (NTUA), this project focuses on employing innovative nano-scale mechanical testing procedures in real industrial environments, by developing harmonised and widely accepted characterisation methods, with reduced measurement discrepancy, and improved interoperability and traceability of data. In this context, Ansys Inc. has been implementing a centralized materials information management platform to capture characterization data and protocols (experimental and virtual), ensuring FAIR principles for the project data and protocols [4-5]. It will also establish (a) software tools for complex data handling for characterization, model calibration and validation, and their availability through digitalized workflows and (b) a reference database for selection of materials and related protocols for reduced time to market, and improved resource efficiency. For the current presentation, the current database structure and workflows to capture nanoindentation data will be presented and discussed [6].

References

[1] N. Romanos et al., “Innovative Data Management in advanced characterization: Implications for materials

design”, 2019, https://doi.org/10.1016/j.mtcomm.2019.100541

[2] H. Besharatloo, J.M. Wheeler, “Influence of indentation size and spacing on statistical phase analysis via highspeed nanoindentation mapping of metal alloys.” Journal of Materials Research 36, 2198–2212 (2021).

https://doi.org/10.1557/s43578-021-00214-5

[3] https://www.nanomecommons.net/

[4] https://www.go-fair.org/fair-principles/

[5] https://www.ansys.com/products/materials/granta-mi

[6] https://www.nanomecommons.net/public-documents/publications/